test: remove Turnstile widget dependency from test mode

- Add LTV unhedged column before LTV hedged column
- Update both render_result and render_job_result tables
- Show both hedged and unhedged LTV for comparison

.env.example

@@ -1,4 +1,9 @@
 APP_HOST=0.0.0.0
 APP_PORT=8000
+# For local development, docker-compose maps host port 8100 -> container port 8000
+# This avoids conflicts with other services on port 8000
 REDIS_URL=redis://localhost:6379
 CONFIG_PATH=/app/config/settings.yaml
+TURNSTILE_SITE_KEY=1x00000000000000000000AA
+TURNSTILE_SECRET_KEY=1x0000000000000000000000000000000AA
+DATABENTO_API_KEY=db-your-api-key-here

.forgejo/workflows/deploy.yaml

@@ -1,155 +0,0 @@
-name: Build and Deploy
-
-on:
-  push:
-    branches: [main]
-  workflow_dispatch:
-
-env:
-  REGISTRY: ${{ vars.REGISTRY || '10.100.0.2:3000' }}
-  IMAGE_NAME: ${{ github.repository }}
-
-jobs:
-  lint:
-    runs-on: [linux, docker]
-    container:
-      image: catthehacker/ubuntu:act-latest
-    steps:
-      - uses: actions/checkout@v4
-      - name: Set up Python
-        uses: actions/setup-python@v5
-        with:
-          python-version: '3.12'
-      - name: Install dependencies
-        run: |
-          python -m pip install --upgrade pip
-          pip install ruff black
-      - name: Run ruff
-        run: ruff check app tests scripts
-      - name: Run black
-        run: black --check app tests scripts
-
-  test:
-    runs-on: [linux, docker]
-    container:
-      image: catthehacker/ubuntu:act-latest
-    steps:
-      - uses: actions/checkout@v4
-      - name: Set up Python
-        uses: actions/setup-python@v5
-        with:
-          python-version: '3.12'
-      - name: Install dependencies
-        run: |
-          set -x
-          python -m pip install --upgrade pip
-          pip install pytest pytest-asyncio httpx
-          pip install nicegui fastapi uvicorn yfinance polars pandas pydantic pyyaml
-          pip list
-      - name: Run tests
-        run: pytest tests/test_pricing.py tests/test_strategies.py tests/test_portfolio.py -v --tb=short
-
-  type-check:
-    runs-on: [linux, docker]
-    container:
-      image: catthehacker/ubuntu:act-latest
-    steps:
-      - uses: actions/checkout@v4
-      - name: Set up Python
-        uses: actions/setup-python@v5
-        with:
-          python-version: '3.12'
-      - name: Install dependencies
-        run: |
-          set -x
-          python -m pip install --upgrade pip
-          pip install mypy
-          pip install nicegui fastapi uvicorn yfinance polars pandas pydantic pyyaml
-          pip list
-      - name: Show working directory
-        run: pwd && ls -la
-      - name: Run mypy
-        run: |
-          echo "Running mypy on core modules..."
-          mypy app/core app/models app/strategies app/services --ignore-missing-imports --show-error-codes --show-traceback || true
-          echo "Type check completed (warnings allowed during development)"
-
-  build:
-    runs-on: [linux, docker]
-    needs: [lint, test, type-check]
-    container:
-      image: catthehacker/ubuntu:act-latest
-    steps:
-      - uses: actions/checkout@v4
-
-      - name: Login to Docker Hub
-        uses: docker/login-action@v3
-        with:
-          registry: docker.io
-          username: ${{ vars.DOCKERHUB_USERNAME }}
-          password: ${{ secrets.DOCKERHUB_TOKEN }}
-
-      - name: Set up Docker Buildx
-        uses: docker/setup-buildx-action@v3
-        with:
-          driver: docker
-
-      - name: Login to Registry
-        uses: docker/login-action@v3
-        with:
-          registry: ${{ env.REGISTRY }}
-          username: ${{ github.actor }}
-          password: ${{ secrets.REGISTRY_PASSWORD || secrets.GITHUB_TOKEN }}
-
-      - name: Build and push
-        uses: docker/build-push-action@v5
-        with:
-          context: .
-          push: true
-          tags: |
-            ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:${{ github.sha }}
-            ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:latest
-          provenance: false
-
-  deploy:
-    runs-on: [linux, docker]
-    needs: build
-    if: github.ref == 'refs/heads/main'
-    container:
-      image: catthehacker/ubuntu:act-latest
-    env:
-      DEPLOY_HOST: ${{ vars.DEPLOY_HOST }}
-      DEPLOY_USER: ${{ vars.DEPLOY_USER || 'deploy' }}
-      DEPLOY_PORT: ${{ vars.DEPLOY_PORT || '22' }}
-      DEPLOY_PATH: ${{ vars.DEPLOY_PATH || '/opt/vault-dash' }}
-      DEPLOY_SSH_PRIVATE_KEY: ${{ secrets.DEPLOY_SSH_PRIVATE_KEY }}
-      APP_IMAGE: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:${{ github.sha }}
-      APP_ENV: production
-      APP_NAME: Vault Dashboard
-      APP_PORT: "8000"
-    steps:
-      - uses: actions/checkout@v4
-
-      - name: Install dependencies
-        run: |
-          apt-get update && apt-get install -y bash openssh-client curl docker.io
-          mkdir -p ~/.ssh
-          chmod 700 ~/.ssh
-
-      - name: Setup SSH key
-        run: |
-          # Handle base64-encoded key (recommended) or raw key
-          mkdir -p ~/.ssh && chmod 700 ~/.ssh
-          if echo "$DEPLOY_SSH_PRIVATE_KEY" | base64 -d > ~/.ssh/id_ed25519 2>/dev/null; then
-            echo "Decoded base64 key"
-          else
-            printf '%s\n' "$DEPLOY_SSH_PRIVATE_KEY" > ~/.ssh/id_ed25519
-          fi
-          chmod 600 ~/.ssh/id_ed25519
-          ssh-keyscan -p "${DEPLOY_PORT:-22}" "${DEPLOY_HOST}" >> ~/.ssh/known_hosts 2>/dev/null || true
-
-      - name: Deploy
-        run: |
-          test -n "$DEPLOY_HOST" || (echo "DEPLOY_HOST must be set" && exit 1)
-          test -n "$DEPLOY_SSH_PRIVATE_KEY" || (echo "DEPLOY_SSH_PRIVATE_KEY must be set" && exit 1)
-          bash scripts/deploy-forgejo.sh

.gitea/workflows/ci.yaml

@@ -24,32 +24,12 @@ jobs:
       - name: Install dependencies
         run: |
           python -m pip install --upgrade pip
-          pip install ruff black
+          pip install -r requirements-dev.txt
       - name: Run ruff
         run: ruff check app tests scripts
       - name: Run black
         run: black --check app tests scripts
 
-  test:
-    runs-on: [linux, docker]
-    container:
-      image: catthehacker/ubuntu:act-latest
-    steps:
-      - uses: actions/checkout@v4
-      - name: Set up Python
-        uses: actions/setup-python@v5
-        with:
-          python-version: '3.12'
-      - name: Install dependencies
-        run: |
-          set -x
-          python -m pip install --upgrade pip
-          pip install pytest pytest-asyncio httpx
-          pip install nicegui fastapi uvicorn yfinance polars pandas pydantic pyyaml
-          pip list
-      - name: Run tests
-        run: pytest tests/test_pricing.py tests/test_strategies.py tests/test_portfolio.py -v --tb=short
-
   type-check:
     runs-on: [linux, docker]
     container:
@@ -64,13 +44,31 @@ jobs:
         run: |
           set -x
           python -m pip install --upgrade pip
-          pip install mypy
+          pip install -r requirements-dev.txt
-          pip install nicegui fastapi uvicorn yfinance polars pandas pydantic pyyaml
           pip list
-      - name: Show working directory
-        run: pwd && ls -la
       - name: Run mypy
         run: |
           echo "Running mypy on core modules..."
-          mypy app/core app/models app/strategies app/services --ignore-missing-imports --show-error-codes --show-traceback || true
+          mypy app/core app/models app/strategies app/services app/domain --show-error-codes --show-traceback
-          echo "Type check completed (warnings allowed during development)"
+          echo "Type check completed successfully"
+
+  test:
+    runs-on: [linux, docker]
+    container:
+      image: mcr.microsoft.com/playwright:v1.58.0-noble
+    env:
+      APP_ENV: test
+    steps:
+      - uses: actions/checkout@v4
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.12'
+      - name: Install dependencies
+        run: |
+          set -x
+          python -m pip install --upgrade pip
+          pip install -r requirements-dev.txt
+          pip list
+      - name: Run tests
+        run: pytest -v --tb=short

.gitea/workflows/deploy.yaml

@@ -0,0 +1,103 @@
+name: Build and Deploy
+
+on:
+  workflow_run:
+    workflows: [CI]
+    types: [completed]
+    branches: [main]
+  workflow_dispatch:
+
+env:
+  REGISTRY: ${{ vars.REGISTRY || '10.100.0.2:3000' }}
+  IMAGE_NAME: ${{ github.repository }}
+  RESOLVED_SHA: ${{ github.event_name == 'workflow_run' && github.event.workflow_run.head_sha || github.sha }}
+  RESOLVED_REF: ${{ github.event_name == 'workflow_run' && github.event.workflow_run.head_branch || github.ref_name }}
+
+jobs:
+  build:
+    if: |
+      github.event_name == 'workflow_dispatch' ||
+      (github.event_name == 'workflow_run' && github.event.workflow_run.conclusion == 'success')
+    runs-on: [linux, docker]
+    container:
+      image: catthehacker/ubuntu:act-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+        with:
+          ref: ${{ env.RESOLVED_SHA }}
+      - name: Login to Docker Hub
+        uses: docker/login-action@v3
+        with:
+          registry: docker.io
+          username: ${{ vars.DOCKERHUB_USERNAME }}
+          password: ${{ secrets.DOCKERHUB_TOKEN }}
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+        with:
+          driver: docker
+      - name: Login to Registry
+        uses: docker/login-action@v3
+        with:
+          registry: ${{ env.REGISTRY }}
+          username: ${{ github.actor }}
+          password: ${{ secrets.REGISTRY_PASSWORD || secrets.GITHUB_TOKEN }}
+      - name: Build and push
+        uses: docker/build-push-action@v5
+        with:
+          context: .
+          push: true
+          tags: |
+            ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:${{ env.RESOLVED_SHA }}
+            ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:latest
+          provenance: false
+
+  deploy:
+    runs-on: [linux, docker]
+    needs: build
+    if: |
+      github.event_name == 'workflow_dispatch' ||
+      (github.event_name == 'workflow_run' && github.event.workflow_run.conclusion == 'success' && github.event.workflow_run.head_branch == 'main')
+    container:
+      image: catthehacker/ubuntu:act-latest
+      env:
+        DEPLOY_HOST: ${{ vars.DEPLOY_HOST }}
+        DEPLOY_USER: ${{ vars.DEPLOY_USER || 'deploy' }}
+        DEPLOY_PORT: ${{ vars.DEPLOY_PORT || '22' }}
+        DEPLOY_PATH: ${{ vars.DEPLOY_PATH || '/opt/vault-dash' }}
+        DEPLOY_SSH_PRIVATE_KEY: ${{ secrets.DEPLOY_SSH_PRIVATE_KEY }}
+        APP_IMAGE: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:${{ env.RESOLVED_SHA }}
+        APP_ENV: production
+        APP_NAME: Vault Dashboard
+        APP_PORT: "8000"
+        TURNSTILE_SITE_KEY: ${{ vars.TURNSTILE_SITE_KEY }}
+        TURNSTILE_SECRET_KEY: ${{ secrets.TURNSTILE_SECRET_KEY }}
+        DATABENTO_API_KEY: ${{ secrets.DATABENTO_API_KEY }}
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          ref: ${{ env.RESOLVED_SHA }}
+
+      - name: Install dependencies
+        run: |
+          apt-get update && apt-get install -y bash openssh-client curl
+          mkdir -p ~/.ssh
+          chmod 700 ~/.ssh
+
+      - name: Setup SSH key
+        run: |
+          # Handle base64-encoded key (recommended) or raw key
+          mkdir -p ~/.ssh && chmod 700 ~/.ssh
+          if echo "$DEPLOY_SSH_PRIVATE_KEY" | base64 -d > ~/.ssh/id_ed25519 2>/dev/null; then
+            echo "Decoded base64 key"
+          else
+            printf '%s\n' "$DEPLOY_SSH_PRIVATE_KEY" > ~/.ssh/id_ed25519
+          fi
+          chmod 600 ~/.ssh/id_ed25519
+          ssh-keyscan -p "${DEPLOY_PORT:-22}" "${DEPLOY_HOST}" >> ~/.ssh/known_hosts 2>/dev/null || true
+
+      - name: Deploy
+        run: |
+          test -n "$DEPLOY_HOST" || (echo "DEPLOY_HOST must be set" && exit 1)
+          test -n "$DEPLOY_SSH_PRIVATE_KEY" || (echo "DEPLOY_SSH_PRIVATE_KEY must be set" && exit 1)
+          bash scripts/deploy-actions.sh

.gitignore

@@ -4,5 +4,14 @@ __pycache__/
 .env
 config/secrets.yaml
 data/cache/
+data/workspaces/
+data/strategy_templates.json
 .idea/
 .vscode/
+.worktrees/
+tests/artifacts/
+secrets/
+.workspaces/
+.cache/
+uv.lock
+

.pre-commit-config.yaml

@@ -0,0 +1,27 @@
+# Pre-commit hooks for vault-dash
+# Install: pip install pre-commit && pre-commit install
+repos:
+  # Ruff - fast Python linter
+  - repo: https://github.com/astral-sh/ruff-pre-commit
+    rev: v0.15.8
+    hooks:
+      - id: ruff
+        args: [--fix, --exit-non-zero-on-fix]
+        files: ^(app|tests|scripts)/
+
+  # Black - Python formatter
+  - repo: https://github.com/psf/black
+    rev: 26.3.1
+    hooks:
+      - id: black
+        files: ^(app|tests|scripts)/
+        language_version: python3.12
+
+  # Type checking with mypy (optional, slower)
+  # Uncomment to enable:
+  # - repo: https://github.com/pre-commit/mirrors-mypy
+  #   rev: v1.15.0
+  #   hooks:
+  #     - id: mypy
+  #       args: [--ignore-missing-imports]
+  #       files: ^app/

.workspaces/83207143-b45c-4288-a1d2-c1363a54a020/backtest_settings.json

@@ -0,0 +1,23 @@
+{
+  "settings_id": "3e5143f6-29da-4416-8fca-edeaaac986ae",
+  "name": "Backtest 2020-01-01 - 2023-12-31",
+  "data_source": "databento",
+  "dataset": "XNAS.BASIC",
+  "schema": "ohlcv-1d",
+  "start_date": "2020-01-01",
+  "end_date": "2023-12-31",
+  "underlying_symbol": "GLD",
+  "start_price": 0.0,
+  "underlying_units": 1000.0,
+  "loan_amount": 0.0,
+  "margin_call_ltv": 0.75,
+  "template_slugs": [
+    "protective-put-atm-12m"
+  ],
+  "cache_key": "",
+  "data_cost_usd": 0.0,
+  "provider_ref": {
+    "provider_id": "synthetic_v1",
+    "pricing_mode": "synthetic_bs_mid"
+  }
+}

.workspaces/b02f124a-9573-4259-8291-13516c8e4cb9/backtest_settings.json

@@ -0,0 +1,23 @@
+{
+  "settings_id": "a48fe9fe-90d0-4cfc-a78f-a8db01cbf4d4",
+  "name": "Backtest 2020-01-01 - 2023-12-31",
+  "data_source": "databento",
+  "dataset": "XNAS.BASIC",
+  "schema": "ohlcv-1d",
+  "start_date": "2020-01-01",
+  "end_date": "2023-12-31",
+  "underlying_symbol": "GLD",
+  "start_price": 0.0,
+  "underlying_units": 1000.0,
+  "loan_amount": 0.0,
+  "margin_call_ltv": 0.75,
+  "template_slugs": [
+    "protective-put-atm-12m"
+  ],
+  "cache_key": "",
+  "data_cost_usd": 0.0,
+  "provider_ref": {
+    "provider_id": "synthetic_v1",
+    "pricing_mode": "synthetic_bs_mid"
+  }
+}

.workspaces/ea5841e7-36e5-4faf-8f90-77c3a8fd6311/backtest_settings.json

@@ -0,0 +1,23 @@
+{
+  "settings_id": "23d8dd8b-1798-45c7-855f-415c04355477",
+  "name": "Backtest 2020-01-01 - 2023-12-31",
+  "data_source": "databento",
+  "dataset": "XNAS.BASIC",
+  "schema": "ohlcv-1d",
+  "start_date": "2020-01-01",
+  "end_date": "2023-12-31",
+  "underlying_symbol": "GLD",
+  "start_price": 0.0,
+  "underlying_units": 1000.0,
+  "loan_amount": 0.0,
+  "margin_call_ltv": 0.75,
+  "template_slugs": [
+    "protective-put-atm-12m"
+  ],
+  "cache_key": "",
+  "data_cost_usd": 0.0,
+  "provider_ref": {
+    "provider_id": "synthetic_v1",
+    "pricing_mode": "synthetic_bs_mid"
+  }
+}

AGENTS.md

@@ -0,0 +1,197 @@
+policy:
+  subagent_usage:
+    required: true
+    rules:
+      - prefer sub-agents for parallelizable implementation work
+      - use sub-agents when implementing independent roadmap items
+      - create worktrees for sub-agents working on the same codebase
+      - review sub-agent output before merging to main
+      - use `agent: implementation-reviewer` for code quality checks
+      - use `agent: qa-validator` for end-to-end validation
+      - chain sub-agents for multi-step workflows (plan → implement → review)
+      - always use sub-agents unless the task is trivial or requires direct interaction
+
+  test_loop:
+    required: true
+    rules:
+      - run the app locally after changes
+      - run real tests against the running app
+      - for UI work, prefer Playwright/browser-visible checks
+      - verify the exact changed route/page
+
+  local_first:
+    required: true
+    rules:
+      - use local Docker/OrbStack before deploy
+      - deploy only after local behavior is verified
+
+  confidence:
+    rules:
+      - browser-visible behavior beats log-only confidence
+      - do not treat returned HTML as success if the page still has runtime/UI errors
+      - do not claim a feature is live unless the rendered UI consumes it
+
+  development_flow:
+    tdd: [red, orange, green]
+    build_rule:
+      - make build must enforce lint first
+      - if build is green, lint is already green
+
+  review:
+    required_before_merge: true
+    install_tool: review_install_agents
+    rules:
+      - install review agents with the review_install_agents tool before running the review workflow if needed
+      - use the full parallel review flow before merging worktree or sub-agent changes to main
+      - do not merge based only on compile/test results
+
+  backlog:
+    review_after_each_sprint: true
+    source_of_truth:
+      - docs/roadmap/ROADMAP.yaml
+      - docs/roadmap/backlog
+      - docs/roadmap/in-progress
+      - docs/roadmap/done
+      - docs/roadmap/blocked
+      - docs/roadmap/cancelled
+    rules:
+      - add newly discovered backlog items
+      - reorder priorities and dependencies based on new knowledge
+      - capture follow-up work explicitly
+
+  compatibility:
+    rules:
+      - preserve shared domain compatibility across parallel worktrees
+      - LombardPortfolio must remain available for strategy/core compatibility until intentionally removed everywhere
+
+learnings:
+  nicegui:
+    - ui.header must be a top-level page layout element
+    - do not nest ui.header inside ui.column or similar containers
+
+  options_page:
+    - loading all expiries/chains before first paint can make the page appear broken
+    - render fast first, then load incrementally
+
+  nicegui_fastapi:
+    - pages should not assume request.app.state is the right access path for shared services
+    - prefer an explicit runtime/service registry
+
+  docker_dev:
+    - do not mount the whole repo over /app when the image contains required runtime scripts
+    - prefer narrower mounts like ./app and ./config
+
+validation_checklist:
+  - local Docker stack starts cleanly
+  - /health returns OK
+  - changed page opens in browser automation
+  - no visible 500/runtime error
+  - screenshot artifact captured when useful
+  - relevant logs checked
+
+gitea_ci:
+  repo:
+    base_url: "http://tea.uncloud.vpn"
+    api_base_url: "http://tea.uncloud.vpn/api/v1"
+    owner: "bu5hm4nn"
+    name: "vault-dash"
+    full_name: "bu5hm4nn/vault-dash"
+    ssh_remote: "ssh://git@tea.uncloud.vpn:2223/bu5hm4nn/vault-dash.git"
+  auth:
+    preferred_method: "tea login"
+    notes:
+      - "`tea` is already logged in for this repo and should be preferred for API access"
+      - "`tea api` works against this Gitea 1.25.5 instance even when higher-level `tea actions` commands are unavailable"
+      - A raw token may exist separately, but automation should not assume one unless the user says so
+    shell_setup: |
+      export GITEA_URL="${GITEA_URL:-http://tea.uncloud.vpn}"
+      export GITEA_API="${GITEA_API:-$GITEA_URL/api/v1}"
+      export GITEA_REPO="bu5hm4nn/vault-dash"
+      tea login list >/dev/null
+      command -v jq >/dev/null
+  triage:
+    preferred_method: "use `tea api` for run/job/log discovery; use the Gitea web UI as fallback"
+    tested_on: "2026-04-07"
+    tested_behavior:
+      - "`tea actions runs list` refuses to run because the server is older than 1.26.0"
+      - "`tea api` works and authenticates via the stored tea login"
+      - Gitea 1.25.5 exposes Actions run, job, log, workflow, artifact, and runner endpoints in swagger
+      - The new server supports `/repos/{owner}/{repo}/actions/runs/{run}/jobs` and `/repos/{owner}/{repo}/actions/jobs/{job_id}/logs`
+    response_shape_note:
+      - Gitea Actions list endpoints return object wrappers such as `.workflow_runs` or `.jobs`
+      - In jq, prefer `(.workflow_runs // .)` for runs and `(.jobs // .)` for jobs
+    default_scope:
+      - Prefer latest run for `git rev-parse HEAD`
+      - If there is no run for HEAD yet, inspect the latest failed run on the current branch
+      - If CI failed, Build and Deploy will not run because deploy is triggered after CI success
+  query_recipes:
+    list_recent_runs_current_branch: |
+      branch="$(git branch --show-current)"
+      tea api -l tea.uncloud.vpn "/repos/bu5hm4nn/vault-dash/actions/runs?branch=$branch&limit=20"       | jq '(.workflow_runs // .) | map({id, workflow_id, status, event, head_branch, head_sha, created_at, html_url})'
+    latest_run_for_head_sha: |
+      branch="$(git branch --show-current)"
+      sha="$(git rev-parse HEAD)"
+      tea api -l tea.uncloud.vpn "/repos/bu5hm4nn/vault-dash/actions/runs?branch=$branch&limit=50"       | jq -r --arg sha "$sha" '((.workflow_runs // .) | map(select((.head_sha // .commit_sha) == $sha)) | sort_by(.created_at // .run_started_at // .id) | reverse | .[0])'
+    latest_failed_run_current_branch: |
+      branch="$(git branch --show-current)"
+      tea api -l tea.uncloud.vpn "/repos/bu5hm4nn/vault-dash/actions/runs?branch=$branch&status=failure&limit=20"       | jq -r '((.workflow_runs // .) | sort_by(.created_at // .run_started_at // .id) | reverse | .[0])'
+    list_jobs_for_run: |
+      run_id="<RUN_ID>"
+      tea api -l tea.uncloud.vpn "/repos/bu5hm4nn/vault-dash/actions/runs/$run_id/jobs"       | jq '(.jobs // .) | map({id, name, status, conclusion, started_at, completed_at})'
+    first_failed_job_for_run: |
+      run_id="<RUN_ID>"
+      tea api -l tea.uncloud.vpn "/repos/bu5hm4nn/vault-dash/actions/runs/$run_id/jobs"       | jq -r '((.jobs // .) | map(select((.conclusion // .status) == "failure" or .status == "failure")) | sort_by(.started_at // .id) | .[0])'
+    download_job_log: |
+      job_id="<JOB_ID>"
+      tea api -l tea.uncloud.vpn "/repos/bu5hm4nn/vault-dash/actions/jobs/$job_id/logs"
+  viewing_job_logs:
+    web_ui:
+      url: "http://tea.uncloud.vpn/bu5hm4nn/vault-dash/actions"
+      steps:
+        - Navigate to Actions tab in the Gitea UI
+        - Open the run from its `html_url` returned by `tea api`
+        - Expand the failing job (lint/test/type-check/build/deploy)
+        - Click the failed step to inspect detailed logs
+    api:
+      preferred_cli: "tea api"
+      notes:
+        - High-level `tea actions` commands may be version-gated by the CLI
+        - "`tea api` is the stable fallback for this Gitea instance"
+  workflows:
+    CI:
+      file: ".gitea/workflows/ci.yaml"
+      jobs: [lint, type-check, test]
+      triggers: [push main, pull_request main]
+    Build_and_Deploy:
+      file: ".gitea/workflows/deploy.yaml"
+      jobs: [build, deploy]
+      triggers:
+        - workflow_run after CI succeeds on main
+        - manual workflow_dispatch
+  common_failures:
+    missing_dependency:
+      symptom: "ModuleNotFoundError: No module named 'X'"
+      fix:
+        - Add runtime deps to requirements.txt
+        - Add dev/test tooling deps to requirements-dev.txt
+        - CI installs requirements-dev.txt, so keep CI-critical deps there
+    playwright_version_drift:
+      symptom: "Playwright browser/package mismatch or local vs CI behavior differs"
+      fix:
+        - Keep Python Playwright pinned in requirements-dev.txt
+        - Keep the pin aligned with `.gitea/workflows/ci.yaml` Playwright container image tag
+    tea_version_gate:
+      symptom: "`tea actions ...` says the server is older than 1.26.0"
+      fix: "Use `tea api` directly against the Actions endpoints instead of high-level tea subcommands"
+    type_error:
+      symptom: "error: Incompatible types..."
+      fix: "Run `mypy app/core app/models app/strategies app/services app/domain --show-error-codes --show-traceback` locally to reproduce"
+    test_failure:
+      symptom: "FAILED test_name"
+      fix: "Run failing test locally with `pytest -xvs <test_path_or_nodeid>`"
+
+pre_merge_checklist:
+  - run `pytest tests/ -v --tb=short` locally and ensure all new/changed tests pass
+  - run `/review` to get implementation review and QA validation
+  - verify CI passes on Gitea (lint, test, type-check, build, deploy)
+  - address all review comments before merging to main

DEPLOYMENT.md

@@ -1,13 +1,13 @@
 # Deployment Guide
 
-This project uses Forgejo Actions for CI/CD, building a Docker image and deploying to a VPN-reachable VPS over SSH.
+This project uses Gitea Actions for CI/CD, building a Docker image and deploying to a VPN-reachable VPS over SSH.
 
 ## Overview
 
 Deployment workflow:
 
-1. **CI** (`.forgejo/workflows/ci.yaml`): Lint, test, type-check on every push
+1. **CI** (`.gitea/workflows/ci.yaml`): lint, test, type-check on every push
-2. **Deploy** (`.forgejo/workflows/deploy.yaml`): Build, scan, and deploy on main branch
+2. **Build and Deploy** (`.gitea/workflows/deploy.yaml`): build and deploy on `main` after CI succeeds, or manually via workflow dispatch
 
 ---
 
@@ -20,14 +20,15 @@ Deployment workflow:
 - SSH access via VPN
 - Python 3.11+ (for healthcheck script)
 
-### Forgejo Instance Setup
+### Gitea Instance Setup
 
-1. Enable Actions in Forgejo admin settings
+1. Enable Actions in Gitea admin settings
-2. Register a runner (or use Forgejo's built-in runner)
+2. Enable Actions for the repository
+3. Register an Actions runner
 
 ### Runner Setup
 
-Forgejo supports both built-in runners and self-hosted Docker runners. For Docker-in-Docker builds, ensure the runner has:
+Gitea Actions uses `act_runner`. For Docker-based builds, ensure the runner host has:
 
 - Docker installed and accessible
 - `docker` and `docker compose` commands available
@@ -35,34 +36,40 @@ Forgejo supports both built-in runners and self-hosted Docker runners. For Docke
 Example runner registration:
 
 ```bash
-# On your Forgejo server
+# On the runner host
-forgejo actions generate-runner-token > token.txt
+./act_runner register --no-interactive --instance http://tea.uncloud.vpn --token <registration-token>
-forgejo-runner register --instance-addr http://localhost:3000 --token $(cat token.txt)
+./act_runner daemon
-forgejo-runner daemon
 ```
 
+Repository, organization, and instance runner tokens can be created from the Gitea web UI under Actions runner settings.
+
 ---
 
 ## 2. Required Secrets
 
-Configure in **Settings → Secrets and variables → Actions**:
+Configure in **Settings → Secrets and variables → Actions**.
+
+### Secrets
 
 | Secret | Description |
 |--------|-------------|
 | `DEPLOY_SSH_PRIVATE_KEY` | SSH key for VPS access |
-| `DEPLOY_HOST` | VPS IP/hostname (VPN-reachable) |
-| `DEPLOY_USER` | Deploy user (default: `deploy`) |
-| `DEPLOY_PORT` | SSH port (default: 22) |
-| `DEPLOY_PATH` | Deploy path (default: `/opt/vault-dash`) |
-| `NICEGUI_STORAGE_SECRET` | Session secret |
 | `REGISTRY_PASSWORD` | Container registry token (if needed) |
+| `DOCKERHUB_TOKEN` | Docker Hub token |
+| `TURNSTILE_SECRET_KEY` | Turnstile secret key |
+| `DATABENTO_API_KEY` | Databento API key |
 
-### Optional Variables
+### Variables
 
 | Variable | Description |
 |----------|-------------|
+| `DEPLOY_HOST` | VPS IP/hostname (VPN-reachable) |
+| `DEPLOY_USER` | Deploy user (default: `deploy`) |
+| `DEPLOY_PORT` | SSH port (default: `22`) |
+| `DEPLOY_PATH` | Deploy path (default: `/opt/vault-dash`) |
 | `REGISTRY` | Container registry URL |
-| `EXTERNAL_HEALTHCHECK_URL` | Public health check URL |
+| `DOCKERHUB_USERNAME` | Docker Hub username |
+| `TURNSTILE_SITE_KEY` | Turnstile site key |
 
 ---
 
@@ -127,7 +134,7 @@ export DEPLOY_SSH_PRIVATE_KEY="$(cat ~/.ssh/deploy_key)"
 export APP_IMAGE="registry.example.com/vault-dash:latest"
 
 # Run deploy script
-bash scripts/deploy.sh
+bash scripts/deploy-actions.sh
 ```
 
 ---
@@ -150,22 +157,12 @@ vault.uncloud.vpn {
 
 ---
 
-## 7. Future: OAuth Integration
+## 7. Troubleshooting
-
-When ready to expose publicly:
-
-1. Set up OAuth provider (Authentik, Keycloak, etc.)
-2. Configure `CORS_ORIGINS` for public URL
-3. Add OAuth middleware to FastAPI
-4. Enable HTTPS via Let's Encrypt
-
----
-
-## 8. Troubleshooting
 
 ### Runner can't build Docker images
 
 Ensure runner has Docker access:
+
 ```bash
 docker run --rm hello-world
 ```

Makefile

@@ -1,4 +1,4 @@
-.PHONY: install dev test build deploy
+.PHONY: install dev lint test build deploy cache-stats cache-clear cache-list
 
 install:
 	python3 -m venv .venv
@@ -7,11 +7,25 @@ install:
 dev:
 	. .venv/bin/activate && python -m uvicorn app.main:app --reload --host 0.0.0.0 --port 8000
 
+lint:
+	. .venv/bin/activate && ruff check app tests scripts
+	. .venv/bin/activate && black --check app tests scripts
+
 test:
 	. .venv/bin/activate && pytest
 
-build:
+build: lint
 	docker build -t vault-dash .
 
 deploy:
 	./scripts/deploy.sh
+
+# Cache management commands
+cache-stats:
+	. .venv/bin/activate && python scripts/cache_cli.py stats
+
+cache-list:
+	. .venv/bin/activate && python scripts/cache_cli.py list
+
+cache-clear:
+	. .venv/bin/activate && python scripts/cache_cli.py clear --yes

README.md

@@ -42,6 +42,37 @@ docker run -p 8000:8000 vault-dash
 docker-compose up -d
 ```
 
+### Turnstile configuration
+
+Workspace creation on the public welcome page is protected by Cloudflare Turnstile.
+
+Local and test environments may use Cloudflare's published test keys:
+
+```bash
+TURNSTILE_SITE_KEY=1x00000000000000000000AA
+TURNSTILE_SECRET_KEY=1x0000000000000000000000000000000AA
+```
+
+Negative-path testing can use the always-fail/blocked test keys:
+
+```bash
+TURNSTILE_SITE_KEY=2x00000000000000000000AB
+TURNSTILE_SECRET_KEY=2x0000000000000000000000000000000AA
+```
+
+Production must provide real keys via environment variables:
+
+```bash
+TURNSTILE_SITE_KEY=...
+TURNSTILE_SECRET_KEY=...
+```
+
+In Forgejo deployment:
+- `vars.TURNSTILE_SITE_KEY` provides the public site key
+- `secrets.TURNSTILE_SECRET_KEY` provides the server-side secret key
+
+Browser tests run with `APP_ENV=test` and the Turnstile test keys.
+
 ## Architecture
 
 ```

app/backtesting/__init__.py

@@ -0,0 +1,5 @@
+"""Backtesting subsystem for historical hedge simulation."""
+
+from .engine import SyntheticBacktestEngine
+
+__all__ = ["SyntheticBacktestEngine"]

app/backtesting/engine.py

@@ -0,0 +1,167 @@
+from __future__ import annotations
+
+from dataclasses import dataclass
+
+from app.models.backtest import (
+    BacktestDailyPoint,
+    BacktestScenario,
+    BacktestSummaryMetrics,
+    TemplateBacktestResult,
+)
+from app.models.strategy_template import StrategyTemplate
+from app.services.backtesting.historical_provider import (
+    BacktestHistoricalProvider,
+    DailyClosePoint,
+    HistoricalOptionPosition,
+)
+
+
+@dataclass
+class OpenSyntheticPosition(HistoricalOptionPosition):
+    pass
+
+
+class SyntheticBacktestEngine:
+    def __init__(self, provider: BacktestHistoricalProvider) -> None:
+        self.provider = provider
+
+    def run_template(
+        self,
+        scenario: BacktestScenario,
+        template: StrategyTemplate,
+        history: list[DailyClosePoint],
+    ) -> TemplateBacktestResult:
+        start_day = history[0]
+        cash_balance = scenario.initial_portfolio.cash_balance
+        total_hedge_cost = 0.0
+        total_option_payoff_realized = 0.0
+        warnings: list[str] = []
+        open_positions = self._open_positions(scenario, template, history, start_day)
+        opening_cost = sum(position.entry_price * position.quantity for position in open_positions)
+        cash_balance -= opening_cost
+        total_hedge_cost += opening_cost
+
+        daily_points: list[BacktestDailyPoint] = []
+        for day in history:
+            premium_cashflow = -opening_cost if day.date == start_day.date else 0.0
+            realized_option_cashflow = 0.0
+            option_market_value = 0.0
+            active_position_ids: list[str] = []
+            remaining_positions: list[HistoricalOptionPosition] = []
+
+            for position in open_positions:
+                valuation = self.provider.mark_position(
+                    position,
+                    symbol=scenario.symbol,
+                    as_of_date=day.date,
+                    spot=day.close,
+                )
+                self._append_warning(warnings, valuation.warning)
+                if not valuation.is_active:
+                    cash_balance += valuation.realized_cashflow
+                    realized_option_cashflow += valuation.realized_cashflow
+                    total_option_payoff_realized += valuation.realized_cashflow
+                    continue
+
+                option_market_value += valuation.mark * position.quantity
+                active_position_ids.append(position.position_id)
+                remaining_positions.append(position)
+
+            open_positions = remaining_positions
+
+            # Use closing price for portfolio value calculations
+            underlying_value_close = scenario.initial_portfolio.underlying_units * day.close
+            net_portfolio_value_close = underlying_value_close + option_market_value + cash_balance
+
+            # Use day's low for margin call evaluation (worst case during the day)
+            # If low is not available, fall back to close
+            worst_price = day.low if day.low is not None else day.close
+            underlying_value_worst = scenario.initial_portfolio.underlying_units * worst_price
+            net_portfolio_value_worst = underlying_value_worst + option_market_value + cash_balance
+
+            # LTVs for display (end-of-day at close)
+            ltv_unhedged = scenario.initial_portfolio.loan_amount / underlying_value_close
+            ltv_hedged = scenario.initial_portfolio.loan_amount / net_portfolio_value_close
+
+            # Margin calls use worst-case (low price) scenario
+            ltv_unhedged_worst = scenario.initial_portfolio.loan_amount / underlying_value_worst
+            ltv_hedged_worst = scenario.initial_portfolio.loan_amount / net_portfolio_value_worst
+
+            # Total option contracts held
+            option_contracts = sum(p.quantity for p in open_positions)
+
+            daily_points.append(
+                BacktestDailyPoint(
+                    date=day.date,
+                    spot_close=day.close,
+                    spot_open=day.open if day.open is not None else day.close,
+                    spot_low=day.low if day.low is not None else day.close,
+                    spot_high=day.high if day.high is not None else day.close,
+                    underlying_value=underlying_value_close,
+                    option_market_value=option_market_value,
+                    premium_cashflow=premium_cashflow,
+                    realized_option_cashflow=realized_option_cashflow,
+                    net_portfolio_value=net_portfolio_value_close,
+                    loan_amount=scenario.initial_portfolio.loan_amount,
+                    ltv_unhedged=ltv_unhedged,
+                    ltv_hedged=ltv_hedged,
+                    margin_call_unhedged=ltv_unhedged_worst >= scenario.initial_portfolio.margin_call_ltv,
+                    margin_call_hedged=ltv_hedged_worst >= scenario.initial_portfolio.margin_call_ltv,
+                    option_contracts=option_contracts,
+                    active_position_ids=tuple(active_position_ids),
+                )
+            )
+
+        margin_call_days_unhedged = sum(1 for point in daily_points if point.margin_call_unhedged)
+        margin_call_days_hedged = sum(1 for point in daily_points if point.margin_call_hedged)
+        summary = BacktestSummaryMetrics(
+            start_value=scenario.initial_portfolio.start_value,
+            end_value_unhedged=daily_points[-1].underlying_value,
+            end_value_hedged_net=daily_points[-1].net_portfolio_value,
+            total_hedge_cost=total_hedge_cost,
+            total_option_payoff_realized=total_option_payoff_realized,
+            max_ltv_unhedged=max(point.ltv_unhedged for point in daily_points),
+            max_ltv_hedged=max(point.ltv_hedged for point in daily_points),
+            margin_call_days_unhedged=margin_call_days_unhedged,
+            margin_call_days_hedged=margin_call_days_hedged,
+            margin_threshold_breached_unhedged=margin_call_days_unhedged > 0,
+            margin_threshold_breached_hedged=margin_call_days_hedged > 0,
+        )
+        return TemplateBacktestResult(
+            template_slug=template.slug,
+            template_id=template.template_id,
+            template_version=template.version,
+            template_name=template.display_name,
+            summary_metrics=summary,
+            daily_path=tuple(daily_points),
+            warnings=tuple(warnings),
+        )
+
+    def _open_positions(
+        self,
+        scenario: BacktestScenario,
+        template: StrategyTemplate,
+        history: list[DailyClosePoint],
+        start_day: DailyClosePoint,
+    ) -> list[HistoricalOptionPosition]:
+        positions: list[HistoricalOptionPosition] = []
+        for index, leg in enumerate(template.legs, start=1):
+            positions.append(
+                self.provider.open_position(
+                    symbol=scenario.symbol,
+                    leg=leg,
+                    position_id=f"{template.slug}-position-{index}",
+                    quantity=(
+                        scenario.initial_portfolio.underlying_units * leg.allocation_weight * leg.target_coverage_pct
+                    ),
+                    as_of_date=start_day.date,
+                    spot=start_day.close,
+                    trading_days=history,
+                )
+            )
+        return positions
+
+    @staticmethod
+    def _append_warning(warnings: list[str], warning: str | None) -> None:
+        if warning and warning not in warnings:
+            warnings.append(warning)

app/components/strategy_panel.py

@@ -4,6 +4,12 @@ from typing import Any
 
 from nicegui import ui
 
+from app.domain.portfolio_math import (
+    strategy_benefit_per_unit,
+    strategy_protection_floor_bounds,
+    strategy_upside_cap_price,
+)
+
 
 class StrategyComparisonPanel:
     """Interactive strategy comparison with scenario slider and cost-benefit table."""
@@ -107,8 +113,6 @@ class StrategyComparisonPanel:
         for strategy in self.strategies:
             name = str(strategy.get("name", "strategy")).replace("_", " ").title()
             cost = float(strategy.get("estimated_cost", 0.0))
-            floor = strategy.get("max_drawdown_floor", "—")
-            cap = strategy.get("upside_cap", "—")
             scenario = self._scenario_benefit(strategy)
             scenario_class = (
                 "text-emerald-600 dark:text-emerald-400" if scenario >= 0 else "text-rose-600 dark:text-rose-400"
@@ -117,8 +121,8 @@ class StrategyComparisonPanel:
                 <tr class=\"border-b border-slate-200 dark:border-slate-800\">
                     <td class=\"px-4 py-3 font-medium text-slate-900 dark:text-slate-100\">{name}</td>
                     <td class=\"px-4 py-3 text-slate-600 dark:text-slate-300\">${cost:,.2f}</td>
-                    <td class=\"px-4 py-3 text-slate-600 dark:text-slate-300\">{self._fmt_optional_money(floor)}</td>
+                    <td class=\"px-4 py-3 text-slate-600 dark:text-slate-300\">{self._format_floor(strategy)}</td>
-                    <td class=\"px-4 py-3 text-slate-600 dark:text-slate-300\">{self._fmt_optional_money(cap)}</td>
+                    <td class=\"px-4 py-3 text-slate-600 dark:text-slate-300\">{self._format_cap(strategy)}</td>
                     <td class=\"px-4 py-3 font-semibold {scenario_class}\">${scenario:,.2f}</td>
                 </tr>
                 """)
@@ -140,17 +144,26 @@ class StrategyComparisonPanel:
         """
 
     def _scenario_benefit(self, strategy: dict[str, Any]) -> float:
-        scenario_spot = self._scenario_spot()
+        return strategy_benefit_per_unit(
-        cost = float(strategy.get("estimated_cost", 0.0))
+            strategy,
-        floor = strategy.get("max_drawdown_floor")
+            current_spot=self.current_spot,
-        cap = strategy.get("upside_cap")
+            scenario_spot=self._scenario_spot(),
-        benefit = -cost
+        )
 
-        if isinstance(floor, (int, float)) and scenario_spot < float(floor):
+    def _format_floor(self, strategy: dict[str, Any]) -> str:
-            benefit += float(floor) - scenario_spot
+        bounds = strategy_protection_floor_bounds(strategy, current_spot=self.current_spot)
-        if isinstance(cap, (int, float)) and scenario_spot > float(cap):
+        if bounds is None:
-            benefit -= scenario_spot - float(cap)
+            return self._fmt_optional_money(strategy.get("max_drawdown_floor"))
-        return benefit
+        low, high = bounds
+        if abs(high - low) < 1e-9:
+            return f"${high:,.2f}"
+        return f"${low:,.2f}–${high:,.2f}"
+
+    def _format_cap(self, strategy: dict[str, Any]) -> str:
+        cap = strategy_upside_cap_price(strategy, current_spot=self.current_spot)
+        if cap is None:
+            return self._fmt_optional_money(strategy.get("upside_cap"))
+        return f"${cap:,.2f}"
 
     @staticmethod
     def _fmt_optional_money(value: Any) -> str:

app/core/calculations.py

@@ -1,7 +1,14 @@
 from __future__ import annotations
 
-from collections.abc import Iterable
+from collections.abc import Iterable, Mapping
+from datetime import date, datetime
 
+from app.core.pricing.black_scholes import (
+    DEFAULT_RISK_FREE_RATE,
+    DEFAULT_VOLATILITY,
+    BlackScholesInputs,
+    black_scholes_price_and_greeks,
+)
 from app.models.option import OptionContract
 from app.models.portfolio import LombardPortfolio
 from app.models.strategy import HedgingStrategy
@@ -96,3 +103,74 @@ def portfolio_net_equity(
         hedge_cost=hedge_cost,
         option_payoff_value=payoff_value,
     )
+
+
+_ZERO_GREEKS = {"delta": 0.0, "gamma": 0.0, "theta": 0.0, "vega": 0.0, "rho": 0.0}
+
+
+def option_row_greeks(
+    row: Mapping[str, object],
+    underlying_price: float,
+    *,
+    risk_free_rate: float = DEFAULT_RISK_FREE_RATE,
+    valuation_date: date | None = None,
+) -> dict[str, float]:
+    """Calculate Black-Scholes Greeks for an option-chain row.
+
+    Prefers live implied volatility when available. If it is missing or invalid,
+    a conservative default volatility is used. Invalid or expired rows return
+    zero Greeks instead of raising.
+    """
+    if underlying_price <= 0:
+        return dict(_ZERO_GREEKS)
+
+    strike_raw = row.get("strike", 0.0)
+    strike = float(strike_raw) if isinstance(strike_raw, (int, float)) else 0.0
+    if strike <= 0:
+        return dict(_ZERO_GREEKS)
+
+    option_type = str(row.get("type", "")).lower()
+    if option_type not in {"call", "put"}:
+        return dict(_ZERO_GREEKS)
+
+    expiry_raw = row.get("expiry")
+    if not isinstance(expiry_raw, str) or not expiry_raw:
+        return dict(_ZERO_GREEKS)
+
+    try:
+        expiry = datetime.fromisoformat(expiry_raw).date()
+    except ValueError:
+        return dict(_ZERO_GREEKS)
+
+    valuation = valuation_date or date.today()
+    days_to_expiry = (expiry - valuation).days
+    if days_to_expiry <= 0:
+        return dict(_ZERO_GREEKS)
+
+    iv_raw = row.get("impliedVolatility", 0.0) or 0.0
+    implied_volatility = float(iv_raw) if isinstance(iv_raw, (int, float)) else 0.0
+    volatility = implied_volatility if implied_volatility > 0 else DEFAULT_VOLATILITY
+
+    # option_type is validated to be in {"call", "put"} above, so it's safe to pass
+    try:
+        pricing = black_scholes_price_and_greeks(
+            BlackScholesInputs(
+                spot=underlying_price,
+                strike=strike,
+                time_to_expiry=days_to_expiry / 365.0,
+                risk_free_rate=risk_free_rate,
+                volatility=volatility,
+                option_type=option_type,  # type: ignore[arg-type]
+                valuation_date=valuation,
+            )
+        )
+    except ValueError:
+        return dict(_ZERO_GREEKS)
+
+    return {
+        "delta": pricing.delta,
+        "gamma": pricing.gamma,
+        "theta": pricing.theta,
+        "vega": pricing.vega,
+        "rho": pricing.rho,
+    }

app/domain/__init__.py

@@ -0,0 +1,51 @@
+from app.domain.backtesting_math import (
+    AssetQuantity,
+    PricePerAsset,
+    asset_quantity_from_floats,
+    asset_quantity_from_money,
+    materialize_backtest_portfolio_state,
+)
+from app.domain.instruments import (
+    asset_quantity_from_weight,
+    instrument_metadata,
+    price_per_weight_from_asset_price,
+    weight_from_asset_quantity,
+)
+from app.domain.portfolio_math import (
+    build_alert_context,
+    portfolio_snapshot_from_config,
+    resolve_portfolio_spot_from_quote,
+    strategy_metrics_from_snapshot,
+)
+from app.domain.units import (
+    BaseCurrency,
+    Money,
+    PricePerWeight,
+    Weight,
+    WeightUnit,
+    decimal_from_float,
+    to_decimal,
+)
+
+__all__ = [
+    "BaseCurrency",
+    "WeightUnit",
+    "Money",
+    "Weight",
+    "PricePerWeight",
+    "AssetQuantity",
+    "PricePerAsset",
+    "asset_quantity_from_money",
+    "asset_quantity_from_floats",
+    "materialize_backtest_portfolio_state",
+    "to_decimal",
+    "decimal_from_float",
+    "portfolio_snapshot_from_config",
+    "build_alert_context",
+    "resolve_portfolio_spot_from_quote",
+    "strategy_metrics_from_snapshot",
+    "instrument_metadata",
+    "price_per_weight_from_asset_price",
+    "weight_from_asset_quantity",
+    "asset_quantity_from_weight",
+]

app/domain/backtesting_math.py

@@ -0,0 +1,148 @@
+from __future__ import annotations
+
+from dataclasses import dataclass
+from decimal import Decimal
+
+from app.domain.units import BaseCurrency, Money, Weight, WeightUnit, _coerce_currency, decimal_from_float, to_decimal
+from app.models.backtest import BacktestPortfolioState
+from app.models.portfolio import PortfolioConfig
+
+
+@dataclass(frozen=True, slots=True)
+class AssetQuantity:
+    amount: Decimal
+    symbol: str
+
+    def __post_init__(self) -> None:
+        object.__setattr__(self, "amount", to_decimal(self.amount))
+        symbol = str(self.symbol).strip().upper()
+        if not symbol:
+            raise ValueError("Asset symbol is required")
+        object.__setattr__(self, "symbol", symbol)
+
+    def __mul__(self, other: object) -> Money:
+        if isinstance(other, PricePerAsset):
+            other.assert_symbol(self.symbol)
+            return Money(amount=self.amount * other.amount, currency=other.currency)
+        return NotImplemented
+
+    def __truediv__(self, other: object) -> AssetQuantity:
+        if isinstance(other, bool):
+            return NotImplemented
+        if isinstance(other, Decimal):
+            return AssetQuantity(amount=self.amount / other, symbol=self.symbol)
+        if isinstance(other, int):
+            return AssetQuantity(amount=self.amount / Decimal(other), symbol=self.symbol)
+        return NotImplemented
+
+
+@dataclass(frozen=True, slots=True)
+class PricePerAsset:
+    amount: Decimal
+    currency: BaseCurrency | str
+    symbol: str
+
+    def __post_init__(self) -> None:
+        amount = to_decimal(self.amount)
+        if amount < 0:
+            raise ValueError("PricePerAsset amount must be non-negative")
+        object.__setattr__(self, "amount", amount)
+        object.__setattr__(self, "currency", _coerce_currency(self.currency))
+        symbol = str(self.symbol).strip().upper()
+        if not symbol:
+            raise ValueError("Asset symbol is required")
+        object.__setattr__(self, "symbol", symbol)
+
+    @property
+    def _currency_typed(self) -> BaseCurrency:
+        """Type-narrowed currency accessor for internal use."""
+        return self.currency  # type: ignore[return-value]
+
+    def assert_symbol(self, symbol: str) -> PricePerAsset:
+        normalized = str(symbol).strip().upper()
+        if self.symbol != normalized:
+            raise ValueError(f"Asset symbol mismatch: {self.symbol} != {normalized}")
+        return self
+
+    def __mul__(self, other: object) -> Money | PricePerAsset:
+        if isinstance(other, bool):
+            return NotImplemented
+        if isinstance(other, AssetQuantity):
+            other_symbol = str(other.symbol).strip().upper()
+            self.assert_symbol(other_symbol)
+            return Money(amount=self.amount * other.amount, currency=self.currency)
+        if isinstance(other, Decimal):
+            return PricePerAsset(amount=self.amount * other, currency=self.currency, symbol=self.symbol)
+        if isinstance(other, int):
+            return PricePerAsset(amount=self.amount * Decimal(other), currency=self.currency, symbol=self.symbol)
+        return NotImplemented
+
+    def __rmul__(self, other: object) -> PricePerAsset:
+        if isinstance(other, bool):
+            return NotImplemented
+        if isinstance(other, Decimal):
+            return PricePerAsset(amount=self.amount * other, currency=self.currency, symbol=self.symbol)
+        if isinstance(other, int):
+            return PricePerAsset(amount=self.amount * Decimal(other), currency=self.currency, symbol=self.symbol)
+        return NotImplemented
+
+
+def asset_quantity_from_money(value: Money, spot: PricePerAsset) -> AssetQuantity:
+    value.assert_currency(spot._currency_typed)
+    if spot.amount <= 0:
+        raise ValueError("Spot price per asset must be positive")
+    return AssetQuantity(amount=value.amount / spot.amount, symbol=spot.symbol)
+
+
+def asset_quantity_from_floats(portfolio_value: float, entry_spot: float, symbol: str) -> float:
+    notional = Money(amount=decimal_from_float(portfolio_value), currency=BaseCurrency.USD)
+    spot = PricePerAsset(amount=decimal_from_float(entry_spot), currency=BaseCurrency.USD, symbol=symbol)
+    return float(asset_quantity_from_money(notional, spot).amount)
+
+
+def asset_quantity_from_workspace_config(config: PortfolioConfig, *, entry_spot: float, symbol: str) -> float:
+    if config.gold_ounces is not None and config.gold_ounces > 0:
+        try:
+            from app.domain.instruments import asset_quantity_from_weight
+
+            quantity = asset_quantity_from_weight(
+                symbol,
+                Weight(amount=decimal_from_float(float(config.gold_ounces)), unit=WeightUnit.OUNCE_TROY),
+            )
+            return float(quantity.amount)
+        except ValueError:
+            pass
+    if config.gold_value is not None:
+        return asset_quantity_from_floats(float(config.gold_value), entry_spot, symbol)
+    raise ValueError("Workspace config must provide collateral weight or value")
+
+
+def materialize_backtest_portfolio_state(
+    *,
+    symbol: str,
+    underlying_units: float,
+    entry_spot: float,
+    loan_amount: float,
+    margin_call_ltv: float,
+    currency: str = "USD",
+    cash_balance: float = 0.0,
+    financing_rate: float = 0.0,
+) -> BacktestPortfolioState:
+    normalized_symbol = str(symbol).strip().upper()
+    quantity = AssetQuantity(amount=decimal_from_float(underlying_units), symbol=normalized_symbol)
+    spot = PricePerAsset(
+        amount=decimal_from_float(entry_spot),
+        currency=BaseCurrency.USD,
+        symbol=normalized_symbol,
+    )
+    loan = Money(amount=decimal_from_float(loan_amount), currency=currency)
+    _ = quantity * spot
+    return BacktestPortfolioState(
+        currency=str(loan.currency),
+        underlying_units=float(quantity.amount),
+        entry_spot=float(spot.amount),
+        loan_amount=float(loan.amount),
+        margin_call_ltv=margin_call_ltv,
+        cash_balance=cash_balance,
+        financing_rate=financing_rate,
+    )

app/domain/conversions.py

@@ -0,0 +1,310 @@
+"""Display mode conversion utilities for GLD/XAU views.
+
+This module handles conversion between GLD share prices and physical gold prices
+based on the user's display mode preference.
+
+Key insight:
+- In GLD mode: show share prices directly, no conversion to oz
+- In XAU mode: convert GLD shares to oz-equivalent using expense-adjusted backing
+"""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+from datetime import date
+from decimal import Decimal
+
+from app.domain.instruments import gld_ounces_per_share
+from app.models.position import Position
+
+
+@dataclass(frozen=True)
+class DisplayContext:
+    """Context for display mode conversions.
+
+    Attributes:
+        mode: Display mode ("GLD" for shares, "XAU" for physical gold)
+        reference_date: Date for historical conversion lookups
+        gld_ounces_per_share: GLD backing ratio for the reference date
+    """
+
+    mode: str
+    reference_date: date | None = None
+    gld_ounces_per_share: Decimal | None = None
+
+    def __post_init__(self) -> None:
+        if self.mode not in {"GLD", "XAU"}:
+            raise ValueError(f"Invalid display mode: {self.mode!r}")
+
+    @classmethod
+    def create(cls, mode: str, reference_date: date | None = None) -> "DisplayContext":
+        """Create a display context with computed GLD backing ratio."""
+        gld_backing = None
+        if mode == "XAU" and reference_date is not None:
+            gld_backing = gld_ounces_per_share(reference_date)
+        return cls(mode=mode, reference_date=reference_date, gld_ounces_per_share=gld_backing)
+
+
+def is_gld_mode(display_mode: str) -> bool:
+    """Check if display mode is GLD (share view)."""
+    return display_mode == "GLD"
+
+
+def is_xau_mode(display_mode: str) -> bool:
+    """Check if display mode is XAU (physical gold view)."""
+    return display_mode == "XAU"
+
+
+def convert_position_to_display(
+    position: Position,
+    display_mode: str,
+    reference_date: date | None = None,
+) -> tuple[Decimal, str, Decimal]:
+    """Convert a position to display units based on display mode.
+
+    Args:
+        position: Position to convert
+        display_mode: "GLD" for shares, "XAU" for physical gold
+        reference_date: Date for historical conversion (for GLD->XAU)
+
+    Returns:
+        Tuple of (display_quantity, display_unit, display_entry_price)
+
+    Examples:
+        >>> # GLD position in GLD mode: show as-is
+        >>> from datetime import date
+        >>> from decimal import Decimal
+        >>> from app.models.position import create_position
+        >>> pos = create_position(
+        ...     underlying="GLD",
+        ...     quantity=Decimal("100"),
+        ...     unit="shares",
+        ...     entry_price=Decimal("400"),
+        ...     entry_date=date.today(),
+        ... )
+        >>> qty, unit, price = convert_position_to_display(pos, "GLD")
+        >>> qty, unit, price
+        (Decimal('100'), 'shares', Decimal('400'))
+
+        >>> # GLD position in XAU mode: convert to oz
+        >>> qty, unit, price = convert_position_to_display(pos, "XAU", date.today())
+        >>> # qty will be shares * oz_per_share
+    """
+    if display_mode == "GLD":
+        # GLD mode: show shares directly
+        if position.underlying == "GLD":
+            return position.quantity, position.unit, position.entry_price
+        # Non-GLD positions in GLD mode: would need conversion (not implemented yet)
+        return position.quantity, position.unit, position.entry_price
+
+    elif display_mode == "XAU":
+        # XAU mode: convert to physical gold ounces
+        if position.underlying == "GLD":
+            # Convert GLD shares to oz using expense-adjusted backing
+            backing = gld_ounces_per_share(reference_date or position.entry_date)
+            display_qty = position.quantity * backing
+            display_price = position.entry_price / backing  # Price per oz
+            return display_qty, "oz", display_price
+        # XAU positions already in oz
+        return position.quantity, position.unit, position.entry_price
+
+    else:
+        raise ValueError(f"Unsupported display mode: {display_mode!r}")
+
+
+def convert_price_to_display(
+    price: Decimal,
+    from_unit: str,
+    to_mode: str,
+    reference_date: date | None = None,
+) -> tuple[Decimal, str]:
+    """Convert a price to display mode units.
+
+    Args:
+        price: Price value to convert
+        from_unit: Source unit ("shares" or "oz")
+        to_mode: Target display mode ("GLD" or "XAU")
+        reference_date: Date for historical conversion
+
+    Returns:
+        Tuple of (converted_price, display_unit)
+    """
+    if to_mode == "GLD":
+        if from_unit == "shares":
+            return price, "shares"
+        elif from_unit == "oz":
+            # Convert oz price to share price
+            backing = gld_ounces_per_share(reference_date or date.today())
+            return price * backing, "shares"
+
+    elif to_mode == "XAU":
+        if from_unit == "oz":
+            return price, "oz"
+        elif from_unit == "shares":
+            # Convert share price to oz price
+            backing = gld_ounces_per_share(reference_date or date.today())
+            return price / backing, "oz"
+
+    raise ValueError(f"Unsupported conversion: {from_unit} -> {to_mode}")
+
+
+def convert_quantity_to_display(
+    quantity: Decimal,
+    from_unit: str,
+    to_mode: str,
+    reference_date: date | None = None,
+) -> tuple[Decimal, str]:
+    """Convert a quantity to display mode units.
+
+    Args:
+        quantity: Quantity value to convert
+        from_unit: Source unit ("shares" or "oz")
+        to_mode: Target display mode ("GLD" or "XAU")
+        reference_date: Date for historical conversion
+
+    Returns:
+        Tuple of (converted_quantity, display_unit)
+    """
+    if to_mode == "GLD":
+        if from_unit == "shares":
+            return quantity, "shares"
+        elif from_unit == "oz":
+            # Convert oz to shares (inverse of backing)
+            backing = gld_ounces_per_share(reference_date or date.today())
+            return quantity / backing, "shares"
+
+    elif to_mode == "XAU":
+        if from_unit == "oz":
+            return quantity, "oz"
+        elif from_unit == "shares":
+            # Convert shares to oz using backing
+            backing = gld_ounces_per_share(reference_date or date.today())
+            return quantity * backing, "oz"
+
+    raise ValueError(f"Unsupported conversion: {from_unit} -> {to_mode}")
+
+
+def get_display_unit_label(underlying: str, display_mode: str) -> str:
+    """Get the display unit label for a position based on display mode.
+
+    Args:
+        underlying: Position underlying symbol
+        display_mode: Display mode ("GLD" or "XAU")
+
+    Returns:
+        Unit label string ("shares", "oz", etc.)
+    """
+    if underlying == "GLD":
+        if display_mode == "GLD":
+            return "shares"
+        else:  # XAU mode
+            return "oz"
+    elif underlying in ("XAU", "GC=F"):
+        return "oz" if display_mode == "XAU" else "oz"  # Physical gold always in oz
+
+    return "units"
+
+
+def calculate_position_value_in_display_mode(
+    quantity: Decimal,
+    unit: str,
+    current_price: Decimal,
+    price_unit: str,
+    display_mode: str,
+    reference_date: date | None = None,
+) -> Decimal:
+    """Calculate position value in display mode.
+
+    Args:
+        quantity: Position quantity
+        unit: Position unit
+        current_price: Current market price
+        price_unit: Price unit ("shares" or "oz")
+        display_mode: Display mode ("GLD" or "XAU")
+        reference_date: Date for conversion
+
+    Returns:
+        Position value in USD
+    """
+    if display_mode == "GLD" and unit == "shares":
+        # GLD mode: shares × share_price
+        return quantity * current_price
+    elif display_mode == "XAU" and unit == "oz":
+        # XAU mode: oz × oz_price
+        return quantity * current_price
+    elif display_mode == "GLD" and unit == "oz":
+        # Convert oz to shares, then calculate
+        backing = gld_ounces_per_share(reference_date or date.today())
+        shares = quantity / backing
+        share_price = current_price * backing
+        return shares * share_price
+    elif display_mode == "XAU" and unit == "shares":
+        # Convert shares to oz, then calculate
+        backing = gld_ounces_per_share(reference_date or date.today())
+        oz = quantity * backing
+        oz_price = current_price / backing
+        return oz * oz_price
+
+    # Fallback: direct multiplication
+    return quantity * current_price
+
+
+def calculate_pnl_in_display_mode(
+    quantity: Decimal,
+    unit: str,
+    entry_price: Decimal,
+    current_price: Decimal,
+    display_mode: str,
+    reference_date: date | None = None,
+) -> Decimal:
+    """Calculate P&L in display mode.
+
+    Args:
+        quantity: Position quantity
+        unit: Position unit
+        entry_price: Entry price per unit
+        current_price: Current price per unit
+        display_mode: Display mode ("GLD" or "XAU")
+        reference_date: Date for conversion
+
+    Returns:
+        P&L in USD
+    """
+    if display_mode == "GLD" and unit == "shares":
+        # GLD mode: (current_share_price - entry_share_price) × shares
+        return (current_price - entry_price) * quantity
+    elif display_mode == "XAU" and unit == "oz":
+        # XAU mode: (current_oz_price - entry_oz_price) × oz
+        return (current_price - entry_price) * quantity
+    elif display_mode == "GLD" and unit == "oz":
+        # Convert to share basis
+        backing = gld_ounces_per_share(reference_date or date.today())
+        shares = quantity * backing  # oz → shares (wait, this is wrong)
+        # Actually: if we have oz, we need to convert to shares
+        # shares = oz / backing
+        shares = quantity / backing
+        share_entry = entry_price / backing
+        share_current = current_price / backing
+        return (share_current - share_entry) * shares
+    elif display_mode == "XAU" and unit == "shares":
+        # Convert to oz basis
+        backing = gld_ounces_per_share(reference_date or date.today())
+        oz = quantity * backing
+        oz_entry = entry_price * backing
+        oz_current = current_price * backing
+        return (oz_current - oz_entry) * oz
+
+    # Fallback
+    return (current_price - entry_price) * quantity
+
+
+def get_display_mode_options() -> dict[str, str]:
+    """Return available display mode options for the settings UI.
+
+    Returns:
+        Dict mapping mode value to display label for NiceGUI select.
+    """
+    return {
+        "GLD": "GLD Shares (show share prices directly)",
+        "XAU": "Physical Gold (oz) (convert to gold ounces)",
+    }

app/domain/instruments.py

@@ -0,0 +1,186 @@
+from __future__ import annotations
+
+import math
+from dataclasses import dataclass
+from datetime import date
+from decimal import Decimal
+from enum import Enum
+
+from app.domain.backtesting_math import AssetQuantity, PricePerAsset
+from app.domain.units import BaseCurrency, PricePerWeight, Weight, WeightUnit
+
+
+class Underlying(str, Enum):
+    """Supported underlying instruments for options evaluation."""
+
+    GLD = "GLD"
+    GC_F = "GC=F"
+
+    def display_name(self) -> str:
+        """Human-readable display name."""
+        return {
+            Underlying.GLD: "SPDR Gold Shares ETF",
+            Underlying.GC_F: "Gold Futures (COMEX)",
+        }.get(self, self.value)
+
+    def description(self) -> str:
+        """Description of the underlying and data source."""
+        return {
+            Underlying.GLD: "SPDR Gold Shares ETF (live data via yfinance)",
+            Underlying.GC_F: "Gold Futures (coming soon)",
+        }.get(self, "")
+
+
+# GLD expense ratio decay parameters (from docs/GLD_BASIS_RESEARCH.md)
+# Formula: ounces_per_share = 0.10 * e^(-0.004 * years_since_2004)
+GLD_INITIAL_OUNCES_PER_SHARE = Decimal("0.10")
+GLD_EXPENSE_DECAY_RATE = Decimal("0.004")  # 0.4% annual decay
+GLD_LAUNCH_YEAR = 2004
+GLD_LAUNCH_DATE = date(2004, 11, 18)  # GLD IPO date on NYSE
+
+# GC=F contract specifications
+GC_F_OUNCES_PER_CONTRACT = Decimal("100")  # 100 troy oz per contract
+GC_F_QUOTE_CURRENCY = BaseCurrency.USD
+
+
+def gld_ounces_per_share(reference_date: date | None = None) -> Decimal:
+    """
+    Calculate GLD's gold backing per share for a specific date.
+
+    GLD's expense ratio (0.40% annually) causes the gold backing per share to
+    decay exponentially from the initial 0.10 oz/share at launch (November 18, 2004).
+
+    Formula: ounces_per_share = 0.10 * e^(-0.004 * years_since_2004)
+
+    Args:
+        reference_date: Date to calculate backing for. Must be on or after
+            GLD launch date (2004-11-18). Defaults to today.
+
+    Returns:
+        Decimal representing troy ounces of gold backing per GLD share.
+
+    Raises:
+        ValueError: If reference_date is before GLD launch (2004-11-18).
+
+    Examples:
+        >>> from datetime import date
+        >>> # Launch date returns initial 0.10 oz/share
+        >>> gld_ounces_per_share(date(2004, 11, 18))
+        Decimal('0.10')
+        >>> # 2026 backing should be ~0.0916 oz/share (8.4% decay)
+        >>> result = gld_ounces_per_share(date(2026, 1, 1))
+        >>> float(result)  # doctest: +SKIP
+        0.0916...
+    """
+    if reference_date is None:
+        reference_date = date.today()
+
+    if reference_date < GLD_LAUNCH_DATE:
+        raise ValueError(
+            f"GLD backing data unavailable before {GLD_LAUNCH_DATE}. " f"GLD launched on November 18, 2004."
+        )
+
+    years_since_launch = Decimal(reference_date.year - GLD_LAUNCH_YEAR)
+    decay_factor = Decimal(str(math.exp(-float(GLD_EXPENSE_DECAY_RATE * years_since_launch))))
+    return GLD_INITIAL_OUNCES_PER_SHARE * decay_factor
+
+
+@dataclass(frozen=True, slots=True)
+class InstrumentMetadata:
+    symbol: str
+    quote_currency: BaseCurrency | str
+    weight_per_share: Weight
+
+    def __post_init__(self) -> None:
+        normalized_symbol = str(self.symbol).strip().upper()
+        if not normalized_symbol:
+            raise ValueError("Instrument symbol is required")
+        object.__setattr__(self, "symbol", normalized_symbol)
+        object.__setattr__(self, "quote_currency", BaseCurrency(self.quote_currency))
+        object.__setattr__(self, "weight_per_share", self.weight_per_share)
+
+    def assert_symbol(self, symbol: str) -> InstrumentMetadata:
+        normalized = str(symbol).strip().upper()
+        if self.symbol != normalized:
+            raise ValueError(f"Instrument symbol mismatch: {self.symbol} != {normalized}")
+        return self
+
+    def assert_currency(self, currency: BaseCurrency | str) -> InstrumentMetadata:
+        normalized = BaseCurrency(currency)
+        if self.quote_currency is not normalized:
+            raise ValueError(f"Instrument currency mismatch: {self.quote_currency} != {normalized}")
+        return self
+
+    def price_per_weight_from_asset_price(
+        self,
+        price: PricePerAsset,
+        *,
+        per_unit: WeightUnit = WeightUnit.OUNCE_TROY,
+    ) -> PricePerWeight:
+        self.assert_symbol(price.symbol)
+        self.assert_currency(price.currency)
+        weight_per_share = self.weight_per_share.to_unit(per_unit)
+        if weight_per_share.amount <= 0:
+            raise ValueError("Instrument weight_per_share must be positive")
+        return PricePerWeight(
+            amount=price.amount / weight_per_share.amount,
+            currency=price.currency,
+            per_unit=per_unit,
+        )
+
+    def weight_from_asset_quantity(self, quantity: AssetQuantity) -> Weight:
+        self.assert_symbol(quantity.symbol)
+        return Weight(amount=quantity.amount * self.weight_per_share.amount, unit=self.weight_per_share.unit)
+
+    def asset_quantity_from_weight(self, weight: Weight) -> AssetQuantity:
+        normalized_weight = weight.to_unit(self.weight_per_share._unit_typed)
+        if self.weight_per_share.amount <= 0:
+            raise ValueError("Instrument weight_per_share must be positive")
+        return AssetQuantity(amount=normalized_weight.amount / self.weight_per_share.amount, symbol=self.symbol)
+
+
+_GLD = InstrumentMetadata(
+    symbol="GLD",
+    quote_currency=BaseCurrency.USD,
+    weight_per_share=Weight(amount=gld_ounces_per_share(), unit=WeightUnit.OUNCE_TROY),
+)
+
+_GC_F = InstrumentMetadata(
+    symbol="GC=F",
+    quote_currency=GC_F_QUOTE_CURRENCY,
+    weight_per_share=Weight(amount=GC_F_OUNCES_PER_CONTRACT, unit=WeightUnit.OUNCE_TROY),
+)
+
+_INSTRUMENTS: dict[str, InstrumentMetadata] = {
+    _GLD.symbol: _GLD,
+    _GC_F.symbol: _GC_F,
+}
+
+
+def supported_underlyings() -> list[Underlying]:
+    """Return list of supported underlying instruments."""
+    return list(Underlying)
+
+
+def instrument_metadata(symbol: str) -> InstrumentMetadata:
+    normalized = str(symbol).strip().upper()
+    metadata = _INSTRUMENTS.get(normalized)
+    if metadata is None:
+        raise ValueError(f"Unsupported instrument metadata: {normalized or symbol!r}")
+    return metadata
+
+
+def price_per_weight_from_asset_price(
+    price: PricePerAsset,
+    *,
+    per_unit: WeightUnit = WeightUnit.OUNCE_TROY,
+) -> PricePerWeight:
+    return instrument_metadata(price.symbol).price_per_weight_from_asset_price(price, per_unit=per_unit)
+
+
+def weight_from_asset_quantity(quantity: AssetQuantity) -> Weight:
+    return instrument_metadata(quantity.symbol).weight_from_asset_quantity(quantity)
+
+
+def asset_quantity_from_weight(symbol: str, weight: Weight) -> AssetQuantity:
+    return instrument_metadata(symbol).asset_quantity_from_weight(weight)

app/domain/portfolio_math.py

@@ -0,0 +1,453 @@
+from __future__ import annotations
+
+import math
+from datetime import date
+from decimal import Decimal, InvalidOperation
+from typing import Any, Mapping, TypedDict
+
+from app.domain.backtesting_math import PricePerAsset
+from app.domain.conversions import is_gld_mode
+from app.domain.instruments import gld_ounces_per_share, instrument_metadata
+from app.domain.units import BaseCurrency, Money, PricePerWeight, Weight, WeightUnit, decimal_from_float
+from app.models.portfolio import PortfolioConfig
+
+_DEFAULT_CASH_BUFFER = 18_500.0
+_DECIMAL_ZERO = Decimal("0")
+_DECIMAL_ONE = Decimal("1")
+_DECIMAL_HUNDRED = Decimal("100")
+
+
+class PortfolioSnapshot(TypedDict):
+    """Typed snapshot of portfolio state for metrics calculations."""
+
+    gold_value: float
+    loan_amount: float
+    ltv_ratio: float
+    net_equity: float
+    spot_price: float
+    gold_units: float
+    margin_call_ltv: float
+    margin_call_price: float
+    cash_buffer: float
+    hedge_budget: float
+    display_mode: str
+
+
+def _decimal_ratio(numerator: Decimal, denominator: Decimal) -> Decimal:
+    if denominator == 0:
+        return _DECIMAL_ZERO
+    return numerator / denominator
+
+
+def _pct_factor(pct: int) -> Decimal:
+    return _DECIMAL_ONE + (Decimal(pct) / _DECIMAL_HUNDRED)
+
+
+def _money_to_float(value: Money) -> float:
+    return float(value.amount)
+
+
+def _as_money(value: Weight | Money) -> Money:
+    """Narrow Weight | Money to Money after multiplication."""
+    if isinstance(value, Money):
+        return value
+    raise TypeError(f"Expected Money, got {type(value).__name__}")
+
+
+def _decimal_to_float(value: Decimal) -> float:
+    return float(value)
+
+
+def _spot_price(spot_price: float) -> PricePerWeight:
+    return PricePerWeight(
+        amount=decimal_from_float(spot_price),
+        currency=BaseCurrency.USD,
+        per_unit=WeightUnit.OUNCE_TROY,
+    )
+
+
+def _gold_weight(gold_ounces: float) -> Weight:
+    return Weight(amount=decimal_from_float(gold_ounces), unit=WeightUnit.OUNCE_TROY)
+
+
+def _safe_quote_price(value: object) -> float:
+    """Parse a price value, returning 0.0 for invalid/non-finite inputs.
+
+    Rejects NaN, Infinity, and non-positive values by returning 0.0.
+    This defensive helper is used for quote data that may come from
+    untrusted sources like APIs or user input.
+    """
+    try:
+        if isinstance(value, (int, float)):
+            parsed = float(value)
+        elif isinstance(value, str):
+            parsed = float(value.strip())
+        else:
+            return 0.0
+    except (TypeError, ValueError):
+        return 0.0
+    if not math.isfinite(parsed) or parsed <= 0:
+        return 0.0
+    return parsed
+
+
+def _strategy_decimal(value: object) -> Decimal | None:
+    if value is None or isinstance(value, bool):
+        return None
+    if isinstance(value, Decimal):
+        return value if value.is_finite() else None
+    if isinstance(value, int):
+        return Decimal(value)
+    if isinstance(value, float):
+        return decimal_from_float(value)
+    if isinstance(value, str):
+        stripped = value.strip()
+        if not stripped:
+            return None
+        try:
+            parsed = Decimal(stripped)
+        except InvalidOperation:
+            return None
+        return parsed if parsed.is_finite() else None
+    return None
+
+
+def _strategy_downside_put_legs(strategy: Mapping[str, Any], current_spot: Decimal) -> list[tuple[Decimal, Decimal]]:
+    raw_legs = strategy.get("downside_put_legs")
+    if isinstance(raw_legs, (list, tuple)):
+        parsed_legs: list[tuple[Decimal, Decimal]] = []
+        for leg in raw_legs:
+            if not isinstance(leg, Mapping):
+                continue
+            weight = _strategy_decimal(leg.get("allocation_weight", leg.get("weight")))
+            strike_pct = _strategy_decimal(leg.get("strike_pct"))
+            if weight is None or strike_pct is None or weight <= 0 or strike_pct <= 0:
+                continue
+            parsed_legs.append((weight, current_spot * strike_pct))
+        if parsed_legs:
+            return parsed_legs
+
+    protection_floor_pct = _strategy_decimal(strategy.get("protection_floor_pct"))
+    if protection_floor_pct is not None and protection_floor_pct > 0:
+        return [(_DECIMAL_ONE, current_spot * protection_floor_pct)]
+
+    absolute_floor = _strategy_decimal(strategy.get("max_drawdown_floor"))
+    if absolute_floor is not None and absolute_floor > 0:
+        return [(_DECIMAL_ONE, absolute_floor)]
+
+    return [(_DECIMAL_ONE, current_spot * Decimal("0.95"))]
+
+
+def _strategy_upside_cap_decimal(strategy: Mapping[str, Any], current_spot: Decimal) -> Decimal | None:
+    upside_cap_pct = _strategy_decimal(strategy.get("upside_cap_pct"))
+    if upside_cap_pct is not None and upside_cap_pct > 0:
+        return current_spot * upside_cap_pct
+
+    absolute_cap = _strategy_decimal(strategy.get("upside_cap"))
+    if absolute_cap is not None and absolute_cap > 0:
+        return absolute_cap
+
+    return None
+
+
+def _strategy_option_payoff_per_unit(
+    strategy: Mapping[str, Any], current_spot: Decimal, scenario_spot: Decimal
+) -> Decimal:
+    return sum(
+        weight * max(strike_price - scenario_spot, _DECIMAL_ZERO)
+        for weight, strike_price in _strategy_downside_put_legs(strategy, current_spot)
+    ) or Decimal("0")
+
+
+def _strategy_upside_cap_effect_per_unit(
+    strategy: Mapping[str, Any], current_spot: Decimal, scenario_spot: Decimal
+) -> Decimal:
+    cap = _strategy_upside_cap_decimal(strategy, current_spot)
+    if cap is None or scenario_spot <= cap:
+        return _DECIMAL_ZERO
+    return -(scenario_spot - cap)
+
+
+def strategy_protection_floor_bounds(strategy: Mapping[str, Any], *, current_spot: float) -> tuple[float, float] | None:
+    current_spot_decimal = decimal_from_float(current_spot)
+    legs = _strategy_downside_put_legs(strategy, current_spot_decimal)
+    if not legs:
+        return None
+    floor_prices = [strike_price for _, strike_price in legs]
+    return _decimal_to_float(min(floor_prices)), _decimal_to_float(max(floor_prices))
+
+
+def strategy_upside_cap_price(strategy: Mapping[str, Any], *, current_spot: float) -> float | None:
+    cap = _strategy_upside_cap_decimal(strategy, decimal_from_float(current_spot))
+    if cap is None:
+        return None
+    return _decimal_to_float(cap)
+
+
+def strategy_benefit_per_unit(strategy: Mapping[str, Any], *, current_spot: float, scenario_spot: float) -> float:
+    current_spot_decimal = decimal_from_float(current_spot)
+    scenario_spot_decimal = decimal_from_float(scenario_spot)
+    cost = _strategy_decimal(strategy.get("estimated_cost")) or _DECIMAL_ZERO
+    benefit = (
+        _strategy_option_payoff_per_unit(strategy, current_spot_decimal, scenario_spot_decimal)
+        + _strategy_upside_cap_effect_per_unit(strategy, current_spot_decimal, scenario_spot_decimal)
+        - cost
+    )
+    return round(float(benefit), 2)
+
+
+def resolve_collateral_spot_from_quote(
+    quote: Mapping[str, object],
+    *,
+    fallback_symbol: str | None = None,
+) -> tuple[float, str, str] | None:
+    quote_price = _safe_quote_price(quote.get("price"))
+    quote_source = str(quote.get("source", "unknown"))
+    quote_updated_at = str(quote.get("updated_at", ""))
+    quote_symbol = str(quote.get("symbol", fallback_symbol or "")).strip().upper()
+    quote_unit = str(quote.get("quote_unit", "")).strip().lower()
+
+    if quote_price <= 0 or not quote_symbol or quote_unit != "share":
+        return None
+
+    try:
+        metadata = instrument_metadata(quote_symbol)
+    except ValueError:
+        return None
+
+    converted_spot = metadata.price_per_weight_from_asset_price(
+        PricePerAsset(amount=decimal_from_float(quote_price), currency=BaseCurrency.USD, symbol=quote_symbol),
+        per_unit=WeightUnit.OUNCE_TROY,
+    )
+    return _decimal_to_float(converted_spot.amount), quote_source, quote_updated_at
+
+
+def resolve_portfolio_spot_from_quote(
+    config: PortfolioConfig,
+    quote: Mapping[str, object],
+    *,
+    fallback_symbol: str | None = None,
+) -> tuple[float, str, str]:
+    """Resolve spot price from quote based on display mode.
+
+    In GLD display mode: return GLD share price directly (no conversion)
+    In XAU display mode: convert GLD share price to oz-equivalent using expense-adjusted backing
+
+    Args:
+        config: Portfolio configuration with display_mode setting
+        quote: Quote data from data service
+        fallback_symbol: Fallback symbol if quote lacks symbol
+
+    Returns:
+        Tuple of (spot_price, source, updated_at)
+    """
+    display_mode = getattr(config, "display_mode", "XAU")
+
+    # Try to resolve from quote first
+    resolved = resolve_collateral_spot_from_quote(quote, fallback_symbol=fallback_symbol)
+
+    if resolved is None:
+        # No valid quote, use configured entry price
+        configured_price = float(config.entry_price or 0.0)
+        return configured_price, "configured_entry_price", ""
+
+    spot_price, source, updated_at = resolved
+
+    # In GLD mode, return share price directly (no conversion to oz)
+    if is_gld_mode(display_mode):
+        # For GLD mode, we want the share price, not the converted oz price
+        quote_price = _safe_quote_price(quote.get("price"))
+        if quote_price > 0:
+            return quote_price, source, updated_at
+
+    # XAU mode: use the converted oz-equivalent price (already done in resolve_collateral_spot_from_quote)
+    return spot_price, source, updated_at
+
+
+def portfolio_snapshot_from_config(
+    config: PortfolioConfig | None = None,
+    *,
+    runtime_spot_price: float | None = None,
+) -> dict[str, float | str]:
+    """Build portfolio snapshot with display-mode-aware calculations.
+
+    In GLD mode:
+    - gold_units: shares (not oz)
+    - spot_price: GLD share price
+    - gold_value: shares × share_price
+
+    In XAU mode:
+    - gold_units: oz
+    - spot_price: USD/oz
+    - gold_value: oz × oz_price
+    """
+    if config is None:
+        gold_weight = Weight(amount=Decimal("1000"), unit=WeightUnit.OUNCE_TROY)
+        spot = PricePerWeight(amount=Decimal("215"), currency=BaseCurrency.USD, per_unit=WeightUnit.OUNCE_TROY)
+        loan_amount = Money(amount=Decimal("145000"), currency=BaseCurrency.USD)
+        margin_call_ltv = Decimal("0.75")
+        hedge_budget = Money(amount=Decimal("8000"), currency=BaseCurrency.USD)
+        display_mode = "XAU"
+    else:
+        display_mode = getattr(config, "display_mode", "XAU")
+        resolved_spot = runtime_spot_price if runtime_spot_price is not None else float(config.entry_price or 0.0)
+
+        if is_gld_mode(display_mode):
+            # GLD mode: work with shares directly
+            # Use positions if available, otherwise fall back to legacy gold_ounces as shares
+            if config.positions:
+                # Sum GLD position quantities in shares
+                total_shares = Decimal("0")
+                for pos in config.positions:
+                    if pos.underlying == "GLD" and pos.unit == "shares":
+                        total_shares += pos.quantity
+                    elif pos.underlying == "GLD" and pos.unit == "oz":
+                        # Convert oz to shares using current backing
+                        backing = gld_ounces_per_share(date.today())
+                        total_shares += pos.quantity / backing
+                    else:
+                        # Non-GLD positions: treat as oz and convert to shares
+                        backing = gld_ounces_per_share(date.today())
+                        total_shares += pos.quantity / backing
+
+                gold_weight = Weight(amount=total_shares, unit=WeightUnit.OUNCE_TROY)  # Store shares in weight for now
+            else:
+                # Legacy: treat gold_ounces as oz, convert to shares
+                backing = gld_ounces_per_share(date.today())
+                shares = Decimal(str(config.gold_ounces or 0.0)) / backing
+                gold_weight = Weight(amount=shares, unit=WeightUnit.OUNCE_TROY)
+
+            spot = PricePerWeight(
+                amount=decimal_from_float(resolved_spot), currency=BaseCurrency.USD, per_unit=WeightUnit.OUNCE_TROY
+            )
+        else:
+            # XAU mode: work with oz
+            gold_weight = _gold_weight(float(config.gold_ounces or 0.0))
+            spot = _spot_price(resolved_spot)
+
+        loan_amount = Money(amount=decimal_from_float(float(config.loan_amount)), currency=BaseCurrency.USD)
+        margin_call_ltv = decimal_from_float(float(config.margin_threshold))
+        hedge_budget = Money(amount=decimal_from_float(float(config.monthly_budget)), currency=BaseCurrency.USD)
+
+    gold_value = _as_money(gold_weight * spot)
+    net_equity = gold_value - loan_amount
+    ltv_ratio = _decimal_ratio(loan_amount.amount, gold_value.amount)
+    margin_call_price = loan_amount.amount / (margin_call_ltv * gold_weight.amount)
+
+    return {
+        "gold_value": _money_to_float(gold_value),
+        "loan_amount": _money_to_float(loan_amount),
+        "ltv_ratio": _decimal_to_float(ltv_ratio),
+        "net_equity": _money_to_float(net_equity),
+        "spot_price": _decimal_to_float(spot.amount),
+        "gold_units": _decimal_to_float(gold_weight.amount),
+        "margin_call_ltv": _decimal_to_float(margin_call_ltv),
+        "margin_call_price": _decimal_to_float(margin_call_price),
+        "cash_buffer": _DEFAULT_CASH_BUFFER,
+        "hedge_budget": _money_to_float(hedge_budget),
+        "display_mode": display_mode,
+    }
+
+
+def build_alert_context(
+    config: PortfolioConfig,
+    *,
+    spot_price: float,
+    source: str,
+    updated_at: str,
+) -> dict[str, float | str]:
+    """Build alert context with display-mode-aware calculations."""
+    display_mode = getattr(config, "display_mode", "XAU")
+
+    if is_gld_mode(display_mode):
+        # GLD mode: work with shares
+        backing = gld_ounces_per_share(date.today())
+        shares = Decimal(str(config.gold_ounces or 0.0)) / backing
+        gold_weight = Weight(amount=shares, unit=WeightUnit.OUNCE_TROY)
+    else:
+        # XAU mode: work with oz
+        gold_weight = _gold_weight(float(config.gold_ounces or 0.0))
+
+    live_spot = _spot_price(spot_price)
+    gold_value = _as_money(gold_weight * live_spot)
+    loan_amount = Money(amount=decimal_from_float(float(config.loan_amount)), currency=BaseCurrency.USD)
+    margin_call_ltv = decimal_from_float(float(config.margin_threshold))
+    margin_call_price = (
+        loan_amount.amount / (margin_call_ltv * gold_weight.amount) if gold_weight.amount > 0 else _DECIMAL_ZERO
+    )
+
+    return {
+        "spot_price": _decimal_to_float(live_spot.amount),
+        "gold_units": _decimal_to_float(gold_weight.amount),
+        "gold_value": _money_to_float(gold_value),
+        "loan_amount": _money_to_float(loan_amount),
+        "ltv_ratio": _decimal_to_float(_decimal_ratio(loan_amount.amount, gold_value.amount)),
+        "net_equity": _money_to_float(gold_value - loan_amount),
+        "margin_call_ltv": _decimal_to_float(margin_call_ltv),
+        "margin_call_price": _decimal_to_float(margin_call_price),
+        "quote_source": source,
+        "quote_updated_at": updated_at,
+        "display_mode": display_mode,
+    }
+
+
+def strategy_metrics_from_snapshot(
+    strategy: dict[str, Any], scenario_pct: int, snapshot: dict[str, Any]
+) -> dict[str, Any]:
+    spot = decimal_from_float(float(snapshot["spot_price"]))
+    gold_weight = _gold_weight(float(snapshot["gold_units"]))
+    current_spot = PricePerWeight(amount=spot, currency=BaseCurrency.USD, per_unit=WeightUnit.OUNCE_TROY)
+    loan_amount = Money(amount=decimal_from_float(float(snapshot["loan_amount"])), currency=BaseCurrency.USD)
+    base_equity = Money(amount=decimal_from_float(float(snapshot["net_equity"])), currency=BaseCurrency.USD)
+    cost = _strategy_decimal(strategy.get("estimated_cost")) or _DECIMAL_ZERO
+
+    scenario_prices = [spot * _pct_factor(pct) for pct in range(-25, 30, 5)]
+    benefits = [
+        strategy_benefit_per_unit(
+            strategy,
+            current_spot=_decimal_to_float(spot),
+            scenario_spot=_decimal_to_float(price),
+        )
+        for price in scenario_prices
+    ]
+
+    scenario_price = spot * _pct_factor(scenario_pct)
+    scenario_gold_value = _as_money(
+        gold_weight
+        * PricePerWeight(
+            amount=scenario_price,
+            currency=BaseCurrency.USD,
+            per_unit=WeightUnit.OUNCE_TROY,
+        )
+    )
+    current_gold_value = _as_money(gold_weight * current_spot)
+    unhedged_equity = scenario_gold_value - loan_amount
+    scenario_payoff_per_unit = _strategy_option_payoff_per_unit(strategy, spot, scenario_price)
+    capped_upside_per_unit = _strategy_upside_cap_effect_per_unit(strategy, spot, scenario_price)
+
+    option_payoff_cash = Money(amount=gold_weight.amount * scenario_payoff_per_unit, currency=BaseCurrency.USD)
+    capped_upside_cash = Money(amount=gold_weight.amount * capped_upside_per_unit, currency=BaseCurrency.USD)
+    hedge_cost_cash = Money(amount=gold_weight.amount * cost, currency=BaseCurrency.USD)
+    hedged_equity = unhedged_equity + option_payoff_cash + capped_upside_cash - hedge_cost_cash
+
+    waterfall_steps = [
+        ("Base equity", round(_money_to_float(base_equity), 2)),
+        ("Spot move", round(_money_to_float(scenario_gold_value - current_gold_value), 2)),
+        ("Option payoff", round(_money_to_float(option_payoff_cash), 2)),
+        ("Call cap", round(_money_to_float(capped_upside_cash), 2)),
+        ("Hedge cost", round(_money_to_float(-hedge_cost_cash), 2)),
+        ("Net equity", round(_money_to_float(hedged_equity), 2)),
+    ]
+
+    return {
+        "strategy": strategy,
+        "scenario_pct": scenario_pct,
+        "scenario_price": round(float(scenario_price), 2),
+        "scenario_series": [
+            {"price": round(float(price), 2), "benefit": benefit}
+            for price, benefit in zip(scenario_prices, benefits, strict=True)
+        ],
+        "waterfall_steps": waterfall_steps,
+        "unhedged_equity": round(_money_to_float(unhedged_equity), 2),
+        "hedged_equity": round(_money_to_float(hedged_equity), 2),
+    }

app/domain/units.py

@@ -0,0 +1,283 @@
+from __future__ import annotations
+
+from dataclasses import dataclass
+from decimal import Decimal
+from enum import StrEnum
+from typing import TYPE_CHECKING
+
+
+class BaseCurrency(StrEnum):
+    USD = "USD"
+    EUR = "EUR"
+    CHF = "CHF"
+
+
+class WeightUnit(StrEnum):
+    GRAM = "g"
+    KILOGRAM = "kg"
+    OUNCE_TROY = "ozt"
+
+
+GRAMS_PER_KILOGRAM = Decimal("1000")
+GRAMS_PER_TROY_OUNCE = Decimal("31.1034768")
+
+
+DecimalLike = Decimal | int | str
+
+
+def to_decimal(value: DecimalLike) -> Decimal:
+    if isinstance(value, bool):
+        raise TypeError("Boolean values are not valid Decimal inputs")
+    if isinstance(value, Decimal):
+        amount = value
+    elif isinstance(value, int):
+        amount = Decimal(value)
+    elif isinstance(value, str):
+        amount = Decimal(value)
+    else:
+        raise TypeError(f"Unsupported decimal input type: {type(value)!r}")
+    if not amount.is_finite():
+        raise ValueError("Decimal value must be finite")
+    return amount
+
+
+def decimal_from_float(value: float) -> Decimal:
+    if not isinstance(value, float):
+        raise TypeError(f"Expected float, got {type(value)!r}")
+    amount = Decimal(str(value))
+    if not amount.is_finite():
+        raise ValueError("Decimal value must be finite")
+    return amount
+
+
+def _coerce_currency(value: BaseCurrency | str) -> BaseCurrency:
+    if isinstance(value, BaseCurrency):
+        return value
+    try:
+        return BaseCurrency(value)
+    except ValueError as exc:
+        raise ValueError(f"Invalid currency: {value!r}") from exc
+
+
+def _coerce_weight_unit(value: WeightUnit | str) -> WeightUnit:
+    if isinstance(value, WeightUnit):
+        return value
+    try:
+        return WeightUnit(value)
+    except ValueError as exc:
+        raise ValueError(f"Invalid weight unit: {value!r}") from exc
+
+
+def weight_unit_factor(unit: WeightUnit) -> Decimal:
+    if unit is WeightUnit.GRAM:
+        return Decimal("1")
+    if unit is WeightUnit.KILOGRAM:
+        return GRAMS_PER_KILOGRAM
+    if unit is WeightUnit.OUNCE_TROY:
+        return GRAMS_PER_TROY_OUNCE
+    raise ValueError(f"Unsupported weight unit: {unit}")
+
+
+def convert_weight(amount: Decimal, from_unit: WeightUnit, to_unit: WeightUnit) -> Decimal:
+    if from_unit is to_unit:
+        return amount
+    grams = amount * weight_unit_factor(from_unit)
+    return grams / weight_unit_factor(to_unit)
+
+
+def convert_price_per_weight(amount: Decimal, from_unit: WeightUnit, to_unit: WeightUnit) -> Decimal:
+    if from_unit is to_unit:
+        return amount
+    return amount * weight_unit_factor(to_unit) / weight_unit_factor(from_unit)
+
+
+@dataclass(frozen=True, slots=True)
+class Money:
+    amount: Decimal
+    currency: BaseCurrency | str
+
+    def __post_init__(self) -> None:
+        object.__setattr__(self, "amount", to_decimal(self.amount))
+        object.__setattr__(self, "currency", _coerce_currency(self.currency))
+
+    @property
+    def _currency_typed(self) -> BaseCurrency:
+        """Type-narrowed currency accessor for internal use."""
+        return self.currency  # type: ignore[return-value]
+
+    @classmethod
+    def zero(cls, currency: BaseCurrency) -> Money:
+        return cls(amount=Decimal("0"), currency=currency)
+
+    def assert_currency(self, currency: BaseCurrency) -> Money:
+        if self.currency is not currency:
+            raise ValueError(f"Currency mismatch: {self.currency} != {currency}")
+        return self
+
+    def __add__(self, other: object) -> Money:
+        if not isinstance(other, Money):
+            return NotImplemented
+        if self.currency is not other.currency:
+            raise ValueError(f"Currency mismatch: {self.currency} != {other.currency}")
+        return Money(amount=self.amount + other.amount, currency=self.currency)
+
+    def __sub__(self, other: object) -> Money:
+        if not isinstance(other, Money):
+            return NotImplemented
+        if self.currency is not other.currency:
+            raise ValueError(f"Currency mismatch: {self.currency} != {other.currency}")
+        return Money(amount=self.amount - other.amount, currency=self.currency)
+
+    def __mul__(self, other: object) -> Money:
+        if isinstance(other, bool):
+            return NotImplemented
+        if isinstance(other, Decimal):
+            return Money(amount=self.amount * other, currency=self.currency)
+        if isinstance(other, int):
+            return Money(amount=self.amount * Decimal(other), currency=self.currency)
+        return NotImplemented
+
+    def __rmul__(self, other: object) -> Money:
+        return self.__mul__(other)
+
+    def __truediv__(self, other: object) -> Money:
+        if isinstance(other, bool):
+            return NotImplemented
+        if isinstance(other, Decimal):
+            return Money(amount=self.amount / other, currency=self.currency)
+        if isinstance(other, int):
+            return Money(amount=self.amount / Decimal(other), currency=self.currency)
+        return NotImplemented
+
+    def __neg__(self) -> Money:
+        return Money(amount=-self.amount, currency=self.currency)
+
+
+if TYPE_CHECKING:
+    # Type narrowing: after __post_init__, these are the actual types
+    Money_amount: Decimal
+    Money_currency: BaseCurrency
+else:
+    Money_amount = Decimal
+    Money_currency = BaseCurrency | str
+
+
+@dataclass(frozen=True, slots=True)
+class Weight:
+    amount: Decimal
+    unit: WeightUnit | str
+
+    def __post_init__(self) -> None:
+        object.__setattr__(self, "amount", to_decimal(self.amount))
+        object.__setattr__(self, "unit", _coerce_weight_unit(self.unit))
+
+    @property
+    def _unit_typed(self) -> WeightUnit:
+        """Type-narrowed unit accessor for internal use."""
+        return self.unit  # type: ignore[return-value]
+
+    def to_unit(self, unit: WeightUnit) -> Weight:
+        return Weight(amount=convert_weight(self.amount, self._unit_typed, unit), unit=unit)
+
+    def __add__(self, other: object) -> Weight:
+        if not isinstance(other, Weight):
+            return NotImplemented
+        other_converted = other.to_unit(self._unit_typed)
+        return Weight(amount=self.amount + other_converted.amount, unit=self._unit_typed)
+
+    def __sub__(self, other: object) -> Weight:
+        if not isinstance(other, Weight):
+            return NotImplemented
+        other_converted = other.to_unit(self._unit_typed)
+        return Weight(amount=self.amount - other_converted.amount, unit=self._unit_typed)
+
+    def __mul__(self, other: object) -> Weight | Money:
+        if isinstance(other, bool):
+            return NotImplemented
+        if isinstance(other, Decimal):
+            return Weight(amount=self.amount * other, unit=self._unit_typed)
+        if isinstance(other, int):
+            return Weight(amount=self.amount * Decimal(other), unit=self._unit_typed)
+        if isinstance(other, PricePerWeight):
+            adjusted_weight = self.to_unit(other._per_unit_typed)
+            return Money(amount=adjusted_weight.amount * other.amount, currency=other._currency_typed)
+        return NotImplemented
+
+    def __rmul__(self, other: object) -> Weight:
+        if isinstance(other, bool):
+            return NotImplemented
+        if isinstance(other, Decimal):
+            return Weight(amount=self.amount * other, unit=self._unit_typed)
+        if isinstance(other, int):
+            return Weight(amount=self.amount * Decimal(other), unit=self._unit_typed)
+        return NotImplemented
+
+    def __truediv__(self, other: object) -> Weight:
+        if isinstance(other, bool):
+            return NotImplemented
+        if isinstance(other, Decimal):
+            return Weight(amount=self.amount / other, unit=self._unit_typed)
+        if isinstance(other, int):
+            return Weight(amount=self.amount / Decimal(other), unit=self._unit_typed)
+        return NotImplemented
+
+
+@dataclass(frozen=True, slots=True)
+class PricePerWeight:
+    amount: Decimal
+    currency: BaseCurrency | str
+    per_unit: WeightUnit | str
+
+    def __post_init__(self) -> None:
+        amount = to_decimal(self.amount)
+        if amount < 0:
+            raise ValueError("PricePerWeight amount must be non-negative")
+        object.__setattr__(self, "amount", amount)
+        object.__setattr__(self, "currency", _coerce_currency(self.currency))
+        object.__setattr__(self, "per_unit", _coerce_weight_unit(self.per_unit))
+
+    @property
+    def _currency_typed(self) -> BaseCurrency:
+        """Type-narrowed currency accessor for internal use."""
+        return self.currency  # type: ignore[return-value]
+
+    @property
+    def _per_unit_typed(self) -> WeightUnit:
+        """Type-narrowed unit accessor for internal use."""
+        return self.per_unit  # type: ignore[return-value]
+
+    def to_unit(self, unit: WeightUnit) -> PricePerWeight:
+        return PricePerWeight(
+            amount=convert_price_per_weight(self.amount, self._per_unit_typed, unit),
+            currency=self._currency_typed,
+            per_unit=unit,
+        )
+
+    def __mul__(self, other: object) -> Money | PricePerWeight:
+        if isinstance(other, bool):
+            return NotImplemented
+        if isinstance(other, Weight):
+            adjusted_weight = other.to_unit(self._per_unit_typed)
+            return Money(amount=adjusted_weight.amount * self.amount, currency=self._currency_typed)
+        if isinstance(other, Decimal):
+            return PricePerWeight(
+                amount=self.amount * other, currency=self._currency_typed, per_unit=self._per_unit_typed
+            )
+        if isinstance(other, int):
+            return PricePerWeight(
+                amount=self.amount * Decimal(other), currency=self._currency_typed, per_unit=self._per_unit_typed
+            )
+        return NotImplemented
+
+    def __rmul__(self, other: object) -> PricePerWeight:
+        if isinstance(other, bool):
+            return NotImplemented
+        if isinstance(other, Decimal):
+            return PricePerWeight(
+                amount=self.amount * other, currency=self._currency_typed, per_unit=self._per_unit_typed
+            )
+        if isinstance(other, int):
+            return PricePerWeight(
+                amount=self.amount * Decimal(other), currency=self._currency_typed, per_unit=self._per_unit_typed
+            )
+        return NotImplemented

app/main.py

@@ -10,14 +10,20 @@ from contextlib import asynccontextmanager
 from dataclasses import dataclass
 from typing import Any
 
-from fastapi import FastAPI, Request, WebSocket, WebSocketDisconnect
+from fastapi import FastAPI, Form, Request, WebSocket, WebSocketDisconnect
 from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import RedirectResponse, Response
 from nicegui import ui  # type: ignore[attr-defined]
 
 import app.pages  # noqa: F401
 from app.api.routes import router as api_router
+from app.domain.portfolio_math import resolve_collateral_spot_from_quote
+from app.models.portfolio import build_default_portfolio_config
+from app.models.workspace import WORKSPACE_COOKIE, get_workspace_repository
+from app.services import turnstile as turnstile_service
 from app.services.cache import CacheService
 from app.services.data_service import DataService
+from app.services.runtime import get_data_service, set_data_service
 
 logging.basicConfig(level=os.getenv("LOG_LEVEL", "INFO"))
 logger = logging.getLogger(__name__)
@@ -34,11 +40,14 @@ class Settings:
     websocket_interval_seconds: int = 5
     nicegui_mount_path: str = "/"
     nicegui_storage_secret: str = "vault-dash-dev-secret"
+    turnstile_site_key: str = ""
+    turnstile_secret_key: str = ""
 
     @classmethod
     def load(cls) -> Settings:
         cls._load_dotenv()
         origins = os.getenv("CORS_ORIGINS", "*")
+        turnstile = turnstile_service.load_turnstile_settings()
         return cls(
             app_name=os.getenv("APP_NAME", cls.app_name),
             environment=os.getenv("APP_ENV", os.getenv("ENVIRONMENT", cls.environment)),
@@ -49,6 +58,8 @@ class Settings:
             websocket_interval_seconds=int(os.getenv("WEBSOCKET_INTERVAL_SECONDS", cls.websocket_interval_seconds)),
             nicegui_mount_path=os.getenv("NICEGUI_MOUNT_PATH", cls.nicegui_mount_path),
             nicegui_storage_secret=os.getenv("NICEGUI_STORAGE_SECRET", cls.nicegui_storage_secret),
+            turnstile_site_key=turnstile.site_key,
+            turnstile_secret_key=turnstile.secret_key,
         )
 
     @staticmethod
@@ -109,7 +120,8 @@ async def lifespan(app: FastAPI):
     app.state.settings = settings
     app.state.cache = CacheService(settings.redis_url, default_ttl=settings.cache_ttl)
     await app.state.cache.connect()
-    app.state.data_service = DataService(app.state.cache, default_symbol=settings.default_symbol)
+    app.state.data_service = DataService(app.state.cache, default_underlying=settings.default_symbol)
+    set_data_service(app.state.data_service)
     app.state.ws_manager = ConnectionManager()
     app.state.publisher_task = asyncio.create_task(publish_updates(app))
     logger.info("Application startup complete")
@@ -144,6 +156,45 @@ async def health(request: Request) -> dict[str, Any]:
     }
 
 
+@app.get("/workspaces/bootstrap", tags=["workspace"])
+async def bootstrap_workspace_redirect() -> RedirectResponse:
+    return RedirectResponse(url="/", status_code=303)
+
+
+@app.post("/workspaces/bootstrap", tags=["workspace"])
+async def bootstrap_workspace(
+    request: Request,
+    turnstile_response: str = Form(alias="cf-turnstile-response", default=""),
+) -> Response:
+    if not turnstile_service.verify_turnstile_token(
+        turnstile_response, request.client.host if request.client else None
+    ):
+        return RedirectResponse(url="/?captcha_error=1", status_code=303)
+
+    repo = get_workspace_repository()
+    config = build_default_portfolio_config()
+    try:
+        data_service = get_data_service()
+        quote = await data_service.get_quote(data_service.default_symbol)
+        resolved_spot = resolve_collateral_spot_from_quote(quote, fallback_symbol=data_service.default_symbol)
+        if resolved_spot is not None:
+            config = build_default_portfolio_config(entry_price=resolved_spot[0])
+    except Exception as exc:
+        logger.warning("Falling back to static default workspace seed: %s", exc)
+
+    workspace_id = repo.create_workspace_id(config=config)
+    response = RedirectResponse(url=f"/{workspace_id}", status_code=303)
+    response.set_cookie(
+        key=WORKSPACE_COOKIE,
+        value=workspace_id,
+        httponly=True,
+        samesite="lax",
+        max_age=60 * 60 * 24 * 365,
+        path="/",
+    )
+    return response
+
+
 @app.websocket("/ws/updates")
 async def websocket_updates(websocket: WebSocket) -> None:
     manager: ConnectionManager = websocket.app.state.ws_manager

app/models/__init__.py

@@ -1,15 +1,26 @@
 """Application domain models."""
 
+from .event_preset import EventPreset, EventScenarioOverrides
 from .option import Greeks, OptionContract, OptionMoneyness
 from .portfolio import LombardPortfolio
+from .position import Position, create_position
 from .strategy import HedgingStrategy, ScenarioResult, StrategyType
+from .strategy_template import EntryPolicy, RollPolicy, StrategyTemplate, TemplateLeg
 
 __all__ = [
+    "EventPreset",
+    "EventScenarioOverrides",
     "Greeks",
     "HedgingStrategy",
     "LombardPortfolio",
     "OptionContract",
     "OptionMoneyness",
+    "Position",
     "ScenarioResult",
     "StrategyType",
+    "StrategyTemplate",
+    "TemplateLeg",
+    "RollPolicy",
+    "EntryPolicy",
+    "create_position",
 ]

app/models/alerts.py

@@ -0,0 +1,102 @@
+"""Alert notification domain models."""
+
+from __future__ import annotations
+
+import json
+import math
+from dataclasses import asdict, dataclass
+from pathlib import Path
+from typing import Any
+
+
+class AlertHistoryLoadError(RuntimeError):
+    def __init__(self, history_path: Path, message: str) -> None:
+        super().__init__(message)
+        self.history_path = history_path
+
+
+@dataclass
+class AlertEvent:
+    severity: str
+    message: str
+    ltv_ratio: float
+    warning_threshold: float
+    critical_threshold: float
+    spot_price: float
+    updated_at: str
+    email_alerts_enabled: bool
+
+    def __post_init__(self) -> None:
+        for field_name in ("severity", "message", "updated_at"):
+            value = getattr(self, field_name)
+            if not isinstance(value, str):
+                raise TypeError(f"{field_name} must be a string")
+        for field_name in ("ltv_ratio", "warning_threshold", "critical_threshold", "spot_price"):
+            value = getattr(self, field_name)
+            if isinstance(value, bool) or not isinstance(value, (int, float)):
+                raise TypeError(f"{field_name} must be numeric")
+            numeric_value = float(value)
+            if not math.isfinite(numeric_value):
+                raise ValueError(f"{field_name} must be finite")
+            setattr(self, field_name, numeric_value)
+        if not isinstance(self.email_alerts_enabled, bool):
+            raise TypeError("email_alerts_enabled must be a bool")
+
+    def to_dict(self) -> dict[str, Any]:
+        return asdict(self)
+
+    @classmethod
+    def from_dict(cls, data: dict[str, Any]) -> "AlertEvent":
+        return cls(**{k: v for k, v in data.items() if k in cls.__dataclass_fields__})
+
+
+@dataclass
+class AlertStatus:
+    severity: str
+    message: str
+    ltv_ratio: float
+    warning_threshold: float
+    critical_threshold: float
+    email_alerts_enabled: bool
+    history: list[AlertEvent]
+    history_unavailable: bool = False
+    history_notice: str | None = None
+
+
+class AlertHistoryRepository:
+    """File-backed alert history store."""
+
+    HISTORY_PATH = Path("data/alert_history.json")
+
+    def __init__(self, history_path: Path | None = None) -> None:
+        self.history_path = history_path or self.HISTORY_PATH
+        self.history_path.parent.mkdir(parents=True, exist_ok=True)
+
+    def load(self) -> list[AlertEvent]:
+        if not self.history_path.exists():
+            return []
+        try:
+            with self.history_path.open() as f:
+                data = json.load(f)
+        except json.JSONDecodeError as exc:
+            raise AlertHistoryLoadError(self.history_path, f"Alert history is not valid JSON: {exc}") from exc
+        except OSError as exc:
+            raise AlertHistoryLoadError(self.history_path, f"Alert history could not be read: {exc}") from exc
+        if not isinstance(data, list):
+            raise AlertHistoryLoadError(self.history_path, "Alert history payload must be a list")
+        events: list[AlertEvent] = []
+        for index, item in enumerate(data):
+            if not isinstance(item, dict):
+                raise AlertHistoryLoadError(self.history_path, f"Alert history entry {index} must be an object")
+            try:
+                events.append(AlertEvent.from_dict(item))
+            except (TypeError, ValueError) as exc:
+                raise AlertHistoryLoadError(
+                    self.history_path,
+                    f"Alert history entry {index} is invalid: {exc}",
+                ) from exc
+        return events
+
+    def save(self, events: list[AlertEvent]) -> None:
+        with self.history_path.open("w") as f:
+            json.dump([event.to_dict() for event in events], f, indent=2)

app/models/backtest.py

@@ -0,0 +1,178 @@
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from datetime import date
+
+from app.models.event_preset import EventPreset
+
+
+@dataclass(frozen=True)
+class BacktestPortfolioState:
+    currency: str
+    underlying_units: float
+    entry_spot: float
+    loan_amount: float
+    margin_call_ltv: float
+    cash_balance: float = 0.0
+    financing_rate: float = 0.0
+
+    def __post_init__(self) -> None:
+        if self.currency.upper() != "USD":
+            raise ValueError("USD is the only supported currency in the MVP")
+        if self.underlying_units <= 0:
+            raise ValueError("underlying_units must be positive")
+        if self.entry_spot <= 0:
+            raise ValueError("entry_spot must be positive")
+        if self.loan_amount < 0:
+            raise ValueError("loan_amount must be non-negative")
+        if not 0 < self.margin_call_ltv < 1:
+            raise ValueError("margin_call_ltv must be between 0 and 1")
+        if self.loan_amount >= self.underlying_units * self.entry_spot:
+            raise ValueError("loan_amount must be less than initial collateral value")
+
+    @property
+    def start_value(self) -> float:
+        return self.underlying_units * self.entry_spot
+
+
+@dataclass(frozen=True)
+class TemplateRef:
+    slug: str
+    version: int
+
+    def __post_init__(self) -> None:
+        if not self.slug:
+            raise ValueError("template slug is required")
+        if self.version <= 0:
+            raise ValueError("template version must be positive")
+
+
+@dataclass(frozen=True)
+class ProviderRef:
+    provider_id: str
+    pricing_mode: str
+
+    def __post_init__(self) -> None:
+        if not self.provider_id:
+            raise ValueError("provider_id is required")
+        if not self.pricing_mode:
+            raise ValueError("pricing_mode is required")
+
+
+@dataclass(frozen=True)
+class BacktestScenario:
+    scenario_id: str
+    display_name: str
+    symbol: str
+    start_date: date
+    end_date: date
+    initial_portfolio: BacktestPortfolioState
+    template_refs: tuple[TemplateRef, ...]
+    provider_ref: ProviderRef
+
+    def __post_init__(self) -> None:
+        if not self.scenario_id:
+            raise ValueError("scenario_id is required")
+        if not self.display_name:
+            raise ValueError("display_name is required")
+        if not self.symbol:
+            raise ValueError("symbol is required")
+        if self.start_date > self.end_date:
+            raise ValueError("start_date must be on or before end_date")
+        if not self.template_refs:
+            raise ValueError("at least one template ref is required")
+
+
+@dataclass(frozen=True)
+class BacktestDailyPoint:
+    date: date
+    spot_close: float
+    underlying_value: float
+    option_market_value: float
+    premium_cashflow: float
+    realized_option_cashflow: float
+    net_portfolio_value: float
+    loan_amount: float
+    ltv_unhedged: float
+    ltv_hedged: float
+    margin_call_unhedged: bool
+    margin_call_hedged: bool
+    active_position_ids: tuple[str, ...] = field(default_factory=tuple)
+    # OHLC fields for chart and margin call evaluation
+    spot_open: float | None = None  # Day's open
+    spot_low: float | None = None  # Day's low for margin call evaluation
+    spot_high: float | None = None  # Day's high
+    # Option position info
+    option_contracts: float = 0.0  # Number of option contracts held
+
+
+@dataclass(frozen=True)
+class BacktestSummaryMetrics:
+    start_value: float
+    end_value_unhedged: float
+    end_value_hedged_net: float
+    total_hedge_cost: float
+    total_option_payoff_realized: float
+    max_ltv_unhedged: float
+    max_ltv_hedged: float
+    margin_call_days_unhedged: int
+    margin_call_days_hedged: int
+    margin_threshold_breached_unhedged: bool
+    margin_threshold_breached_hedged: bool
+
+
+@dataclass(frozen=True)
+class TemplateBacktestResult:
+    template_slug: str
+    template_id: str
+    template_version: int
+    template_name: str
+    summary_metrics: BacktestSummaryMetrics
+    daily_path: tuple[BacktestDailyPoint, ...]
+    warnings: tuple[str, ...] = field(default_factory=tuple)
+
+
+@dataclass(frozen=True)
+class BacktestRunResult:
+    scenario_id: str
+    template_results: tuple[TemplateBacktestResult, ...]
+
+
+@dataclass(frozen=True)
+class EventComparisonRanking:
+    rank: int
+    template_slug: str
+    template_name: str
+    survived_margin_call: bool
+    margin_call_days_hedged: int
+    max_ltv_hedged: float
+    hedge_cost: float
+    final_equity: float
+    result: TemplateBacktestResult
+
+
+@dataclass(frozen=True)
+class EventComparisonReport:
+    event_preset: EventPreset
+    scenario: BacktestScenario
+    rankings: tuple[EventComparisonRanking, ...]
+    run_result: BacktestRunResult
+
+
+@dataclass(frozen=True)
+class BacktestPortfolioPreset:
+    """User-facing preset for quick scenario configuration."""
+
+    preset_id: str
+    name: str
+    description: str
+    underlying_symbol: str
+    start_date: date
+    end_date: date
+    entry_spot: float | None = None  # If None, derive from historical data
+    underlying_units: float = 1000.0
+    loan_amount: float = 50000.0
+    margin_call_ltv: float = 0.80
+    template_slug: str = "protective-put-atm-12m"
+    # Event-specific overrides
+    scenario_overrides: dict[str, object] | None = None

app/models/backtest_settings.py

@@ -0,0 +1,88 @@
+"""Backtest settings model for configuring backtest scenarios independently of portfolio settings."""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+from datetime import date
+from typing import Literal
+from uuid import UUID, uuid4
+
+# Self type annotation
+from app.models.backtest import ProviderRef
+
+
+@dataclass(frozen=True)
+class BacktestSettings:
+    """Configuration for running backtests independent of portfolio settings.
+
+    These settings determine what data to fetch and how to run backtests,
+    separate from the actual portfolio configurations being tested.
+    """
+
+    settings_id: UUID
+    name: str
+    data_source: Literal["databento", "yfinance", "synthetic"]
+    dataset: str
+    schema: str
+    start_date: date
+    end_date: date
+    underlying_symbol: Literal["GLD", "GC", "XAU"]
+    start_price: float
+    underlying_units: float
+    loan_amount: float
+    margin_call_ltv: float
+    template_slugs: tuple[str, ...]
+    cache_key: str
+    data_cost_usd: float
+    provider_ref: ProviderRef
+
+    def __post_init__(self) -> None:
+        if not self.settings_id:
+            raise ValueError("settings_id is required")
+        if not self.name:
+            raise ValueError("name is required")
+        if self.start_date > self.end_date:
+            raise ValueError("start_date must be on or before end_date")
+        if self.data_source not in ("databento", "yfinance", "synthetic"):
+            raise ValueError("data_source must be 'databento', 'yfinance', or 'synthetic'")
+        if self.underlying_symbol not in ("GLD", "GC", "XAU"):
+            raise ValueError("underlying_symbol must be 'GLD', 'GC', or 'XAU'")
+        if self.start_price < 0:
+            raise ValueError("start_price must be non-negative")
+        if self.underlying_units <= 0:
+            raise ValueError("underlying_units must be positive")
+        if self.loan_amount < 0:
+            raise ValueError("loan_amount must be non-negative")
+        if not 0 < self.margin_call_ltv < 1:
+            raise ValueError("margin_call_ltv must be between 0 and 1")
+        if not self.template_slugs:
+            raise ValueError("at least one template slug is required")
+        if self.data_cost_usd < 0:
+            raise ValueError("data_cost_usd must be non-negative")
+
+    @classmethod
+    def create_default(cls, name: str = "Default Backtest Settings") -> BacktestSettings:
+        """Create default backtest settings configuration."""
+        return cls(
+            settings_id=uuid4(),
+            name=name,
+            data_source="databento",
+            dataset="XNAS.BASIC",
+            schema="ohlcv-1d",
+            start_date=date(2020, 1, 1),
+            end_date=date(2023, 12, 31),
+            underlying_symbol="GLD",
+            start_price=0.0,
+            underlying_units=1000.0,
+            loan_amount=0.0,
+            margin_call_ltv=0.75,
+            template_slugs=("default-template",),
+            cache_key="",
+            data_cost_usd=0.0,
+            provider_ref=ProviderRef(provider_id="default", pricing_mode="standard"),
+        )
+
+
+# For backward compatibility - alias to existing models
+BacktestScenario = "app.models.backtest.BacktestScenario"
+# TemplateRef and ProviderRef imported from app.models.backtest

app/models/backtest_settings_repository.py

@@ -0,0 +1,128 @@
+"""Repository for persisting backtest settings configuration."""
+
+from __future__ import annotations
+
+import json
+from datetime import date
+from pathlib import Path
+from typing import Any
+from uuid import UUID
+
+from app.models.backtest_settings import BacktestSettings
+
+
+class BacktestSettingsRepository:
+    """Repository for persisting backtest settings configuration.
+
+    Persists to `.workspaces/{workspace_id}/backtest_settings.json`
+    """
+
+    def __init__(self, base_path: Path | str = Path(".workspaces")) -> None:
+        self.base_path = Path(base_path)
+        self.base_path.mkdir(parents=True, exist_ok=True)
+
+    def load(self, workspace_id: str) -> BacktestSettings | None:
+        """Load backtest settings for a workspace.
+
+        Args:
+            workspace_id: The workspace ID to load settings for
+
+        Returns:
+            BacktestSettings: The loaded settings, or None if no settings exist
+
+        Raises:
+            ValueError: If settings file is invalid
+        """
+        settings_path = self._settings_path(workspace_id)
+        if not settings_path.exists():
+            return None
+
+        try:
+            with open(settings_path) as f:
+                data = json.load(f)
+            return self._settings_from_dict(data)
+        except (json.JSONDecodeError, KeyError) as e:
+            raise ValueError(f"Invalid backtest settings file: {e}") from e
+
+    def save(self, workspace_id: str, settings: BacktestSettings) -> None:
+        """Save backtest settings for a workspace.
+
+        Args:
+            workspace_id: The workspace ID to save settings for
+            settings: The settings to save
+        """
+        settings_path = self._settings_path(workspace_id)
+        settings_path.parent.mkdir(parents=True, exist_ok=True)
+
+        payload = self._to_dict(settings)
+        tmp_path = settings_path.with_name(f"{settings_path.name}.tmp")
+
+        with open(tmp_path, "w") as f:
+            json.dump(payload, f, indent=2)
+            f.flush()
+        # Atomic replace
+        tmp_path.replace(settings_path)
+
+    def _settings_path(self, workspace_id: str) -> Path:
+        """Get the path to the settings file for a workspace."""
+        return self.base_path / workspace_id / "backtest_settings.json"
+
+    def _to_dict(self, settings: BacktestSettings) -> dict[str, Any]:
+        """Convert BacktestSettings to a dictionary for serialization."""
+        return {
+            "settings_id": str(settings.settings_id),
+            "name": settings.name,
+            "data_source": settings.data_source,
+            "dataset": settings.dataset,
+            "schema": settings.schema,
+            "start_date": settings.start_date.isoformat(),
+            "end_date": settings.end_date.isoformat(),
+            "underlying_symbol": settings.underlying_symbol,
+            "start_price": settings.start_price,
+            "underlying_units": settings.underlying_units,
+            "loan_amount": settings.loan_amount,
+            "margin_call_ltv": settings.margin_call_ltv,
+            "template_slugs": list(settings.template_slugs),
+            "cache_key": settings.cache_key,
+            "data_cost_usd": settings.data_cost_usd,
+            "provider_ref": {
+                "provider_id": settings.provider_ref.provider_id,
+                "pricing_mode": settings.provider_ref.pricing_mode,
+            },
+        }
+
+    def _settings_from_dict(self, data: dict[str, Any]) -> BacktestSettings:
+        """Create BacktestSettings from a dictionary."""
+        # Handle potential string dates
+        start_date = data["start_date"]
+        if isinstance(start_date, str):
+            start_date = date.fromisoformat(start_date)
+
+        end_date = data["end_date"]
+        if isinstance(end_date, str):
+            end_date = date.fromisoformat(end_date)
+
+        # Import here to avoid circular import issues at module level
+        from app.models.backtest import ProviderRef
+
+        return BacktestSettings(
+            settings_id=UUID(data["settings_id"]),
+            name=data["name"],
+            data_source=data["data_source"],
+            dataset=data["dataset"],
+            schema=data["schema"],
+            start_date=start_date,
+            end_date=end_date,
+            underlying_symbol=data["underlying_symbol"],
+            start_price=data["start_price"],
+            underlying_units=data["underlying_units"],
+            loan_amount=data["loan_amount"],
+            margin_call_ltv=data["margin_call_ltv"],
+            template_slugs=tuple(data["template_slugs"]),
+            cache_key=data["cache_key"],
+            data_cost_usd=data["data_cost_usd"],
+            provider_ref=ProviderRef(
+                provider_id=data["provider_ref"]["provider_id"],
+                pricing_mode=data["provider_ref"]["pricing_mode"],
+            ),
+        )

app/models/event_preset.py

@@ -0,0 +1,105 @@
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from datetime import date, datetime, timezone
+from typing import Literal
+
+EventType = Literal["selloff", "recovery", "stress_test"]
+
+
+@dataclass(frozen=True)
+class EventScenarioOverrides:
+    lookback_days: int | None = None
+    recovery_days: int | None = None
+    default_template_slugs: tuple[str, ...] = field(default_factory=tuple)
+
+    def __post_init__(self) -> None:
+        if self.lookback_days is not None and self.lookback_days < 0:
+            raise ValueError("lookback_days must be non-negative")
+        if self.recovery_days is not None and self.recovery_days < 0:
+            raise ValueError("recovery_days must be non-negative")
+        if any(not slug for slug in self.default_template_slugs):
+            raise ValueError("default_template_slugs must not contain empty values")
+
+    def to_dict(self) -> dict[str, object]:
+        return {
+            "lookback_days": self.lookback_days,
+            "recovery_days": self.recovery_days,
+            "default_template_slugs": list(self.default_template_slugs),
+        }
+
+    @classmethod
+    def from_dict(cls, payload: dict[str, object] | None) -> EventScenarioOverrides:
+        if payload is None:
+            return cls()
+        return cls(
+            lookback_days=payload.get("lookback_days"),  # type: ignore[arg-type]
+            recovery_days=payload.get("recovery_days"),  # type: ignore[arg-type]
+            default_template_slugs=tuple(payload.get("default_template_slugs", [])),  # type: ignore[arg-type]
+        )
+
+
+@dataclass(frozen=True)
+class EventPreset:
+    event_preset_id: str
+    slug: str
+    display_name: str
+    symbol: str
+    window_start: date
+    window_end: date
+    anchor_date: date | None
+    event_type: EventType
+    tags: tuple[str, ...] = field(default_factory=tuple)
+    description: str = ""
+    scenario_overrides: EventScenarioOverrides = field(default_factory=EventScenarioOverrides)
+    created_at: datetime = field(default_factory=lambda: datetime.now(timezone.utc))
+
+    def __post_init__(self) -> None:
+        if not self.event_preset_id:
+            raise ValueError("event_preset_id is required")
+        if not self.slug:
+            raise ValueError("slug is required")
+        if not self.display_name:
+            raise ValueError("display_name is required")
+        if not self.symbol:
+            raise ValueError("symbol is required")
+        if self.window_start > self.window_end:
+            raise ValueError("window_start must be on or before window_end")
+        if self.anchor_date is not None and not (self.window_start <= self.anchor_date <= self.window_end):
+            raise ValueError("anchor_date must fall inside the event window")
+        if self.event_type not in {"selloff", "recovery", "stress_test"}:
+            raise ValueError("unsupported event_type")
+
+    def to_dict(self) -> dict[str, object]:
+        return {
+            "event_preset_id": self.event_preset_id,
+            "slug": self.slug,
+            "display_name": self.display_name,
+            "symbol": self.symbol,
+            "window_start": self.window_start.isoformat(),
+            "window_end": self.window_end.isoformat(),
+            "anchor_date": self.anchor_date.isoformat() if self.anchor_date is not None else None,
+            "event_type": self.event_type,
+            "tags": list(self.tags),
+            "description": self.description,
+            "scenario_overrides": self.scenario_overrides.to_dict(),
+            "created_at": self.created_at.isoformat(),
+        }
+
+    @classmethod
+    def from_dict(cls, payload: dict[str, object]) -> EventPreset:
+        anchor_date = payload.get("anchor_date")
+        return cls(
+            event_preset_id=str(payload["event_preset_id"]),
+            slug=str(payload["slug"]),
+            display_name=str(payload["display_name"]),
+            symbol=str(payload["symbol"]),
+            window_start=date.fromisoformat(str(payload["window_start"])),
+            window_end=date.fromisoformat(str(payload["window_end"])),
+            anchor_date=date.fromisoformat(str(anchor_date)) if anchor_date else None,
+            event_type=payload["event_type"],  # type: ignore[arg-type]
+            tags=tuple(payload.get("tags", [])),  # type: ignore[arg-type]
+            description=str(payload.get("description", "")),
+            scenario_overrides=EventScenarioOverrides.from_dict(payload.get("scenario_overrides")),  # type: ignore[arg-type]
+            created_at=datetime.fromisoformat(str(payload["created_at"])),
+        )

app/models/ltv_history.py

@@ -0,0 +1,198 @@
+from __future__ import annotations
+
+import json
+from dataclasses import dataclass
+from datetime import date, datetime
+from decimal import Decimal, InvalidOperation
+from pathlib import Path
+from typing import Any
+
+
+class LtvHistoryLoadError(RuntimeError):
+    def __init__(self, history_path: Path, message: str) -> None:
+        super().__init__(message)
+        self.history_path = history_path
+
+
+@dataclass(frozen=True)
+class LtvSnapshot:
+    snapshot_date: str
+    captured_at: str
+    ltv_ratio: Decimal
+    margin_threshold: Decimal
+    loan_amount: Decimal
+    collateral_value: Decimal
+    spot_price: Decimal
+    source: str
+
+    def __post_init__(self) -> None:
+        for field_name in ("snapshot_date", "captured_at", "source"):
+            value = getattr(self, field_name)
+            if not isinstance(value, str) or not value.strip():
+                raise ValueError(f"{field_name} must be a non-empty string")
+        date.fromisoformat(self.snapshot_date)
+        datetime.fromisoformat(self.captured_at.replace("Z", "+00:00"))
+        for field_name in (
+            "ltv_ratio",
+            "margin_threshold",
+            "loan_amount",
+            "collateral_value",
+            "spot_price",
+        ):
+            value = getattr(self, field_name)
+            if not isinstance(value, Decimal) or not value.is_finite():
+                raise TypeError(f"{field_name} must be a finite Decimal")
+        if self.ltv_ratio < 0:
+            raise ValueError("ltv_ratio must be zero or greater")
+        if not Decimal("0") < self.margin_threshold < Decimal("1"):
+            raise ValueError("margin_threshold must be between 0 and 1")
+        if self.loan_amount < 0:
+            raise ValueError("loan_amount must be zero or greater")
+        if self.collateral_value <= 0:
+            raise ValueError("collateral_value must be positive")
+        if self.spot_price <= 0:
+            raise ValueError("spot_price must be positive")
+
+    def to_dict(self) -> dict[str, Any]:
+        return {
+            "snapshot_date": self.snapshot_date,
+            "captured_at": self.captured_at,
+            "ltv_ratio": _structured_ratio_payload(self.ltv_ratio),
+            "margin_threshold": _structured_ratio_payload(self.margin_threshold),
+            "loan_amount": _structured_money_payload(self.loan_amount),
+            "collateral_value": _structured_money_payload(self.collateral_value),
+            "spot_price": _structured_price_payload(self.spot_price),
+            "source": self.source,
+        }
+
+    @classmethod
+    def from_dict(cls, data: dict[str, Any]) -> "LtvSnapshot":
+        return cls(
+            snapshot_date=_require_non_empty_string(data, "snapshot_date"),
+            captured_at=_require_non_empty_string(data, "captured_at"),
+            ltv_ratio=_parse_ratio_payload(data.get("ltv_ratio"), field_name="ltv_ratio"),
+            margin_threshold=_parse_ratio_payload(data.get("margin_threshold"), field_name="margin_threshold"),
+            loan_amount=_parse_money_payload(data.get("loan_amount"), field_name="loan_amount"),
+            collateral_value=_parse_money_payload(data.get("collateral_value"), field_name="collateral_value"),
+            spot_price=_parse_price_payload(data.get("spot_price"), field_name="spot_price"),
+            source=_require_non_empty_string(data, "source"),
+        )
+
+
+class LtvHistoryRepository:
+    def __init__(self, base_path: Path | str = Path("data/workspaces")) -> None:
+        self.base_path = Path(base_path)
+        self.base_path.mkdir(parents=True, exist_ok=True)
+
+    def load(self, workspace_id: str) -> list[LtvSnapshot]:
+        history_path = self.history_path(workspace_id)
+        if not history_path.exists():
+            return []
+        try:
+            payload = json.loads(history_path.read_text())
+        except json.JSONDecodeError as exc:
+            raise LtvHistoryLoadError(history_path, f"LTV history is not valid JSON: {exc}") from exc
+        except OSError as exc:
+            raise LtvHistoryLoadError(history_path, f"LTV history could not be read: {exc}") from exc
+        if not isinstance(payload, list):
+            raise LtvHistoryLoadError(history_path, "LTV history payload must be a list")
+        snapshots: list[LtvSnapshot] = []
+        for index, item in enumerate(payload):
+            if not isinstance(item, dict):
+                raise LtvHistoryLoadError(history_path, f"LTV history entry {index} must be an object")
+            try:
+                snapshots.append(LtvSnapshot.from_dict(item))
+            except (TypeError, ValueError, KeyError) as exc:
+                raise LtvHistoryLoadError(history_path, f"LTV history entry {index} is invalid: {exc}") from exc
+        return snapshots
+
+    def save(self, workspace_id: str, snapshots: list[LtvSnapshot]) -> None:
+        history_path = self.history_path(workspace_id)
+        history_path.parent.mkdir(parents=True, exist_ok=True)
+        history_path.write_text(json.dumps([snapshot.to_dict() for snapshot in snapshots], indent=2))
+
+    def history_path(self, workspace_id: str) -> Path:
+        return self.base_path / workspace_id / "ltv_history.json"
+
+
+def _require_non_empty_string(data: dict[str, Any], field_name: str) -> str:
+    value = data.get(field_name)
+    if not isinstance(value, str) or not value.strip():
+        raise ValueError(f"{field_name} must be a non-empty string")
+    return value
+
+
+def _decimal_text(value: Decimal) -> str:
+    if value == value.to_integral():
+        return str(value.quantize(Decimal("1")))
+    normalized = value.normalize()
+    exponent = normalized.as_tuple().exponent
+    if isinstance(exponent, int) and exponent < 0:
+        return format(normalized, "f")
+    return str(normalized)
+
+
+def _parse_decimal_payload(
+    payload: object,
+    *,
+    field_name: str,
+    expected_tag_key: str,
+    expected_tag_value: str,
+    expected_currency: str | None = None,
+    expected_per_weight_unit: str | None = None,
+) -> Decimal:
+    if not isinstance(payload, dict):
+        raise TypeError(f"{field_name} must be an object")
+    if payload.get(expected_tag_key) != expected_tag_value:
+        raise ValueError(f"{field_name} must declare {expected_tag_key}={expected_tag_value!r}")
+    if expected_currency is not None and payload.get("currency") != expected_currency:
+        raise ValueError(f"{field_name} must declare currency={expected_currency!r}")
+    if expected_per_weight_unit is not None and payload.get("per_weight_unit") != expected_per_weight_unit:
+        raise ValueError(f"{field_name} must declare per_weight_unit={expected_per_weight_unit!r}")
+    raw_value = payload.get("value")
+    if not isinstance(raw_value, str) or not raw_value.strip():
+        raise ValueError(f"{field_name}.value must be a non-empty string")
+    try:
+        value = Decimal(raw_value)
+    except InvalidOperation as exc:
+        raise ValueError(f"{field_name}.value must be numeric") from exc
+    if not value.is_finite():
+        raise ValueError(f"{field_name}.value must be finite")
+    return value
+
+
+def _parse_ratio_payload(payload: object, *, field_name: str) -> Decimal:
+    return _parse_decimal_payload(payload, field_name=field_name, expected_tag_key="unit", expected_tag_value="ratio")
+
+
+def _parse_money_payload(payload: object, *, field_name: str) -> Decimal:
+    return _parse_decimal_payload(
+        payload,
+        field_name=field_name,
+        expected_tag_key="currency",
+        expected_tag_value="USD",
+        expected_currency="USD",
+    )
+
+
+def _parse_price_payload(payload: object, *, field_name: str) -> Decimal:
+    return _parse_decimal_payload(
+        payload,
+        field_name=field_name,
+        expected_tag_key="currency",
+        expected_tag_value="USD",
+        expected_currency="USD",
+        expected_per_weight_unit="ozt",
+    )
+
+
+def _structured_ratio_payload(value: Decimal) -> dict[str, str]:
+    return {"value": str(value), "unit": "ratio"}
+
+
+def _structured_money_payload(value: Decimal) -> dict[str, str]:
+    return {"value": _decimal_text(value), "currency": "USD"}
+
+
+def _structured_price_payload(value: Decimal) -> dict[str, str]:
+    return {"value": _decimal_text(value), "currency": "USD", "per_weight_unit": "ozt"}

app/models/portfolio.py

@@ -1,12 +1,90 @@
-"""Portfolio configuration models with validation and persistence."""
+"""Portfolio configuration and domain portfolio models."""
 
 from __future__ import annotations
 
 import json
 import os
 from dataclasses import dataclass, field
+from datetime import date
+from decimal import Decimal
 from pathlib import Path
-from typing import Any
+from typing import Any, Literal
+
+from app.models.position import Position, create_position
+
+# Type aliases for display mode and entry basis
+DisplayMode = Literal["GLD", "XAU"]
+EntryBasisMode = Literal["value_price", "weight"]
+
+_DEFAULT_GOLD_VALUE = 215_000.0
+_DEFAULT_ENTRY_PRICE = 2_150.0
+_LEGACY_DEFAULT_ENTRY_PRICE = 215.0
+_DEFAULT_GOLD_OUNCES = 100.0
+_LEGACY_DEFAULT_GOLD_OUNCES = 1_000.0
+
+
+def build_default_portfolio_config(*, entry_price: float | None = None) -> "PortfolioConfig":
+    resolved_entry_price = float(entry_price) if entry_price is not None else _DEFAULT_ENTRY_PRICE
+    gold_value = resolved_entry_price * _DEFAULT_GOLD_OUNCES
+    return PortfolioConfig(
+        gold_value=gold_value,
+        entry_price=resolved_entry_price,
+        gold_ounces=_DEFAULT_GOLD_OUNCES,
+        entry_basis_mode="value_price",
+    )
+
+
+@dataclass(frozen=True)
+class LombardPortfolio:
+    """Lombard loan portfolio backed by physical gold."""
+
+    gold_ounces: float
+    gold_price_per_ounce: float
+    loan_amount: float
+    initial_ltv: float
+    margin_call_ltv: float
+
+    def __post_init__(self) -> None:
+        if self.gold_ounces <= 0:
+            raise ValueError("gold_ounces must be positive")
+        if self.gold_price_per_ounce <= 0:
+            raise ValueError("gold_price_per_ounce must be positive")
+        if self.loan_amount < 0:
+            raise ValueError("loan_amount must be non-negative")
+        if not 0 < self.initial_ltv < 1:
+            raise ValueError("initial_ltv must be between 0 and 1")
+        if not 0 < self.margin_call_ltv < 1:
+            raise ValueError("margin_call_ltv must be between 0 and 1")
+        if self.initial_ltv > self.margin_call_ltv:
+            raise ValueError("initial_ltv cannot exceed margin_call_ltv")
+        if self.loan_amount > self.gold_value:
+            raise ValueError("loan_amount cannot exceed current gold value")
+
+    @property
+    def gold_value(self) -> float:
+        return self.gold_ounces * self.gold_price_per_ounce
+
+    @property
+    def current_ltv(self) -> float:
+        return self.loan_amount / self.gold_value
+
+    @property
+    def net_equity(self) -> float:
+        return self.gold_value - self.loan_amount
+
+    def gold_value_at_price(self, gold_price_per_ounce: float) -> float:
+        if gold_price_per_ounce <= 0:
+            raise ValueError("gold_price_per_ounce must be positive")
+        return self.gold_ounces * gold_price_per_ounce
+
+    def ltv_at_price(self, gold_price_per_ounce: float) -> float:
+        return self.loan_amount / self.gold_value_at_price(gold_price_per_ounce)
+
+    def net_equity_at_price(self, gold_price_per_ounce: float) -> float:
+        return self.gold_value_at_price(gold_price_per_ounce) - self.loan_amount
+
+    def margin_call_price(self) -> float:
+        return self.loan_amount / (self.margin_call_ltv * self.gold_ounces)
 
 
 @dataclass
@@ -14,14 +92,21 @@ class PortfolioConfig:
     """User portfolio configuration with validation.
 
     Attributes:
-        gold_value: Current gold collateral value in USD
+        gold_value: Collateral baseline value in USD at entry
+        entry_price: Gold entry price per ounce in USD
+        gold_ounces: Canonical gold collateral weight in ounces
+        entry_basis_mode: Preferred settings UI input mode
         loan_amount: Outstanding loan amount in USD
         margin_threshold: LTV threshold for margin call (default 0.75)
         monthly_budget: Approved monthly hedge budget
         ltv_warning: LTV warning level for alerts (default 0.70)
+        positions: List of position entries (multi-position support)
     """
 
-    gold_value: float = 215000.0
+    gold_value: float | None = None
+    entry_price: float | None = _DEFAULT_ENTRY_PRICE
+    gold_ounces: float | None = None
+    entry_basis_mode: EntryBasisMode = "value_price"
     loan_amount: float = 145000.0
     margin_threshold: float = 0.75
     monthly_budget: float = 8000.0
@@ -32,19 +117,147 @@ class PortfolioConfig:
     fallback_source: str = "yfinance"
     refresh_interval: int = 5
 
+    # Underlying instrument selection
+    underlying: str = "GLD"
+
+    # Display mode: how to show positions (GLD shares vs physical gold)
+    display_mode: DisplayMode = "XAU"  # "GLD" for share view, "XAU" for physical gold view
+
     # Alert settings
     volatility_spike: float = 0.25
     spot_drawdown: float = 7.5
     email_alerts: bool = False
 
-    def __post_init__(self):
+    # Multi-position support
-        """Validate configuration after initialization."""
+    positions: list[Position] = field(default_factory=list)
+
+    def __post_init__(self) -> None:
+        """Normalize entry basis fields and validate configuration."""
+        self._normalize_entry_basis()
         self.validate()
 
+    def migrate_to_positions_if_needed(self) -> None:
+        """Migrate legacy single-entry portfolios to multi-position format.
+
+        Call this after loading from persistence to migrate legacy configs.
+        If positions list is empty but gold_ounces exists, create one Position
+        representing the legacy single entry.
+        """
+        if self.positions:
+            # Already has positions, no migration needed
+            return
+
+        if self.gold_ounces is None or self.entry_price is None:
+            return
+
+        # Create a single position from legacy fields
+        position = create_position(
+            underlying=self.underlying,
+            quantity=Decimal(str(self.gold_ounces)),
+            unit="oz",
+            entry_price=Decimal(str(self.entry_price)),
+            entry_date=date.today(),
+            entry_basis_mode=self.entry_basis_mode,
+        )
+        # PortfolioConfig is not frozen, so we can set directly
+        self.positions = [position]
+
+    def _normalize_entry_basis(self) -> None:
+        """Resolve user input into canonical weight + entry price representation."""
+        if self.entry_basis_mode not in {"value_price", "weight"}:
+            raise ValueError("Entry basis mode must be 'value_price' or 'weight'")
+
+        if self.entry_price is None or self.entry_price <= 0:
+            raise ValueError("Entry price must be positive")
+
+        if self.gold_value is not None and self.gold_value <= 0:
+            raise ValueError("Gold value must be positive")
+        if self.gold_ounces is not None and self.gold_ounces <= 0:
+            raise ValueError("Gold weight must be positive")
+
+        if self.gold_value is None and self.gold_ounces is None:
+            default = build_default_portfolio_config(entry_price=self.entry_price)
+            self.gold_value = default.gold_value
+            self.gold_ounces = default.gold_ounces
+            return
+
+        if self.gold_value is None and self.gold_ounces is not None:
+            self.gold_value = self.gold_ounces * self.entry_price
+            return
+
+        if self.gold_ounces is None and self.gold_value is not None:
+            self.gold_ounces = self.gold_value / self.entry_price
+            return
+
+        assert self.gold_value is not None
+        assert self.gold_ounces is not None
+        derived_gold_value = self.gold_ounces * self.entry_price
+        tolerance = max(0.01, abs(derived_gold_value) * 1e-9)
+        if abs(self.gold_value - derived_gold_value) > tolerance:
+            raise ValueError("Gold value and weight contradict each other")
+        self.gold_value = derived_gold_value
+
+    def _migrate_legacy_to_positions(self) -> None:
+        """Migrate legacy single-entry portfolios to multi-position format.
+
+        If positions list is empty but gold_ounces exists, create one Position
+        representing the legacy single entry.
+        """
+        if self.positions:
+            # Already has positions, no migration needed
+            return
+
+        if self.gold_ounces is None or self.entry_price is None:
+            return
+
+        # Create a single position from legacy fields
+        position = create_position(
+            underlying=self.underlying,
+            quantity=Decimal(str(self.gold_ounces)),
+            unit="oz",
+            entry_price=Decimal(str(self.entry_price)),
+            entry_date=date.today(),
+            entry_basis_mode=self.entry_basis_mode,
+        )
+        # PortfolioConfig is not frozen, so we can set directly
+        self.positions = [position]
+
+    def _sync_legacy_fields_from_positions(self) -> None:
+        """Sync legacy gold_ounces, entry_price, gold_value from positions.
+
+        For backward compatibility, compute aggregate values from positions list.
+        """
+        if not self.positions:
+            return
+
+        # For now, assume homogeneous positions (same underlying and unit)
+        # Sum quantities and compute weighted average entry price
+        total_quantity = Decimal("0")
+        total_value = Decimal("0")
+
+        for pos in self.positions:
+            if pos.unit == "oz":
+                total_quantity += pos.quantity
+                total_value += pos.entry_value
+
+        if total_quantity > 0:
+            avg_entry_price = total_value / total_quantity
+            self.gold_ounces = float(total_quantity)
+            self.entry_price = float(avg_entry_price)
+            self.gold_value = float(total_value)
+
     def validate(self) -> None:
         """Validate configuration values."""
+        assert self.gold_value is not None
+        assert self.entry_price is not None
+        assert self.gold_ounces is not None
+
         if self.gold_value <= 0:
             raise ValueError("Gold value must be positive")
+        if self.entry_price <= 0:
+            raise ValueError("Entry price must be positive")
+        if self.gold_ounces <= 0:
+            raise ValueError("Gold weight must be positive")
         if self.loan_amount < 0:
             raise ValueError("Loan amount cannot be negative")
         if self.loan_amount >= self.gold_value:
@@ -53,12 +266,15 @@ class PortfolioConfig:
             raise ValueError("Margin threshold must be between 10% and 95%")
         if not 0.1 <= self.ltv_warning <= 0.95:
             raise ValueError("LTV warning level must be between 10% and 95%")
+        if self.ltv_warning >= self.margin_threshold:
+            raise ValueError("LTV warning level must be less than the margin threshold")
         if self.refresh_interval < 1:
             raise ValueError("Refresh interval must be at least 1 second")
 
     @property
     def current_ltv(self) -> float:
         """Calculate current loan-to-value ratio."""
+        assert self.gold_value is not None
         if self.gold_value == 0:
             return 0.0
         return self.loan_amount / self.gold_value
@@ -71,19 +287,29 @@ class PortfolioConfig:
     @property
     def net_equity(self) -> float:
         """Calculate net equity (gold value - loan)."""
+        assert self.gold_value is not None
         return self.gold_value - self.loan_amount
 
     @property
     def margin_call_price(self) -> float:
-        """Calculate gold price at which margin call occurs."""
+        """Calculate gold price per ounce at which margin call occurs."""
-        if self.margin_threshold == 0:
+        assert self.gold_ounces is not None
-            return float('inf')
+        if self.margin_threshold == 0 or self.gold_ounces == 0:
-        return self.loan_amount / self.margin_threshold
+            return float("inf")
+        return self.loan_amount / (self.margin_threshold * self.gold_ounces)
 
     def to_dict(self) -> dict[str, Any]:
         """Convert configuration to dictionary."""
-        return {
+        assert self.gold_value is not None
+        assert self.entry_price is not None
+        assert self.gold_ounces is not None
+        # Sync legacy fields from positions before serializing
+        self._sync_legacy_fields_from_positions()
+        result: dict[str, Any] = {
             "gold_value": self.gold_value,
+            "entry_price": self.entry_price,
+            "gold_ounces": self.gold_ounces,
+            "entry_basis_mode": self.entry_basis_mode,
             "loan_amount": self.loan_amount,
             "margin_threshold": self.margin_threshold,
             "monthly_budget": self.monthly_budget,
@@ -91,15 +317,55 @@ class PortfolioConfig:
             "primary_source": self.primary_source,
             "fallback_source": self.fallback_source,
             "refresh_interval": self.refresh_interval,
+            "underlying": self.underlying,
+            "display_mode": self.display_mode,
             "volatility_spike": self.volatility_spike,
             "spot_drawdown": self.spot_drawdown,
             "email_alerts": self.email_alerts,
         }
+        # Include positions if any exist
+        if self.positions:
+            result["positions"] = [pos.to_dict() for pos in self.positions]
+        return result
 
     @classmethod
     def from_dict(cls, data: dict[str, Any]) -> PortfolioConfig:
         """Create configuration from dictionary."""
-        return cls(**{k: v for k, v in data.items() if k in cls.__dataclass_fields__})
+        # Extract positions if present (may already be Position objects from deserialization)
+        positions_data = data.pop("positions", None)
+        config_data = {k: v for k, v in data.items() if k in cls.__dataclass_fields__}
+
+        # Create config without positions first (will be set in __post_init__)
+        config = cls(**config_data)
+
+        # Set positions after initialization
+        if positions_data:
+            if positions_data and isinstance(positions_data[0], Position):
+                # Already deserialized by _deserialize_value
+                positions = positions_data
+            else:
+                positions = [Position.from_dict(p) for p in positions_data]
+            config.positions = positions
+
+        return config
+
+
+def _coerce_persisted_decimal(value: Any) -> Decimal:
+    if isinstance(value, bool):
+        raise TypeError("Boolean values are not valid decimal persistence inputs")
+    if isinstance(value, Decimal):
+        amount = value
+    elif isinstance(value, int):
+        amount = Decimal(value)
+    elif isinstance(value, float):
+        amount = Decimal(str(value))
+    elif isinstance(value, str):
+        amount = Decimal(value)
+    else:
+        raise TypeError(f"Unsupported persisted decimal input type: {type(value)!r}")
+    if not amount.is_finite():
+        raise ValueError("Decimal persistence value must be finite")
+    return amount
 
 
 class PortfolioRepository:
@@ -109,36 +375,297 @@ class PortfolioRepository:
     """
 
     CONFIG_PATH = Path("data/portfolio_config.json")
+    SCHEMA_VERSION = 2
+    PERSISTENCE_CURRENCY = "USD"
+    PERSISTENCE_WEIGHT_UNIT = "ozt"
+    _WEIGHT_FACTORS = {
+        "g": Decimal("1"),
+        "kg": Decimal("1000"),
+        "ozt": Decimal("31.1034768"),
+    }
+    _MONEY_FIELDS = {"gold_value", "loan_amount", "monthly_budget"}
+    _WEIGHT_FIELDS = {"gold_ounces"}
+    _PRICE_PER_WEIGHT_FIELDS = {"entry_price"}
+    _RATIO_FIELDS = {"margin_threshold", "ltv_warning", "volatility_spike"}
+    _PERCENT_FIELDS = {"spot_drawdown"}
+    _INTEGER_FIELDS = {"refresh_interval"}
+    _PERSISTED_FIELDS = {
+        "gold_value",
+        "entry_price",
+        "gold_ounces",
+        "entry_basis_mode",
+        "loan_amount",
+        "margin_threshold",
+        "monthly_budget",
+        "ltv_warning",
+        "primary_source",
+        "fallback_source",
+        "refresh_interval",
+        "underlying",  # optional with default "GLD"
+        "display_mode",  # optional with default "XAU"
+        "volatility_spike",
+        "spot_drawdown",
+        "email_alerts",
+        "positions",  # multi-position support
+    }
 
-    def __init__(self):
+    def __init__(self, config_path: Path | None = None) -> None:
-        # Ensure data directory exists
+        self.config_path = config_path or self.CONFIG_PATH
-        self.CONFIG_PATH.parent.mkdir(parents=True, exist_ok=True)
+        self.config_path.parent.mkdir(parents=True, exist_ok=True)
 
     def save(self, config: PortfolioConfig) -> None:
         """Save configuration to disk."""
-        with open(self.CONFIG_PATH, "w") as f:
+        payload = self._to_persistence_payload(config)
-            json.dump(config.to_dict(), f, indent=2)
+        tmp_path = self.config_path.with_name(f"{self.config_path.name}.tmp")
+        with open(tmp_path, "w") as f:
+            json.dump(payload, f, indent=2)
+            f.flush()
+            os.fsync(f.fileno())
+        os.replace(tmp_path, self.config_path)
 
     def load(self) -> PortfolioConfig:
         """Load configuration from disk.
 
         Returns default configuration if file doesn't exist.
         """
-        if not self.CONFIG_PATH.exists():
+        if not self.config_path.exists():
             default = PortfolioConfig()
             self.save(default)
             return default
 
         try:
-            with open(self.CONFIG_PATH) as f:
+            with open(self.config_path) as f:
                 data = json.load(f)
-            return PortfolioConfig.from_dict(data)
+        except json.JSONDecodeError as e:
-        except (json.JSONDecodeError, ValueError) as e:
+            raise ValueError(f"Invalid portfolio config JSON: {e}") from e
-            print(f"Warning: Failed to load portfolio config: {e}. Using defaults.")
+
-            return PortfolioConfig()
+        return self._config_from_payload(data)
+
+    @classmethod
+    def _to_persistence_payload(cls, config: PortfolioConfig) -> dict[str, Any]:
+        # Serialize positions separately before calling to_dict
+        positions_data = [pos.to_dict() for pos in config.positions] if config.positions else []
+        config_dict = config.to_dict()
+        # Remove positions from config_dict since we handle it separately
+        config_dict.pop("positions", None)
+        return {
+            "schema_version": cls.SCHEMA_VERSION,
+            "portfolio": {
+                **{key: cls._serialize_value(key, value) for key, value in config_dict.items()},
+                **({"positions": positions_data} if positions_data else {}),
+            },
+        }
+
+    @classmethod
+    def _serialize_value(cls, key: str, value: Any) -> Any:
+        if key in cls._MONEY_FIELDS:
+            return {"value": cls._decimal_to_string(value), "currency": cls.PERSISTENCE_CURRENCY}
+        if key in cls._WEIGHT_FIELDS:
+            return {"value": cls._decimal_to_string(value), "unit": cls.PERSISTENCE_WEIGHT_UNIT}
+        if key in cls._PRICE_PER_WEIGHT_FIELDS:
+            return {
+                "value": cls._decimal_to_string(value),
+                "currency": cls.PERSISTENCE_CURRENCY,
+                "per_weight_unit": cls.PERSISTENCE_WEIGHT_UNIT,
+            }
+        if key in cls._RATIO_FIELDS:
+            return {"value": cls._decimal_to_string(value), "unit": "ratio"}
+        if key in cls._PERCENT_FIELDS:
+            return {"value": cls._decimal_to_string(value), "unit": "percent"}
+        if key in cls._INTEGER_FIELDS:
+            return cls._serialize_integer(value, unit="seconds")
+        if key == "positions" and isinstance(value, list):
+            # Already serialized as dicts from _to_persistence_payload
+            return value
+        return value
+
+    @classmethod
+    def _config_from_payload(cls, data: dict[str, Any]) -> PortfolioConfig:
+        if not isinstance(data, dict):
+            raise TypeError("portfolio config payload must be an object")
+        schema_version = data.get("schema_version")
+        if schema_version != cls.SCHEMA_VERSION:
+            raise ValueError(f"Unsupported portfolio schema_version: {schema_version}")
+        portfolio = data.get("portfolio")
+        if not isinstance(portfolio, dict):
+            raise TypeError("portfolio payload must be an object")
+        cls._validate_portfolio_fields(portfolio)
+        deserialized = cls._deserialize_portfolio_payload(portfolio)
+        upgraded = cls._upgrade_legacy_default_workspace(deserialized)
+        config = PortfolioConfig.from_dict(upgraded)
+        # Migrate legacy configs without positions to single position
+        config.migrate_to_positions_if_needed()
+        return config
+
+    # Fields that must be present in persisted payloads
+    # (underlying is optional with default "GLD")
+    # (positions is optional - legacy configs won't have it)
+    _REQUIRED_FIELDS = (_PERSISTED_FIELDS - {"underlying", "display_mode"}) - {"positions"}
+
+    @classmethod
+    def _validate_portfolio_fields(cls, payload: dict[str, Any]) -> None:
+        keys = set(payload.keys())
+        missing = sorted(cls._REQUIRED_FIELDS - keys)
+        unknown = sorted(keys - cls._PERSISTED_FIELDS)
+        if missing or unknown:
+            details: list[str] = []
+            if missing:
+                details.append(f"missing={missing}")
+            if unknown:
+                details.append(f"unknown={unknown}")
+            raise ValueError(f"Invalid portfolio payload fields: {'; '.join(details)}")
+
+    @classmethod
+    def _deserialize_portfolio_payload(cls, payload: dict[str, Any]) -> dict[str, Any]:
+        return {key: cls._deserialize_value(key, value) for key, value in payload.items()}
+
+    @classmethod
+    def _upgrade_legacy_default_workspace(cls, payload: dict[str, Any]) -> dict[str, Any]:
+        if not cls._looks_like_legacy_default_workspace(payload):
+            return payload
+        upgraded = dict(payload)
+        upgraded["entry_price"] = _DEFAULT_ENTRY_PRICE
+        upgraded["gold_ounces"] = _DEFAULT_GOLD_OUNCES
+        upgraded["gold_value"] = _DEFAULT_GOLD_VALUE
+        return upgraded
+
+    @staticmethod
+    def _looks_like_legacy_default_workspace(payload: dict[str, Any]) -> bool:
+        def _close(key: str, expected: float) -> bool:
+            value = payload.get(key)
+            return isinstance(value, (int, float)) and abs(float(value) - expected) <= 1e-9
+
+        return (
+            _close("gold_value", _DEFAULT_GOLD_VALUE)
+            and _close("entry_price", _LEGACY_DEFAULT_ENTRY_PRICE)
+            and _close("gold_ounces", _LEGACY_DEFAULT_GOLD_OUNCES)
+            and payload.get("entry_basis_mode") == "value_price"
+            and _close("loan_amount", 145_000.0)
+            and _close("margin_threshold", 0.75)
+            and _close("monthly_budget", 8_000.0)
+            and _close("ltv_warning", 0.70)
+            and payload.get("primary_source") == "yfinance"
+            and payload.get("fallback_source") == "yfinance"
+            and payload.get("refresh_interval") == 5
+            and _close("volatility_spike", 0.25)
+            and _close("spot_drawdown", 7.5)
+            and payload.get("email_alerts") is False
+        )
+
+    @classmethod
+    def _deserialize_value(cls, key: str, value: Any) -> Any:
+        if key in cls._MONEY_FIELDS:
+            return float(cls._deserialize_money(value))
+        if key in cls._WEIGHT_FIELDS:
+            return float(cls._deserialize_weight(value))
+        if key in cls._PRICE_PER_WEIGHT_FIELDS:
+            return float(cls._deserialize_price_per_weight(value))
+        if key in cls._RATIO_FIELDS:
+            return float(cls._deserialize_ratio(value))
+        if key in cls._PERCENT_FIELDS:
+            return float(cls._deserialize_percent(value))
+        if key in cls._INTEGER_FIELDS:
+            return cls._deserialize_integer(value, expected_unit="seconds")
+        if key == "positions" and isinstance(value, list):
+            return [Position.from_dict(p) for p in value]
+        return value
+
+    @classmethod
+    def _deserialize_money(cls, value: Any) -> Decimal:
+        if not isinstance(value, dict):
+            raise TypeError("money field must be an object")
+        currency = value.get("currency")
+        if currency != cls.PERSISTENCE_CURRENCY:
+            raise ValueError(f"Unsupported currency: {currency!r}")
+        return _coerce_persisted_decimal(value.get("value"))
+
+    @classmethod
+    def _deserialize_weight(cls, value: Any) -> Decimal:
+        if not isinstance(value, dict):
+            raise TypeError("weight field must be an object")
+        amount = _coerce_persisted_decimal(value.get("value"))
+        unit = value.get("unit")
+        return cls._convert_weight(amount, unit, cls.PERSISTENCE_WEIGHT_UNIT)
+
+    @classmethod
+    def _deserialize_price_per_weight(cls, value: Any) -> Decimal:
+        if not isinstance(value, dict):
+            raise TypeError("price-per-weight field must be an object")
+        currency = value.get("currency")
+        if currency != cls.PERSISTENCE_CURRENCY:
+            raise ValueError(f"Unsupported currency: {currency!r}")
+        amount = _coerce_persisted_decimal(value.get("value"))
+        unit = value.get("per_weight_unit")
+        return cls._convert_price_per_weight(amount, unit, cls.PERSISTENCE_WEIGHT_UNIT)
+
+    @classmethod
+    def _deserialize_ratio(cls, value: Any) -> Decimal:
+        if not isinstance(value, dict):
+            raise TypeError("ratio field must be an object")
+        amount = _coerce_persisted_decimal(value.get("value"))
+        unit = value.get("unit")
+        if unit == "ratio":
+            return amount
+        if unit == "percent":
+            return amount / Decimal("100")
+        raise ValueError(f"Unsupported ratio unit: {unit!r}")
+
+    @classmethod
+    def _deserialize_percent(cls, value: Any) -> Decimal:
+        if not isinstance(value, dict):
+            raise TypeError("percent field must be an object")
+        amount = _coerce_persisted_decimal(value.get("value"))
+        unit = value.get("unit")
+        if unit == "percent":
+            return amount
+        if unit == "ratio":
+            return amount * Decimal("100")
+        raise ValueError(f"Unsupported percent unit: {unit!r}")
+
+    @staticmethod
+    def _serialize_integer(value: Any, *, unit: str) -> dict[str, Any]:
+        if isinstance(value, bool) or not isinstance(value, int):
+            raise TypeError("integer field value must be an int")
+        return {"value": value, "unit": unit}
+
+    @staticmethod
+    def _deserialize_integer(value: Any, *, expected_unit: str) -> int:
+        if not isinstance(value, dict):
+            raise TypeError("integer field must be an object")
+        unit = value.get("unit")
+        if unit != expected_unit:
+            raise ValueError(f"Unsupported integer unit: {unit!r}")
+        raw = value.get("value")
+        if isinstance(raw, bool) or not isinstance(raw, int):
+            raise TypeError("integer field value must be an int")
+        return raw
+
+    @classmethod
+    def _convert_weight(cls, amount: Decimal, from_unit: Any, to_unit: str) -> Decimal:
+        if from_unit not in cls._WEIGHT_FACTORS or to_unit not in cls._WEIGHT_FACTORS:
+            raise ValueError(f"Unsupported weight unit conversion: {from_unit!r} -> {to_unit!r}")
+        if from_unit == to_unit:
+            return amount
+        grams = amount * cls._WEIGHT_FACTORS[from_unit]
+        return grams / cls._WEIGHT_FACTORS[to_unit]
+
+    @classmethod
+    def _convert_price_per_weight(cls, amount: Decimal, from_unit: Any, to_unit: str) -> Decimal:
+        if from_unit not in cls._WEIGHT_FACTORS or to_unit not in cls._WEIGHT_FACTORS:
+            raise ValueError(f"Unsupported price-per-weight unit conversion: {from_unit!r} -> {to_unit!r}")
+        if from_unit == to_unit:
+            return amount
+        return amount * cls._WEIGHT_FACTORS[to_unit] / cls._WEIGHT_FACTORS[from_unit]
+
+    @staticmethod
+    def _decimal_to_string(value: Any) -> str:
+        decimal_value = _coerce_persisted_decimal(value)
+        normalized = format(decimal_value, "f")
+        if "." not in normalized:
+            normalized = f"{normalized}.0"
+        return normalized
 
 
-# Singleton repository instance
 _portfolio_repo: PortfolioRepository | None = None
 
 

app/models/position.py

@@ -0,0 +1,155 @@
+"""Position model for multi-position portfolio entries."""
+
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from datetime import UTC, date, datetime
+from decimal import Decimal
+from typing import Any
+from uuid import UUID, uuid4
+
+
+@dataclass(frozen=True)
+class Position:
+    """A single position entry in a portfolio.
+
+    Attributes:
+        id: Unique identifier for this position
+        underlying: Underlying instrument symbol (e.g., "GLD", "GC=F", "XAU")
+        quantity: Number of units held (shares, contracts, grams, or oz)
+        unit: Unit of quantity (e.g., "shares", "contracts", "g", "oz")
+        entry_price: Price per unit at purchase (in USD)
+        entry_date: Date of position entry (for historical conversion lookups)
+        entry_basis_mode: Entry basis mode ("weight" or "value_price")
+        purchase_premium: Dealer markup over spot as percentage (e.g., Decimal("0.04") for 4%)
+        bid_ask_spread: Expected sale discount below spot as percentage (e.g., Decimal("0.03") for 3%)
+        notes: Optional notes about this position
+        storage_cost_basis: Annual storage cost as percentage (e.g., Decimal("0.12") for 0.12%) or fixed amount
+        storage_cost_period: Period for storage cost ("annual" or "monthly")
+        storage_cost_currency: Currency for fixed amount costs (default "USD")
+        created_at: Timestamp when position was created
+    """
+
+    id: UUID
+    underlying: str
+    quantity: Decimal
+    unit: str
+    entry_price: Decimal
+    entry_date: date
+    entry_basis_mode: str = "weight"
+    purchase_premium: Decimal | None = None
+    bid_ask_spread: Decimal | None = None
+    notes: str = ""
+    storage_cost_basis: Decimal | None = None
+    storage_cost_period: str | None = None
+    storage_cost_currency: str = "USD"
+    created_at: datetime = field(default_factory=lambda: datetime.now(UTC))
+
+    def __post_init__(self) -> None:
+        """Validate position fields."""
+        if not self.underlying:
+            raise ValueError("underlying must be non-empty")
+        # Use object.__getattribute__ because Decimal comparison with frozen dataclass
+        quantity = object.__getattribute__(self, "quantity")
+        entry_price = object.__getattribute__(self, "entry_price")
+        if quantity <= 0:
+            raise ValueError("quantity must be positive")
+        if not self.unit:
+            raise ValueError("unit must be non-empty")
+        if entry_price <= 0:
+            raise ValueError("entry_price must be positive")
+        if self.entry_basis_mode not in {"weight", "value_price"}:
+            raise ValueError("entry_basis_mode must be 'weight' or 'value_price'")
+
+    @property
+    def entry_value(self) -> Decimal:
+        """Calculate total entry value (quantity × entry_price)."""
+        return self.quantity * self.entry_price
+
+    def to_dict(self) -> dict[str, Any]:
+        """Convert position to dictionary for serialization."""
+        return {
+            "id": str(self.id),
+            "underlying": self.underlying,
+            "quantity": str(self.quantity),
+            "unit": self.unit,
+            "entry_price": str(self.entry_price),
+            "entry_date": self.entry_date.isoformat(),
+            "entry_basis_mode": self.entry_basis_mode,
+            "purchase_premium": str(self.purchase_premium) if self.purchase_premium is not None else None,
+            "bid_ask_spread": str(self.bid_ask_spread) if self.bid_ask_spread is not None else None,
+            "notes": self.notes,
+            "storage_cost_basis": str(self.storage_cost_basis) if self.storage_cost_basis is not None else None,
+            "storage_cost_period": self.storage_cost_period,
+            "storage_cost_currency": self.storage_cost_currency,
+            "created_at": self.created_at.isoformat(),
+        }
+
+    @classmethod
+    def from_dict(cls, data: dict[str, Any]) -> Position:
+        """Create position from dictionary."""
+        return cls(
+            id=UUID(data["id"]) if isinstance(data["id"], str) else data["id"],
+            underlying=data["underlying"],
+            quantity=Decimal(data["quantity"]),
+            unit=data["unit"],
+            entry_price=Decimal(data["entry_price"]),
+            entry_date=date.fromisoformat(data["entry_date"]),
+            entry_basis_mode=data.get("entry_basis_mode", "weight"),
+            purchase_premium=(Decimal(data["purchase_premium"]) if data.get("purchase_premium") is not None else None),
+            bid_ask_spread=(Decimal(data["bid_ask_spread"]) if data.get("bid_ask_spread") is not None else None),
+            notes=data.get("notes", ""),
+            storage_cost_basis=(
+                Decimal(data["storage_cost_basis"]) if data.get("storage_cost_basis") is not None else None
+            ),
+            storage_cost_period=data.get("storage_cost_period"),
+            storage_cost_currency=data.get("storage_cost_currency", "USD"),
+            created_at=datetime.fromisoformat(data["created_at"]) if "created_at" in data else datetime.now(UTC),
+        )
+
+
+def create_position(
+    underlying: str = "GLD",
+    quantity: Decimal | None = None,
+    unit: str = "oz",
+    entry_price: Decimal | None = None,
+    entry_date: date | None = None,
+    entry_basis_mode: str = "weight",
+    purchase_premium: Decimal | None = None,
+    bid_ask_spread: Decimal | None = None,
+    notes: str = "",
+    storage_cost_basis: Decimal | None = None,
+    storage_cost_period: str | None = None,
+    storage_cost_currency: str = "USD",
+) -> Position:
+    """Create a new position with sensible defaults.
+
+    Args:
+        underlying: Underlying instrument (default: "GLD")
+        quantity: Position quantity (default: Decimal("100"))
+        unit: Unit of quantity (default: "oz")
+        entry_price: Entry price per unit (default: Decimal("2150"))
+        entry_date: Entry date (default: today)
+        entry_basis_mode: Entry basis mode (default: "weight")
+        purchase_premium: Dealer markup over spot as percentage (default: None)
+        bid_ask_spread: Expected sale discount below spot as percentage (default: None)
+        notes: Optional notes
+        storage_cost_basis: Annual storage cost as percentage or fixed amount (default: None)
+        storage_cost_period: Period for storage cost ("annual" or "monthly", default: None)
+        storage_cost_currency: Currency for fixed amount costs (default: "USD")
+    """
+    return Position(
+        id=uuid4(),
+        underlying=underlying,
+        quantity=quantity if quantity is not None else Decimal("100"),
+        unit=unit,
+        entry_price=entry_price if entry_price is not None else Decimal("2150"),
+        entry_date=entry_date or date.today(),
+        entry_basis_mode=entry_basis_mode,
+        purchase_premium=purchase_premium,
+        bid_ask_spread=bid_ask_spread,
+        notes=notes,
+        storage_cost_basis=storage_cost_basis,
+        storage_cost_period=storage_cost_period,
+        storage_cost_currency=storage_cost_currency,
+    )

app/models/strategy_template.py

@@ -0,0 +1,309 @@
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from datetime import datetime, timezone
+from typing import Any, Literal
+
+StrategyTemplateKind = Literal["protective_put", "laddered_put"]
+StrategyTemplateStatus = Literal["draft", "active", "archived"]
+ContractMode = Literal["continuous_units", "listed_contracts"]
+LegSide = Literal["long", "short"]
+LegOptionType = Literal["put", "call"]
+StrikeRuleType = Literal["spot_pct"]
+QuantityRule = Literal["target_coverage_pct"]
+RollPolicyType = Literal["hold_to_expiry", "roll_n_days_before_expiry"]
+EntryTiming = Literal["scenario_start_close"]
+
+
+@dataclass(frozen=True)
+class StrikeRule:
+    rule_type: StrikeRuleType
+    value: float
+
+    def __post_init__(self) -> None:
+        if self.rule_type != "spot_pct":
+            raise ValueError("unsupported strike rule")
+        if self.value <= 0:
+            raise ValueError("strike rule value must be positive")
+
+    def to_dict(self) -> dict[str, Any]:
+        return {"rule_type": self.rule_type, "value": self.value}
+
+    @classmethod
+    def from_dict(cls, payload: dict[str, Any]) -> StrikeRule:
+        return cls(rule_type=payload["rule_type"], value=float(payload["value"]))
+
+
+@dataclass(frozen=True)
+class TemplateLeg:
+    leg_id: str
+    side: LegSide
+    option_type: LegOptionType
+    allocation_weight: float
+    strike_rule: StrikeRule
+    target_expiry_days: int
+    quantity_rule: QuantityRule
+    target_coverage_pct: float = 1.0
+
+    def __post_init__(self) -> None:
+        if self.side not in {"long", "short"}:
+            raise ValueError("unsupported leg side")
+        if self.option_type not in {"put", "call"}:
+            raise ValueError("unsupported option type")
+        if self.allocation_weight <= 0:
+            raise ValueError("allocation_weight must be positive")
+        if self.target_expiry_days <= 0:
+            raise ValueError("target_expiry_days must be positive")
+        if self.quantity_rule != "target_coverage_pct":
+            raise ValueError("unsupported quantity rule")
+        if self.target_coverage_pct <= 0:
+            raise ValueError("target_coverage_pct must be positive")
+
+    def to_dict(self) -> dict[str, Any]:
+        return {
+            "leg_id": self.leg_id,
+            "side": self.side,
+            "option_type": self.option_type,
+            "allocation_weight": self.allocation_weight,
+            "strike_rule": self.strike_rule.to_dict(),
+            "target_expiry_days": self.target_expiry_days,
+            "quantity_rule": self.quantity_rule,
+            "target_coverage_pct": self.target_coverage_pct,
+        }
+
+    @classmethod
+    def from_dict(cls, payload: dict[str, Any]) -> TemplateLeg:
+        return cls(
+            leg_id=payload["leg_id"],
+            side=payload["side"],
+            option_type=payload["option_type"],
+            allocation_weight=float(payload["allocation_weight"]),
+            strike_rule=StrikeRule.from_dict(payload["strike_rule"]),
+            target_expiry_days=int(payload["target_expiry_days"]),
+            quantity_rule=payload.get("quantity_rule", "target_coverage_pct"),
+            target_coverage_pct=float(payload.get("target_coverage_pct", 1.0)),
+        )
+
+
+@dataclass(frozen=True)
+class RollPolicy:
+    policy_type: RollPolicyType
+    days_before_expiry: int | None = None
+    rebalance_on_new_deposit: bool = False
+
+    def __post_init__(self) -> None:
+        if self.policy_type not in {"hold_to_expiry", "roll_n_days_before_expiry"}:
+            raise ValueError("unsupported roll policy")
+        if self.policy_type == "roll_n_days_before_expiry" and (self.days_before_expiry or 0) <= 0:
+            raise ValueError("days_before_expiry is required for rolling policies")
+
+    def to_dict(self) -> dict[str, Any]:
+        return {
+            "policy_type": self.policy_type,
+            "days_before_expiry": self.days_before_expiry,
+            "rebalance_on_new_deposit": self.rebalance_on_new_deposit,
+        }
+
+    @classmethod
+    def from_dict(cls, payload: dict[str, Any]) -> RollPolicy:
+        return cls(
+            policy_type=payload["policy_type"],
+            days_before_expiry=payload.get("days_before_expiry"),
+            rebalance_on_new_deposit=bool(payload.get("rebalance_on_new_deposit", False)),
+        )
+
+
+@dataclass(frozen=True)
+class EntryPolicy:
+    entry_timing: EntryTiming
+    stagger_days: int | None = None
+
+    def __post_init__(self) -> None:
+        if self.entry_timing != "scenario_start_close":
+            raise ValueError("unsupported entry timing")
+        if self.stagger_days is not None and self.stagger_days < 0:
+            raise ValueError("stagger_days must be non-negative")
+
+    def to_dict(self) -> dict[str, Any]:
+        return {"entry_timing": self.entry_timing, "stagger_days": self.stagger_days}
+
+    @classmethod
+    def from_dict(cls, payload: dict[str, Any]) -> EntryPolicy:
+        return cls(entry_timing=payload["entry_timing"], stagger_days=payload.get("stagger_days"))
+
+
+@dataclass(frozen=True)
+class StrategyTemplate:
+    template_id: str
+    slug: str
+    display_name: str
+    description: str
+    template_kind: StrategyTemplateKind
+    status: StrategyTemplateStatus
+    version: int
+    underlying_symbol: str
+    contract_mode: ContractMode
+    legs: tuple[TemplateLeg, ...]
+    roll_policy: RollPolicy
+    entry_policy: EntryPolicy
+    tags: tuple[str, ...] = field(default_factory=tuple)
+    created_at: datetime = field(default_factory=lambda: datetime.now(timezone.utc))
+    updated_at: datetime = field(default_factory=lambda: datetime.now(timezone.utc))
+
+    def __post_init__(self) -> None:
+        if self.template_kind not in {"protective_put", "laddered_put"}:
+            raise ValueError("unsupported template_kind")
+        if self.status not in {"draft", "active", "archived"}:
+            raise ValueError("unsupported template status")
+        if self.contract_mode not in {"continuous_units", "listed_contracts"}:
+            raise ValueError("unsupported contract mode")
+        if not self.slug:
+            raise ValueError("slug is required")
+        if not self.display_name:
+            raise ValueError("display_name is required")
+        if self.version <= 0:
+            raise ValueError("version must be positive")
+        if not self.legs:
+            raise ValueError("at least one template leg is required")
+        if self.template_kind in {"protective_put", "laddered_put"}:
+            if any(leg.side != "long" or leg.option_type != "put" for leg in self.legs):
+                raise ValueError("put templates support only long put legs")
+            total_weight = sum(leg.allocation_weight for leg in self.legs)
+            if abs(total_weight - 1.0) > 1e-9:
+                raise ValueError("weights must sum to 1.0")
+        expiry_days = {leg.target_expiry_days for leg in self.legs}
+        if len(expiry_days) != 1:
+            raise ValueError("all template legs must share target_expiry_days in MVP")
+
+    @property
+    def target_expiry_days(self) -> int:
+        return self.legs[0].target_expiry_days
+
+    def to_dict(self) -> dict[str, Any]:
+        return {
+            "template_id": self.template_id,
+            "slug": self.slug,
+            "display_name": self.display_name,
+            "description": self.description,
+            "template_kind": self.template_kind,
+            "status": self.status,
+            "version": self.version,
+            "underlying_symbol": self.underlying_symbol,
+            "contract_mode": self.contract_mode,
+            "legs": [leg.to_dict() for leg in self.legs],
+            "roll_policy": self.roll_policy.to_dict(),
+            "entry_policy": self.entry_policy.to_dict(),
+            "tags": list(self.tags),
+            "created_at": self.created_at.isoformat(),
+            "updated_at": self.updated_at.isoformat(),
+        }
+
+    @classmethod
+    def from_dict(cls, payload: dict[str, Any]) -> StrategyTemplate:
+        return cls(
+            template_id=payload["template_id"],
+            slug=payload["slug"],
+            display_name=payload["display_name"],
+            description=payload.get("description", ""),
+            template_kind=payload["template_kind"],
+            status=payload.get("status", "active"),
+            version=int(payload.get("version", 1)),
+            underlying_symbol=payload.get("underlying_symbol", "GLD"),
+            contract_mode=payload.get("contract_mode", "continuous_units"),
+            legs=tuple(TemplateLeg.from_dict(leg) for leg in payload["legs"]),
+            roll_policy=RollPolicy.from_dict(payload["roll_policy"]),
+            entry_policy=EntryPolicy.from_dict(payload["entry_policy"]),
+            tags=tuple(payload.get("tags", [])),
+            created_at=datetime.fromisoformat(payload["created_at"]),
+            updated_at=datetime.fromisoformat(payload["updated_at"]),
+        )
+
+    @classmethod
+    def protective_put(
+        cls,
+        *,
+        template_id: str,
+        slug: str,
+        display_name: str,
+        description: str,
+        strike_pct: float,
+        target_expiry_days: int,
+        underlying_symbol: str = "GLD",
+        tags: tuple[str, ...] = (),
+    ) -> StrategyTemplate:
+        now = datetime.now(timezone.utc)
+        return cls(
+            template_id=template_id,
+            slug=slug,
+            display_name=display_name,
+            description=description,
+            template_kind="protective_put",
+            status="active",
+            version=1,
+            underlying_symbol=underlying_symbol,
+            contract_mode="continuous_units",
+            legs=(
+                TemplateLeg(
+                    leg_id=f"{template_id}-leg-1",
+                    side="long",
+                    option_type="put",
+                    allocation_weight=1.0,
+                    strike_rule=StrikeRule(rule_type="spot_pct", value=strike_pct),
+                    target_expiry_days=target_expiry_days,
+                    quantity_rule="target_coverage_pct",
+                    target_coverage_pct=1.0,
+                ),
+            ),
+            roll_policy=RollPolicy(policy_type="hold_to_expiry"),
+            entry_policy=EntryPolicy(entry_timing="scenario_start_close"),
+            tags=tags,
+            created_at=now,
+            updated_at=now,
+        )
+
+    @classmethod
+    def laddered_put(
+        cls,
+        *,
+        template_id: str,
+        slug: str,
+        display_name: str,
+        description: str,
+        strike_pcts: tuple[float, ...],
+        weights: tuple[float, ...],
+        target_expiry_days: int,
+        underlying_symbol: str = "GLD",
+        tags: tuple[str, ...] = (),
+    ) -> StrategyTemplate:
+        if len(strike_pcts) != len(weights):
+            raise ValueError("strike_pcts and weights must have the same length")
+        now = datetime.now(timezone.utc)
+        return cls(
+            template_id=template_id,
+            slug=slug,
+            display_name=display_name,
+            description=description,
+            template_kind="laddered_put",
+            status="active",
+            version=1,
+            underlying_symbol=underlying_symbol,
+            contract_mode="continuous_units",
+            legs=tuple(
+                TemplateLeg(
+                    leg_id=f"{template_id}-leg-{index}",
+                    side="long",
+                    option_type="put",
+                    allocation_weight=weight,
+                    strike_rule=StrikeRule(rule_type="spot_pct", value=strike_pct),
+                    target_expiry_days=target_expiry_days,
+                    quantity_rule="target_coverage_pct",
+                    target_coverage_pct=1.0,
+                )
+                for index, (strike_pct, weight) in enumerate(zip(strike_pcts, weights, strict=True), start=1)
+            ),
+            roll_policy=RollPolicy(policy_type="hold_to_expiry"),
+            entry_policy=EntryPolicy(entry_timing="scenario_start_close"),
+            tags=tags,
+            created_at=now,
+            updated_at=now,
+        )

app/models/workspace.py

@@ -0,0 +1,141 @@
+from __future__ import annotations
+
+import re
+from pathlib import Path
+from uuid import UUID, uuid4
+
+from app.models.portfolio import PortfolioConfig, PortfolioRepository, build_default_portfolio_config
+from app.models.position import Position
+
+WORKSPACE_COOKIE = "workspace_id"
+_WORKSPACE_ID_RE = re.compile(
+    r"^[0-9a-f]{8}-[0-9a-f]{4}-4[0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}$",
+    re.IGNORECASE,
+)
+
+
+class WorkspaceRepository:
+    """Persist workspace-scoped portfolio configuration on disk."""
+
+    def __init__(self, base_path: Path | str = Path("data/workspaces")) -> None:
+        self.base_path = Path(base_path)
+        self.base_path.mkdir(parents=True, exist_ok=True)
+
+    def is_valid_workspace_id(self, workspace_id: str) -> bool:
+        return bool(_WORKSPACE_ID_RE.match(workspace_id))
+
+    def workspace_exists(self, workspace_id: str) -> bool:
+        if not self.is_valid_workspace_id(workspace_id):
+            return False
+        portfolio_path = self._portfolio_path(workspace_id)
+        if not portfolio_path.exists():
+            return False
+        try:
+            PortfolioRepository(portfolio_path).load()
+        except (ValueError, TypeError, FileNotFoundError):
+            return False
+        return True
+
+    def create_workspace(
+        self,
+        workspace_id: str | None = None,
+        *,
+        config: PortfolioConfig | None = None,
+    ) -> PortfolioConfig:
+        resolved_workspace_id = workspace_id or str(uuid4())
+        if not self.is_valid_workspace_id(resolved_workspace_id):
+            raise ValueError("workspace_id must be a UUID4 string")
+        created_config = config or build_default_portfolio_config()
+        self.save_portfolio_config(resolved_workspace_id, created_config)
+        return created_config
+
+    def create_workspace_id(self, *, config: PortfolioConfig | None = None) -> str:
+        workspace_id = str(uuid4())
+        self.create_workspace(workspace_id, config=config)
+        return workspace_id
+
+    def load_portfolio_config(self, workspace_id: str) -> PortfolioConfig:
+        if not self.workspace_exists(workspace_id):
+            raise FileNotFoundError(f"Unknown workspace: {workspace_id}")
+        return PortfolioRepository(self._portfolio_path(workspace_id)).load()
+
+    def save_portfolio_config(self, workspace_id: str, config: PortfolioConfig) -> None:
+        if not self.is_valid_workspace_id(workspace_id):
+            raise ValueError("workspace_id must be a UUID4 string")
+        PortfolioRepository(self._portfolio_path(workspace_id)).save(config)
+
+    def add_position(self, workspace_id: str, position: Position) -> None:
+        """Add a position to the workspace portfolio."""
+        if not self.is_valid_workspace_id(workspace_id):
+            raise ValueError("workspace_id must be a UUID4 string")
+        config = self.load_portfolio_config(workspace_id)
+        # Use object.__setattr__ because positions is in a frozen dataclass
+        object.__setattr__(config, "positions", list(config.positions) + [position])
+        self.save_portfolio_config(workspace_id, config)
+
+    def remove_position(self, workspace_id: str, position_id: UUID) -> None:
+        """Remove a position from the workspace portfolio."""
+        if not self.is_valid_workspace_id(workspace_id):
+            raise ValueError("workspace_id must be a UUID4 string")
+        config = self.load_portfolio_config(workspace_id)
+        updated_positions = [p for p in config.positions if p.id != position_id]
+        object.__setattr__(config, "positions", updated_positions)
+        self.save_portfolio_config(workspace_id, config)
+
+    def update_position(
+        self,
+        workspace_id: str,
+        position_id: UUID,
+        updates: dict[str, object],
+    ) -> None:
+        """Update a position's fields."""
+        if not self.is_valid_workspace_id(workspace_id):
+            raise ValueError("workspace_id must be a UUID4 string")
+        config = self.load_portfolio_config(workspace_id)
+        updated_positions = []
+        for pos in config.positions:
+            if pos.id == position_id:
+                # Create updated position (Position is frozen, so create new instance)
+                update_kwargs: dict[str, object] = {}
+                for key, value in updates.items():
+                    if key in {"id", "created_at"}:
+                        continue  # Skip immutable fields
+                    update_kwargs[key] = value
+                # Use dataclass replace-like pattern
+                pos_dict = pos.to_dict()
+                pos_dict.update(update_kwargs)
+                updated_positions.append(Position.from_dict(pos_dict))
+            else:
+                updated_positions.append(pos)
+        object.__setattr__(config, "positions", updated_positions)
+        self.save_portfolio_config(workspace_id, config)
+
+    def get_position(self, workspace_id: str, position_id: UUID) -> Position | None:
+        """Get a specific position by ID."""
+        if not self.is_valid_workspace_id(workspace_id):
+            raise ValueError("workspace_id must be a UUID4 string")
+        config = self.load_portfolio_config(workspace_id)
+        for pos in config.positions:
+            if pos.id == position_id:
+                return pos
+        return None
+
+    def list_positions(self, workspace_id: str) -> list[Position]:
+        """List all positions in the workspace portfolio."""
+        if not self.is_valid_workspace_id(workspace_id):
+            raise ValueError("workspace_id must be a UUID4 string")
+        config = self.load_portfolio_config(workspace_id)
+        return list(config.positions)
+
+    def _portfolio_path(self, workspace_id: str) -> Path:
+        return self.base_path / workspace_id / "portfolio_config.json"
+
+
+_workspace_repo: WorkspaceRepository | None = None
+
+
+def get_workspace_repository() -> WorkspaceRepository:
+    global _workspace_repo
+    if _workspace_repo is None:
+        _workspace_repo = WorkspaceRepository()
+    return _workspace_repo

app/pages/__init__.py

@@ -1,3 +1,3 @@
-from . import hedge, options, overview, settings
+from . import backtests, event_comparison, hedge, options, overview, settings
 
-__all__ = ["overview", "hedge", "options", "settings"]
+__all__ = ["overview", "hedge", "options", "backtests", "event_comparison", "settings"]

app/pages/common.py

@@ -6,74 +6,52 @@ from typing import Any
 
 from nicegui import ui
 
+from app.domain.portfolio_math import portfolio_snapshot_from_config, strategy_metrics_from_snapshot
+from app.models.portfolio import PortfolioConfig
+from app.services.strategy_templates import StrategyTemplateService
+
 NAV_ITEMS: list[tuple[str, str, str]] = [
-    ("overview", "/", "Overview"),
+    ("welcome", "/", "Welcome"),
-    ("hedge", "/hedge", "Hedge Analysis"),
     ("options", "/options", "Options Chain"),
-    ("settings", "/settings", "Settings"),
 ]
 
 
+def nav_items(workspace_id: str | None = None) -> list[tuple[str, str, str]]:
+    if not workspace_id:
+        return NAV_ITEMS
+    return [
+        ("overview", f"/{workspace_id}", "Overview"),
+        ("hedge", f"/{workspace_id}/hedge", "Hedge Analysis"),
+        ("options", "/options", "Options Chain"),
+        ("backtests", f"/{workspace_id}/backtests", "Backtests"),
+        ("event-comparison", f"/{workspace_id}/event-comparison", "Event Comparison"),
+        ("settings", f"/{workspace_id}/settings", "Settings"),
+    ]
+
+
 def demo_spot_price() -> float:
     return 215.0
 
 
-def portfolio_snapshot() -> dict[str, float]:
+def portfolio_snapshot(
-    gold_units = 1_000.0
+    config: PortfolioConfig | None = None,
-    spot = demo_spot_price()
+    *,
-    gold_value = gold_units * spot
+    runtime_spot_price: float | None = None,
-    loan_amount = 145_000.0
+) -> dict[str, float]:
-    margin_call_ltv = 0.75
+    return portfolio_snapshot_from_config(config, runtime_spot_price=runtime_spot_price)
-    return {
-        "gold_value": gold_value,
-        "loan_amount": loan_amount,
-        "ltv_ratio": loan_amount / gold_value,
-        "net_equity": gold_value - loan_amount,
-        "spot_price": spot,
-        "margin_call_ltv": margin_call_ltv,
-        "margin_call_price": loan_amount / (margin_call_ltv * gold_units),
-        "cash_buffer": 18_500.0,
-        "hedge_budget": 8_000.0,
-    }
 
 
 def strategy_catalog() -> list[dict[str, Any]]:
-    return [
+    return StrategyTemplateService().catalog_items()
-        {
-            "name": "protective_put",
-            "label": "Protective Put",
-            "description": "Full downside protection below the hedge strike with uncapped upside.",
-            "estimated_cost": 6.25,
-            "max_drawdown_floor": 210.0,
-            "coverage": "High",
-        },
-        {
-            "name": "collar",
-            "label": "Collar",
-            "description": "Lower premium by financing puts with covered call upside caps.",
-            "estimated_cost": 2.10,
-            "max_drawdown_floor": 208.0,
-            "upside_cap": 228.0,
-            "coverage": "Balanced",
-        },
-        {
-            "name": "laddered_puts",
-            "label": "Laddered Puts",
-            "description": "Multiple maturities and strikes reduce roll concentration and smooth protection.",
-            "estimated_cost": 4.45,
-            "max_drawdown_floor": 205.0,
-            "coverage": "Layered",
-        },
-    ]
 
 
-def quick_recommendations() -> list[dict[str, str]]:
+def quick_recommendations(portfolio: dict[str, Any] | None = None) -> list[dict[str, str]]:
-    portfolio = portfolio_snapshot()
+    portfolio = portfolio or portfolio_snapshot()
     ltv_gap = (portfolio["margin_call_ltv"] - portfolio["ltv_ratio"]) * 100
     return [
         {
             "title": "Balanced hedge favored",
-            "summary": "A collar keeps the current LTV comfortably below the margin threshold while limiting upfront spend.",
+            "summary": "A 95% protective put balances margin-call protection with a lower upfront hedge cost.",
             "tone": "positive",
         },
         {
@@ -131,59 +109,34 @@ def option_chain() -> list[dict[str, Any]]:
     return rows
 
 
-def strategy_metrics(strategy_name: str, scenario_pct: int) -> dict[str, Any]:
+def strategy_metrics(
+    strategy_key: str,
+    scenario_pct: int,
+    *,
+    portfolio: dict[str, Any] | None = None,
+) -> dict[str, Any]:
+    catalog = strategy_catalog()
     strategy = next(
-        (item for item in strategy_catalog() if item["name"] == strategy_name),
+        (item for item in catalog if item.get("template_slug") == strategy_key or item.get("name") == strategy_key),
-        strategy_catalog()[0],
+        catalog[0],
     )
-    spot = demo_spot_price()
+    portfolio = portfolio or portfolio_snapshot()
-    floor = float(strategy.get("max_drawdown_floor", spot * 0.95))
+    return strategy_metrics_from_snapshot(strategy, scenario_pct, portfolio)
-    cap = strategy.get("upside_cap")
-    cost = float(strategy["estimated_cost"])
 
-    scenario_prices = [round(spot * (1 + pct / 100), 2) for pct in range(-25, 30, 5)]
-    benefits: list[float] = []
-    for price in scenario_prices:
-        payoff = max(floor - price, 0.0)
-        if isinstance(cap, (int, float)) and price > float(cap):
-            payoff -= price - float(cap)
-        benefits.append(round(payoff - cost, 2))
 
-    scenario_price = round(spot * (1 + scenario_pct / 100), 2)
+def split_page_panes(*, left_testid: str, right_testid: str) -> tuple[ui.column, ui.column]:
-    unhedged_equity = scenario_price * 1_000 - 145_000.0
+    """Render responsive page panes with a desktop 1:2 flex split and stable test hooks."""
-    scenario_payoff = max(floor - scenario_price, 0.0)
+    with ui.row().classes("w-full items-start gap-6 max-lg:flex-col lg:flex-nowrap"):
-    capped_upside = 0.0
+        left = ui.column().classes("min-w-0 w-full gap-6 lg:flex-[1_1_0%]").props(f"data-testid={left_testid}")
-    if isinstance(cap, (int, float)) and scenario_price > float(cap):
+        right = ui.column().classes("min-w-0 w-full gap-6 lg:flex-[2_1_0%]").props(f"data-testid={right_testid}")
-        capped_upside = -(scenario_price - float(cap))
+    return left, right
-    hedged_equity = unhedged_equity + scenario_payoff + capped_upside - cost * 1_000
-
-    waterfall_steps = [
-        ("Base equity", round(70_000.0, 2)),
-        ("Spot move", round((scenario_price - spot) * 1_000, 2)),
-        ("Option payoff", round(scenario_payoff * 1_000, 2)),
-        ("Call cap", round(capped_upside * 1_000, 2)),
-        ("Hedge cost", round(-cost * 1_000, 2)),
-        ("Net equity", round(hedged_equity, 2)),
-    ]
-
-    return {
-        "strategy": strategy,
-        "scenario_pct": scenario_pct,
-        "scenario_price": scenario_price,
-        "scenario_series": [
-            {"price": price, "benefit": benefit} for price, benefit in zip(scenario_prices, benefits, strict=True)
-        ],
-        "waterfall_steps": waterfall_steps,
-        "unhedged_equity": round(unhedged_equity, 2),
-        "hedged_equity": round(hedged_equity, 2),
-    }
 
 
 @contextmanager
-def dashboard_page(title: str, subtitle: str, current: str) -> Iterator[ui.column]:
+def dashboard_page(title: str, subtitle: str, current: str, workspace_id: str | None = None) -> Iterator[ui.column]:
     ui.colors(primary="#0f172a", secondary="#1e293b", accent="#0ea5e9")
 
-    with ui.column().classes("mx-auto w-full max-w-7xl gap-6 bg-slate-50 p-6 dark:bg-slate-950") as container:
+    # Header must be at page level, not inside container
     with ui.header(elevated=False).classes(
         "items-center justify-between border-b border-slate-200 bg-white/90 px-6 py-4 backdrop-blur dark:border-slate-800 dark:bg-slate-950/90"
     ):
@@ -193,7 +146,7 @@ def dashboard_page(title: str, subtitle: str, current: str) -> Iterator[ui.colum
                 ui.label("Vault Dashboard").classes("text-lg font-bold text-slate-900 dark:text-slate-50")
                 ui.label("NiceGUI hedging cockpit").classes("text-xs text-slate-500 dark:text-slate-400")
         with ui.row().classes("items-center gap-2 max-sm:flex-wrap"):
-                for key, href, label in NAV_ITEMS:
+            for key, href, label in nav_items(workspace_id):
                 active = key == current
                 link_classes = "rounded-lg px-4 py-2 text-sm font-medium no-underline transition " + (
                     "bg-slate-900 text-white dark:bg-slate-100 dark:text-slate-900"
@@ -202,6 +155,7 @@ def dashboard_page(title: str, subtitle: str, current: str) -> Iterator[ui.colum
                 )
                 ui.link(label, href).classes(link_classes)
 
+    with ui.column().classes("w-full gap-6 bg-slate-50 p-6 dark:bg-slate-950") as container:
         with ui.row().classes("w-full items-end justify-between gap-4 max-md:flex-col max-md:items-start"):
             with ui.column().classes("gap-1"):
                 ui.label(title).classes("text-3xl font-bold text-slate-900 dark:text-slate-50")
@@ -209,6 +163,23 @@ def dashboard_page(title: str, subtitle: str, current: str) -> Iterator[ui.colum
         yield container
 
 
+def render_workspace_recovery(title: str = "Workspace not found", message: str | None = None) -> None:
+    resolved_message = (
+        message or "The requested workspace is unavailable. Start a new workspace or return to the welcome page."
+    )
+    with ui.column().classes("mx-auto mt-24 w-full max-w-2xl gap-6 px-6 text-center"):
+        ui.icon("folder_off").classes("mx-auto text-6xl text-slate-400")
+        ui.label(title).classes("text-3xl font-bold text-slate-900 dark:text-slate-50")
+        ui.label(resolved_message).classes("text-base text-slate-500 dark:text-slate-400")
+        with ui.row().classes("mx-auto gap-3"):
+            ui.link("Get started", "/").classes(
+                "rounded-lg bg-slate-900 px-5 py-3 text-sm font-semibold text-white no-underline dark:bg-slate-100 dark:text-slate-900"
+            )
+            ui.link("Go to welcome page", "/").classes(
+                "rounded-lg border border-slate-300 px-5 py-3 text-sm font-semibold text-slate-700 no-underline dark:border-slate-700 dark:text-slate-200"
+            )
+
+
 def recommendation_style(tone: str) -> str:
     return {
         "positive": "border-emerald-200 bg-emerald-50 dark:border-emerald-900/60 dark:bg-emerald-950/30",

app/pages/event_comparison.py

@@ -0,0 +1,623 @@
+from __future__ import annotations
+
+import logging
+
+from fastapi.responses import RedirectResponse
+from nicegui import ui
+
+from app.domain.backtesting_math import asset_quantity_from_workspace_config
+from app.models.workspace import get_workspace_repository
+from app.pages.common import dashboard_page, split_page_panes
+from app.services.event_comparison_ui import EventComparisonPageService
+
+logger = logging.getLogger(__name__)
+
+
+def validate_and_calculate_units(initial_value: float, entry_spot: float) -> tuple[float, str | None]:
+    """Validate inputs and calculate underlying units.
+
+    Returns (units, error_message). If error_message is not None, units is 0.0.
+    """
+    if initial_value <= 0:
+        return 0.0, "Initial portfolio value must be positive."
+    if entry_spot <= 0:
+        return 0.0, "Cannot calculate units: entry spot is invalid. Please select a valid preset."
+    return initial_value / entry_spot, None
+
+
+def _chart_options(dates: tuple[str, ...], series: tuple[dict[str, object], ...]) -> dict:
+    return {
+        "tooltip": {"trigger": "axis"},
+        "legend": {"type": "scroll"},
+        "xAxis": {"type": "category", "data": list(dates)},
+        "yAxis": {"type": "value", "name": "Net value"},
+        "series": [
+            {
+                "name": item["name"],
+                "type": "line",
+                "smooth": True,
+                "data": item["values"],
+            }
+            for item in series
+        ],
+    }
+
+
+@ui.page("/{workspace_id}/event-comparison")
+def workspace_event_comparison_page(workspace_id: str) -> None:
+    repo = get_workspace_repository()
+    if not repo.workspace_exists(workspace_id):
+        return RedirectResponse(url="/", status_code=307)
+    _render_event_comparison_page(workspace_id=workspace_id)
+
+
+def _render_event_comparison_page(workspace_id: str | None = None) -> None:
+    service = EventComparisonPageService()
+    preset_options = service.preset_options("GLD")
+    template_options = service.template_options("GLD")
+    repo = get_workspace_repository()
+    config = repo.load_portfolio_config(workspace_id) if workspace_id else None
+    default_preset_slug = str(preset_options[0]["slug"]) if preset_options else None
+    default_template_slugs = list(preset_options[0]["default_template_slugs"]) if preset_options else []
+    default_entry_spot = 100.0
+    if default_preset_slug is not None:
+        default_preview = service.preview_scenario(
+            preset_slug=default_preset_slug,
+            template_slugs=tuple(default_template_slugs),
+            underlying_units=1.0,
+            loan_amount=0.0,
+            margin_call_ltv=0.75,
+        )
+        default_entry_spot = default_preview.initial_portfolio.entry_spot
+    default_units = (
+        asset_quantity_from_workspace_config(config, entry_spot=default_entry_spot, symbol="GLD")
+        if config is not None and default_entry_spot > 0
+        else 1000.0
+    )
+
+    default_loan = float(config.loan_amount) if config else 68000.0
+    default_margin_call_ltv = float(config.margin_threshold) if config else 0.75
+
+    preset_select_options = {str(option["slug"]): str(option["label"]) for option in preset_options}
+    template_select_options = {str(option["slug"]): str(option["label"]) for option in template_options}
+    preset_lookup = {str(option["slug"]): option for option in preset_options}
+
+    with dashboard_page(
+        "Event Comparison",
+        "Thin BT-003A read-only UI over EventComparisonService with deterministic seeded GLD presets.",
+        "event-comparison",
+        workspace_id=workspace_id,
+    ):
+        left_pane, right_pane = split_page_panes(
+            left_testid="event-comparison-left-pane",
+            right_testid="event-comparison-right-pane",
+        )
+
+        with left_pane:
+            with ui.card().classes(
+                "w-full rounded-2xl border border-slate-200 bg-white shadow-sm dark:border-slate-800 dark:bg-slate-900"
+            ):
+                ui.label("Comparison Form").classes("text-lg font-semibold text-slate-900 dark:text-slate-100")
+                ui.label(
+                    "Preset selection is deterministic and read-only in the sense that runs reuse seeded event windows and existing BT-003 ranking logic."
+                ).classes("text-sm text-slate-500 dark:text-slate-400")
+                if workspace_id:
+                    ui.label("Workspace defaults seed underlying units, loan amount, and margin threshold.").classes(
+                        "text-sm text-slate-500 dark:text-slate-400"
+                    )
+                preset_select = ui.select(
+                    preset_select_options,
+                    value=default_preset_slug,
+                    label="Event preset",
+                ).classes("w-full")
+                template_select = ui.select(
+                    template_select_options,
+                    value=default_template_slugs,
+                    label="Strategy templates",
+                    multiple=True,
+                ).classes("w-full")
+                ui.label(
+                    "Changing the preset resets strategy templates to that preset's default comparison set."
+                ).classes("text-xs text-slate-500 dark:text-slate-400")
+                ui.label("Underlying units will be calculated from initial value ÷ entry spot.").classes(
+                    "text-xs text-slate-500 dark:text-slate-400"
+                )
+                initial_value_input = ui.number(
+                    "Initial portfolio value ($)", value=default_units * default_entry_spot, min=0.01, step=1000
+                ).classes("w-full")
+                loan_input = ui.number("Loan amount", value=default_loan, min=0, step=1000).classes("w-full")
+                ltv_input = ui.number(
+                    "Margin call LTV",
+                    value=default_margin_call_ltv,
+                    min=0.01,
+                    max=0.99,
+                    step=0.01,
+                ).classes("w-full")
+                metadata_label = ui.label("").classes("text-sm text-slate-500 dark:text-slate-400")
+                scenario_label = ui.label("").classes("text-sm text-slate-500 dark:text-slate-400")
+                validation_label = ui.label("").classes("text-sm text-rose-600 dark:text-rose-300")
+                run_button = ui.button("Run comparison").props("color=primary")
+
+            selected_summary = ui.card().classes(
+                "w-full rounded-2xl border border-slate-200 bg-white shadow-sm dark:border-slate-800 dark:bg-slate-900"
+            )
+
+        with right_pane:
+            result_panel = ui.column().classes("w-full gap-6")
+
+        syncing_controls = {"value": False}
+
+        def selected_template_slugs() -> tuple[str, ...]:
+            raw_value = template_select.value or []
+            if isinstance(raw_value, str):
+                return (raw_value,) if raw_value else ()
+            return tuple(str(item) for item in raw_value if item)
+
+        def render_selected_summary(entry_spot: float | None = None, entry_spot_error: str | None = None) -> None:
+            selected_summary.clear()
+            with selected_summary:
+                ui.label("Scenario Summary").classes("text-lg font-semibold text-slate-900 dark:text-slate-100")
+                # Calculate underlying units with validation
+                initial_value = float(initial_value_input.value or 0.0)
+                computed_units, units_error = (
+                    validate_and_calculate_units(initial_value, entry_spot)
+                    if entry_spot is not None
+                    else (0.0, "Entry spot unavailable.")
+                )
+                with ui.grid(columns=1).classes("w-full gap-4 sm:grid-cols-2 lg:grid-cols-1 xl:grid-cols-2"):
+                    cards = [
+                        (
+                            "Initial portfolio value",
+                            f"${float(initial_value_input.value or 0.0):,.0f}",
+                        ),
+                        ("Templates", str(len(selected_template_slugs()))),
+                        ("Underlying units", f"{computed_units:,.0f}" if computed_units > 0 else "—"),
+                        ("Loan amount", f"${float(loan_input.value or 0.0):,.0f}"),
+                        ("Margin call LTV", f"{float(ltv_input.value or 0.0):.1%}"),
+                        ("Entry spot", f"${entry_spot:,.2f}" if entry_spot is not None else "Unavailable"),
+                    ]
+                    for label, value in cards:
+                        with ui.card().classes(
+                            "rounded-xl border border-slate-200 bg-slate-50 p-4 shadow-none dark:border-slate-800 dark:bg-slate-950"
+                        ):
+                            ui.label(label).classes("text-sm text-slate-500 dark:text-slate-400")
+                            ui.label(value).classes("text-xl font-bold text-slate-900 dark:text-slate-100")
+                # Show validation errors (units_error takes priority, then entry_spot_error)
+                display_error = units_error or entry_spot_error
+                if display_error:
+                    tone_class = (
+                        "text-rose-600 dark:text-rose-300"
+                        if "must be positive" in display_error
+                        else "text-amber-700 dark:text-amber-300"
+                    )
+                    ui.label(display_error).classes(f"text-sm {tone_class}")
+
+        def render_result_state(title: str, message: str, *, tone: str = "info") -> None:
+            tone_classes = {
+                "info": "border-sky-200 bg-sky-50 dark:border-sky-900/60 dark:bg-sky-950/30",
+                "warning": "border-amber-200 bg-amber-50 dark:border-amber-900/60 dark:bg-amber-950/30",
+                "error": "border-rose-200 bg-rose-50 dark:border-rose-900/60 dark:bg-rose-950/30",
+            }
+            text_classes = {
+                "info": "text-sky-800 dark:text-sky-200",
+                "warning": "text-amber-800 dark:text-amber-200",
+                "error": "text-rose-800 dark:text-rose-200",
+            }
+            result_panel.clear()
+            with result_panel:
+                with ui.card().classes(
+                    f"w-full rounded-2xl border shadow-sm {tone_classes.get(tone, tone_classes['info'])}"
+                ):
+                    ui.label(title).classes("text-lg font-semibold text-slate-900 dark:text-slate-100")
+                    ui.label(message).classes(f"text-sm {text_classes.get(tone, text_classes['info'])}")
+
+        def mark_results_stale() -> None:
+            render_result_state(
+                "Results out of date",
+                "Inputs changed. Run comparison again to refresh rankings and portfolio paths for the current scenario.",
+                tone="info",
+            )
+
+        def refresh_preview(*, reset_templates: bool = False, reseed_units: bool = False) -> str | None:
+            option = preset_lookup.get(str(preset_select.value or ""))
+            if option is None:
+                metadata_label.set_text("")
+                scenario_label.set_text("")
+                render_selected_summary(entry_spot=None)
+                return None
+
+            if reset_templates:
+                syncing_controls["value"] = True
+                try:
+                    template_select.value = list(service.default_template_selection(str(option["slug"])))
+                finally:
+                    syncing_controls["value"] = False
+
+            template_slugs = selected_template_slugs()
+
+            try:
+                # Get initial portfolio value from UI and derive entry spot
+                preview_initial_value = float(initial_value_input.value or 0.0)
+                preview_entry_spot = service.derive_entry_spot(
+                    preset_slug=str(option["slug"]),
+                    template_slugs=template_slugs,
+                )
+                # Validate and calculate underlying units
+                preview_units, units_error = validate_and_calculate_units(preview_initial_value, preview_entry_spot)
+                if units_error:
+                    metadata_label.set_text(f"Preset: {option['label']} — {option['description']}")
+                    scenario_label.set_text(units_error)
+                    render_selected_summary(entry_spot=preview_entry_spot, entry_spot_error=units_error)
+                    return units_error
+
+                if workspace_id and config is not None and reseed_units:
+                    # Recalculate from workspace config
+                    workspace_units = asset_quantity_from_workspace_config(
+                        config,
+                        entry_spot=preview_entry_spot,
+                        symbol="GLD",
+                    )
+                    syncing_controls["value"] = True
+                    try:
+                        initial_value_input.value = workspace_units * preview_entry_spot
+                        preview_units = workspace_units
+                        preview_initial_value = workspace_units * preview_entry_spot
+                    finally:
+                        syncing_controls["value"] = False
+                scenario = service.preview_scenario(
+                    preset_slug=str(option["slug"]),
+                    template_slugs=template_slugs,
+                    underlying_units=preview_units,
+                    loan_amount=float(loan_input.value or 0.0),
+                    margin_call_ltv=float(ltv_input.value or 0.0),
+                )
+            except (ValueError, KeyError) as exc:
+                metadata_label.set_text(f"Preset: {option['label']} — {option['description']}")
+                scenario_label.set_text(str(exc))
+                render_selected_summary(entry_spot=None, entry_spot_error=str(exc))
+                return str(exc)
+            except Exception:
+                logger.exception(
+                    "Event comparison preview failed for workspace=%s preset=%s templates=%s initial_value=%s loan=%s margin_call_ltv=%s",
+                    workspace_id,
+                    preset_select.value,
+                    selected_template_slugs(),
+                    initial_value_input.value,
+                    loan_input.value,
+                    ltv_input.value,
+                )
+                message = "Event comparison preview failed. Please verify the seeded inputs and try again."
+                metadata_label.set_text(f"Preset: {option['label']} — {option['description']}")
+                scenario_label.set_text(message)
+                render_selected_summary(entry_spot=None, entry_spot_error=message)
+                return message
+            preset = service.event_preset_service.get_preset(str(option["slug"]))
+            metadata_label.set_text(f"Preset: {option['label']} — {option['description']}")
+            scenario_label.set_text(
+                "Scenario preview: "
+                f"{scenario.start_date.isoformat()} → {scenario.end_date.isoformat()}"
+                + (
+                    f" · Anchor date: {preset.anchor_date.isoformat()}"
+                    if preset.anchor_date is not None
+                    else " · Anchor date: none"
+                )
+                + f" · Entry spot: ${scenario.initial_portfolio.entry_spot:,.2f}"
+            )
+            render_selected_summary(entry_spot=float(scenario.initial_portfolio.entry_spot))
+            return None
+
+        def render_report() -> None:
+            validation_label.set_text("")
+            result_panel.clear()
+            template_slugs = selected_template_slugs()
+            try:
+                # Get initial portfolio value and calculate underlying units with validation
+                initial_value = float(initial_value_input.value or 0.0)
+                # Get entry spot from preview
+                option = preset_lookup.get(str(preset_select.value or ""))
+                if option is None:
+                    validation_label.set_text("Select a preset to run comparison.")
+                    return
+                entry_spot = service.derive_entry_spot(
+                    preset_slug=str(option["slug"]),
+                    template_slugs=template_slugs,
+                )
+                # Validate and calculate underlying units
+                underlying_units, units_error = validate_and_calculate_units(initial_value, entry_spot)
+                if units_error:
+                    validation_label.set_text(units_error)
+                    render_result_state("Input validation failed", units_error, tone="warning")
+                    return
+
+                report = service.run_read_only_comparison(
+                    preset_slug=str(preset_select.value or ""),
+                    template_slugs=template_slugs,
+                    underlying_units=underlying_units,
+                    loan_amount=float(loan_input.value or 0.0),
+                    margin_call_ltv=float(ltv_input.value or 0.0),
+                )
+            except (ValueError, KeyError) as exc:
+                validation_label.set_text(str(exc))
+                render_result_state("Scenario validation failed", str(exc), tone="warning")
+                return
+            except Exception:
+                message = "Event comparison failed. Please verify the seeded inputs and try again."
+                logger.exception(
+                    "Event comparison page run failed for workspace=%s preset=%s templates=%s initial_value=%s loan=%s margin_call_ltv=%s",
+                    workspace_id,
+                    preset_select.value,
+                    selected_template_slugs(),
+                    initial_value_input.value,
+                    loan_input.value,
+                    ltv_input.value,
+                )
+                validation_label.set_text(message)
+                render_result_state("Event comparison failed", message, tone="error")
+                return
+
+            preset = report.event_preset
+            scenario = report.scenario
+            metadata_label.set_text(
+                f"Preset: {preset.display_name} ({preset.event_type}) · Tags: {', '.join(preset.tags) or 'none'}"
+            )
+            scenario_label.set_text(
+                "Scenario dates used: "
+                f"{scenario.start_date.isoformat()} → {scenario.end_date.isoformat()} · "
+                f"Entry spot: ${scenario.initial_portfolio.entry_spot:,.2f}"
+            )
+            render_selected_summary(entry_spot=float(scenario.initial_portfolio.entry_spot))
+            chart_model = service.chart_model(report)
+            drilldown_options = service.drilldown_options(report)
+            initial_drilldown_slug = next(iter(drilldown_options), None)
+
+            with result_panel:
+                with ui.card().classes(
+                    "w-full rounded-2xl border border-slate-200 bg-white shadow-sm dark:border-slate-800 dark:bg-slate-900"
+                ):
+                    ui.label("Scenario Results").classes("text-lg font-semibold text-slate-900 dark:text-slate-100")
+                    with ui.grid(columns=4).classes("w-full gap-4 max-lg:grid-cols-2 max-sm:grid-cols-1"):
+                        cards = [
+                            ("Symbol", scenario.symbol),
+                            ("Event window", f"{preset.window_start.isoformat()} → {preset.window_end.isoformat()}"),
+                            (
+                                "Anchor date",
+                                preset.anchor_date.isoformat() if preset.anchor_date is not None else "None",
+                            ),
+                            (
+                                "Scenario dates used",
+                                f"{scenario.start_date.isoformat()} → {scenario.end_date.isoformat()}",
+                            ),
+                            ("Initial value", f"${float(initial_value_input.value or 0.0):,.0f}"),
+                            ("Underlying units", f"{scenario.initial_portfolio.underlying_units:,.0f}"),
+                            ("Loan amount", f"${scenario.initial_portfolio.loan_amount:,.0f}"),
+                            ("Margin call LTV", f"{scenario.initial_portfolio.margin_call_ltv:.1%}"),
+                            ("Templates compared", str(len(report.rankings))),
+                        ]
+                        for label, value in cards:
+                            with ui.card().classes(
+                                "rounded-xl border border-slate-200 bg-slate-50 p-4 shadow-none dark:border-slate-800 dark:bg-slate-950"
+                            ):
+                                ui.label(label).classes("text-sm text-slate-500 dark:text-slate-400")
+                                ui.label(value).classes("text-xl font-bold text-slate-900 dark:text-slate-100")
+
+                with ui.card().classes(
+                    "w-full rounded-2xl border border-slate-200 bg-white shadow-sm dark:border-slate-800 dark:bg-slate-900"
+                ):
+                    ui.label("Ranked Results").classes("text-lg font-semibold text-slate-900 dark:text-slate-100")
+                    ui.table(
+                        columns=[
+                            {"name": "rank", "label": "Rank", "field": "rank", "align": "right"},
+                            {"name": "template_name", "label": "Template", "field": "template_name", "align": "left"},
+                            {
+                                "name": "survived_margin_call",
+                                "label": "Survived margin call",
+                                "field": "survived_margin_call",
+                                "align": "center",
+                            },
+                            {
+                                "name": "margin_call_days_hedged",
+                                "label": "Hedged margin call days",
+                                "field": "margin_call_days_hedged",
+                                "align": "right",
+                            },
+                            {
+                                "name": "max_ltv_hedged",
+                                "label": "Max hedged LTV",
+                                "field": "max_ltv_hedged",
+                                "align": "right",
+                            },
+                            {"name": "hedge_cost", "label": "Hedge cost", "field": "hedge_cost", "align": "right"},
+                            {
+                                "name": "final_equity",
+                                "label": "Final equity",
+                                "field": "final_equity",
+                                "align": "right",
+                            },
+                        ],
+                        rows=[
+                            {
+                                "rank": item.rank,
+                                "template_name": item.template_name,
+                                "survived_margin_call": "Yes" if item.survived_margin_call else "No",
+                                "margin_call_days_hedged": item.margin_call_days_hedged,
+                                "max_ltv_hedged": f"{item.max_ltv_hedged:.1%}",
+                                "hedge_cost": f"${item.hedge_cost:,.0f}",
+                                "final_equity": f"${item.final_equity:,.0f}",
+                            }
+                            for item in report.rankings
+                        ],
+                        row_key="rank",
+                    ).classes("w-full")
+
+                with ui.card().classes(
+                    "w-full rounded-2xl border border-slate-200 bg-white shadow-sm dark:border-slate-800 dark:bg-slate-900"
+                ):
+                    ui.label("Strategy Drilldown").classes("text-lg font-semibold text-slate-900 dark:text-slate-100")
+                    ui.label(
+                        "Select a ranked strategy to inspect margin-call pressure, payoff realization, and the full seeded daily path."
+                    ).classes("text-sm text-slate-500 dark:text-slate-400")
+                    drilldown_select = ui.select(
+                        drilldown_options,
+                        value=initial_drilldown_slug,
+                        label="Strategy drilldown",
+                    ).classes("w-full")
+                    drilldown_container = ui.column().classes("w-full gap-4")
+
+                    def render_drilldown() -> None:
+                        drilldown_container.clear()
+                        if drilldown_select.value is None:
+                            return
+                        drilldown = service.drilldown_model(report, template_slug=str(drilldown_select.value))
+                        breach_dates = ", ".join(drilldown.breach_dates) if drilldown.breach_dates else "None"
+                        worst_ltv_point = (
+                            f"{drilldown.worst_ltv_date} · {drilldown.worst_ltv_hedged:.1%}"
+                            if drilldown.worst_ltv_date is not None
+                            else "Unavailable"
+                        )
+                        with drilldown_container:
+                            ui.label(f"Selected strategy: {drilldown.template_name}").classes(
+                                "text-lg font-semibold text-slate-900 dark:text-slate-100"
+                            )
+                            ui.label(
+                                f"Rank #{drilldown.rank} · {'Survived margin call' if drilldown.survived_margin_call else 'Breached margin threshold'}"
+                            ).classes("text-sm text-slate-500 dark:text-slate-400")
+                            with ui.grid(columns=4).classes("w-full gap-4 max-lg:grid-cols-2 max-sm:grid-cols-1"):
+                                cards = [
+                                    ("Margin-call days", str(drilldown.margin_call_days_hedged)),
+                                    ("Payoff realized", f"${drilldown.total_option_payoff_realized:,.0f}"),
+                                    ("Hedge cost", f"${drilldown.hedge_cost:,.0f}"),
+                                    ("Final equity", f"${drilldown.final_equity:,.0f}"),
+                                ]
+                                for label, value in cards:
+                                    with ui.card().classes(
+                                        "rounded-xl border border-slate-200 bg-slate-50 p-4 shadow-none dark:border-slate-800 dark:bg-slate-950"
+                                    ):
+                                        ui.label(label).classes("text-sm text-slate-500 dark:text-slate-400")
+                                        ui.label(value).classes("text-xl font-bold text-slate-900 dark:text-slate-100")
+                            with ui.grid(columns=2).classes("w-full gap-4 max-md:grid-cols-1"):
+                                with ui.card().classes(
+                                    "rounded-xl border border-slate-200 bg-slate-50 p-4 shadow-none dark:border-slate-800 dark:bg-slate-950"
+                                ):
+                                    ui.label("Worst LTV point").classes("text-sm text-slate-500 dark:text-slate-400")
+                                    ui.label(worst_ltv_point).classes(
+                                        "text-xl font-bold text-slate-900 dark:text-slate-100"
+                                    )
+                                with ui.card().classes(
+                                    "rounded-xl border border-amber-200 bg-amber-50 p-4 shadow-none dark:border-amber-900/60 dark:bg-amber-950/30"
+                                ):
+                                    ui.label("Margin threshold breach dates").classes(
+                                        "text-sm text-amber-700 dark:text-amber-300"
+                                    )
+                                    ui.label(breach_dates).classes(
+                                        "text-base font-semibold text-amber-800 dark:text-amber-200"
+                                    )
+                            with ui.card().classes(
+                                "w-full rounded-xl border border-slate-200 bg-slate-50 p-4 shadow-none dark:border-slate-800 dark:bg-slate-950"
+                            ):
+                                ui.label("Daily path details").classes(
+                                    "text-base font-semibold text-slate-900 dark:text-slate-100"
+                                )
+                                ui.table(
+                                    columns=[
+                                        {"name": "date", "label": "Date", "field": "date", "align": "left"},
+                                        {
+                                            "name": "spot_close",
+                                            "label": "Spot",
+                                            "field": "spot_close",
+                                            "align": "right",
+                                        },
+                                        {
+                                            "name": "net_portfolio_value",
+                                            "label": "Net hedged",
+                                            "field": "net_portfolio_value",
+                                            "align": "right",
+                                        },
+                                        {
+                                            "name": "option_market_value",
+                                            "label": "Option value",
+                                            "field": "option_market_value",
+                                            "align": "right",
+                                        },
+                                        {
+                                            "name": "realized_option_cashflow",
+                                            "label": "Payoff realized",
+                                            "field": "realized_option_cashflow",
+                                            "align": "right",
+                                        },
+                                        {
+                                            "name": "ltv_hedged",
+                                            "label": "Hedged LTV",
+                                            "field": "ltv_hedged",
+                                            "align": "right",
+                                        },
+                                        {
+                                            "name": "margin_call_hedged",
+                                            "label": "Breach",
+                                            "field": "margin_call_hedged",
+                                            "align": "center",
+                                        },
+                                    ],
+                                    rows=[
+                                        {
+                                            "date": row.date,
+                                            "spot_close": f"${row.spot_close:,.2f}",
+                                            "net_portfolio_value": f"${row.net_portfolio_value:,.0f}",
+                                            "option_market_value": f"${row.option_market_value:,.0f}",
+                                            "realized_option_cashflow": f"${row.realized_option_cashflow:,.0f}",
+                                            "ltv_hedged": f"{row.ltv_hedged:.1%}",
+                                            "margin_call_hedged": "Yes" if row.margin_call_hedged else "No",
+                                        }
+                                        for row in drilldown.rows
+                                    ],
+                                    row_key="date",
+                                ).classes("w-full")
+
+                    drilldown_select.on_value_change(lambda _: render_drilldown())
+                    render_drilldown()
+
+                with ui.card().classes(
+                    "w-full rounded-2xl border border-slate-200 bg-white shadow-sm dark:border-slate-800 dark:bg-slate-900"
+                ):
+                    ui.label("Portfolio Value Paths").classes(
+                        "text-lg font-semibold text-slate-900 dark:text-slate-100"
+                    )
+                    ui.label(
+                        "Baseline series shows the unhedged collateral value path for the same seeded event window."
+                    ).classes("text-sm text-slate-500 dark:text-slate-400")
+                    ui.echart(
+                        _chart_options(
+                            chart_model.dates,
+                            tuple({"name": item.name, "values": list(item.values)} for item in chart_model.series),
+                        )
+                    ).classes("h-96 w-full")
+
+        def on_preset_change() -> None:
+            if syncing_controls["value"]:
+                return
+            validation_label.set_text("")
+            preview_error = refresh_preview(reset_templates=True, reseed_units=False)
+            if preview_error:
+                validation_label.set_text(preview_error)
+                render_result_state("Scenario validation failed", preview_error, tone="warning")
+            else:
+                mark_results_stale()
+
+        def on_preview_input_change() -> None:
+            if syncing_controls["value"]:
+                return
+            validation_label.set_text("")
+            preview_error = refresh_preview()
+            if preview_error:
+                validation_label.set_text(preview_error)
+                render_result_state("Scenario validation failed", preview_error, tone="warning")
+            else:
+                mark_results_stale()
+
+        preset_select.on_value_change(lambda _: on_preset_change())
+        template_select.on_value_change(lambda _: on_preview_input_change())
+        initial_value_input.on_value_change(lambda _: on_preview_input_change())
+        loan_input.on_value_change(lambda _: on_preview_input_change())
+        ltv_input.on_value_change(lambda _: on_preview_input_change())
+        run_button.on_click(lambda: render_report())
+        refresh_preview(reset_templates=False, reseed_units=False)
+        render_report()

app/pages/hedge.py

@@ -1,24 +1,35 @@
 from __future__ import annotations
 
+import logging
+
+from fastapi.responses import RedirectResponse
 from nicegui import ui
 
+from app.domain.portfolio_math import resolve_portfolio_spot_from_quote
+from app.models.workspace import get_workspace_repository
 from app.pages.common import (
     dashboard_page,
     demo_spot_price,
-    strategy_catalog,
+    portfolio_snapshot,
+    split_page_panes,
     strategy_metrics,
 )
+from app.services.runtime import get_data_service
+from app.services.strategy_templates import StrategyTemplateService
+
+logger = logging.getLogger(__name__)
 
 
 def _cost_benefit_options(metrics: dict) -> dict:
     return {
         "tooltip": {"trigger": "axis"},
+        "grid": {"left": 64, "right": 24, "top": 24, "bottom": 48},
         "xAxis": {
             "type": "category",
             "data": [f"${point['price']:.0f}" for point in metrics["scenario_series"]],
-            "name": "GLD spot",
+            "name": "Collateral spot",
         },
-        "yAxis": {"type": "value", "name": "Net benefit / oz"},
+        "yAxis": {"type": "value", "name": "Net hedge benefit / oz"},
         "series": [
             {
                 "type": "bar",
@@ -26,6 +37,11 @@ def _cost_benefit_options(metrics: dict) -> dict:
                 "itemStyle": {
                     "color": "#0ea5e9",
                 },
+                "markLine": {
+                    "symbol": "none",
+                    "lineStyle": {"color": "#94a3b8", "type": "dashed"},
+                    "data": [{"yAxis": 0}],
+                },
             }
         ],
     }
@@ -33,98 +49,232 @@ def _cost_benefit_options(metrics: dict) -> dict:
 
 def _waterfall_options(metrics: dict) -> dict:
     steps = metrics["waterfall_steps"]
-    running = 0.0
+    values: list[dict[str, object]] = []
-    base: list[float] = []
+    for label, amount in steps:
-    values: list[float] = []
+        color = "#0ea5e9" if label == "Net equity" else ("#22c55e" if amount >= 0 else "#ef4444")
-    for index, (_, amount) in enumerate(steps):
+        values.append({"value": amount, "itemStyle": {"color": color}})
-        if index == 0:
+
-            base.append(0)
-            values.append(amount)
-            running = amount
-        elif index == len(steps) - 1:
-            base.append(0)
-            values.append(amount)
-        else:
-            base.append(running)
-            values.append(amount)
-            running += amount
     return {
         "tooltip": {"trigger": "axis", "axisPointer": {"type": "shadow"}},
+        "grid": {"left": 80, "right": 24, "top": 24, "bottom": 48},
         "xAxis": {"type": "category", "data": [label for label, _ in steps]},
         "yAxis": {"type": "value", "name": "USD"},
         "series": [
             {
                 "type": "bar",
-                "stack": "total",
-                "data": base,
-                "itemStyle": {"color": "rgba(0,0,0,0)"},
-            },
-            {
-                "type": "bar",
-                "stack": "total",
                 "data": values,
-                "itemStyle": {
+                "label": {"show": True, "position": "top", "formatter": "{c}"},
-                    "color": "#22c55e",
-                },
             },
         ],
     }
 
 
-@ui.page("/hedge")
+@ui.page("/{workspace_id}/hedge")
-def hedge_page() -> None:
+async def workspace_hedge_page(workspace_id: str) -> None:
-    strategies = strategy_catalog()
+    repo = get_workspace_repository()
-    strategy_map = {strategy["label"]: strategy["name"] for strategy in strategies}
+    if not repo.workspace_exists(workspace_id):
-    selected = {"strategy": strategies[0]["name"], "scenario_pct": 0}
+        return RedirectResponse(url="/", status_code=307)
+    await _render_hedge_page(workspace_id=workspace_id)
+
+
+async def _resolve_hedge_spot(workspace_id: str | None = None) -> tuple[dict[str, float], str, str]:
+    """Resolve hedge page spot price using the same quote-unit seam as overview."""
+    repo = get_workspace_repository()
+    config = repo.load_portfolio_config(workspace_id) if workspace_id else None
+    if config is None:
+        return {"spot_price": demo_spot_price()}, "demo", ""
+
+    try:
+        data_service = get_data_service()
+        underlying = config.underlying or "GLD"
+        quote = await data_service.get_quote(underlying)
+        spot, source, updated_at = resolve_portfolio_spot_from_quote(config, quote, fallback_symbol=underlying)
+        portfolio = portfolio_snapshot(config, runtime_spot_price=spot)
+        return portfolio, source, updated_at
+    except Exception as exc:
+        logger.warning("Falling back to configured hedge spot for workspace %s: %s", workspace_id, exc)
+        portfolio = portfolio_snapshot(config)
+        return portfolio, "configured_entry_price", ""
+
+
+async def _render_hedge_page(workspace_id: str | None = None) -> None:
+    portfolio, quote_source, quote_updated_at = await _resolve_hedge_spot(workspace_id)
+    template_service = StrategyTemplateService()
+    strategies_state = {"items": template_service.catalog_items()}
+
+    def strategy_map() -> dict[str, str]:
+        return {strategy["label"]: strategy["template_slug"] for strategy in strategies_state["items"]}
+
+    selected = {
+        "strategy": strategies_state["items"][0]["template_slug"],
+        "label": strategies_state["items"][0]["label"],
+        "scenario_pct": 0,
+    }
+
+    display_mode = portfolio.get("display_mode", "XAU")
+
+    if display_mode == "GLD":
+        spot_unit = "/share"
+        spot_desc = "GLD share price"
+    else:
+        spot_unit = "/oz"
+        spot_desc = "converted collateral spot"
+
+    if quote_source == "configured_entry_price":
+        spot_label = f"Current spot reference: ${portfolio['spot_price']:,.2f}{spot_unit} (configured entry price)"
+    else:
+        spot_label = (
+            f"Current spot reference: ${portfolio['spot_price']:,.2f}{spot_unit} ({spot_desc} via {quote_source})"
+        )
+    updated_label = f"Quote timestamp: {quote_updated_at}" if quote_updated_at else "Quote timestamp: unavailable"
+
+    # Get underlying for display
+    underlying = "GLD"
+    if workspace_id:
+        try:
+            repo = get_workspace_repository()
+            config = repo.load_portfolio_config(workspace_id)
+            underlying = config.underlying or "GLD"
+        except Exception:
+            pass
 
     with dashboard_page(
         "Hedge Analysis",
-        "Compare hedge structures across scenarios, visualize cost-benefit tradeoffs, and inspect net equity impacts.",
+        f"Compare hedge structures across scenarios, visualize cost-benefit tradeoffs, and inspect net equity impacts for {underlying}.",
         "hedge",
+        workspace_id=workspace_id,
     ):
-        with ui.row().classes("w-full gap-6 max-lg:flex-col"):
+        with ui.row().classes("w-full items-center justify-between gap-4 max-md:flex-col max-md:items-start"):
+            ui.label(f"Active underlying: {underlying}").classes("text-sm text-slate-500 dark:text-slate-400")
+
+        left_pane, right_pane = split_page_panes(
+            left_testid="hedge-left-pane",
+            right_testid="hedge-right-pane",
+        )
+
+        with left_pane:
             with ui.card().classes(
                 "w-full rounded-2xl border border-slate-200 bg-white shadow-sm dark:border-slate-800 dark:bg-slate-900"
             ):
                 ui.label("Strategy Controls").classes("text-lg font-semibold text-slate-900 dark:text-slate-100")
-                selector = ui.select(strategy_map, value=selected["strategy"], label="Strategy selector").classes(
+                selector = ui.select(
-                    "w-full"
+                    list(strategy_map().keys()), value=selected["label"], label="Strategy selector"
-                )
+                ).classes("w-full")
                 slider_value = ui.label("Scenario move: +0%").classes("text-sm text-slate-500 dark:text-slate-400")
                 slider = ui.slider(min=-25, max=25, value=0, step=5).classes("w-full")
-                ui.label(f"Current spot reference: ${demo_spot_price():,.2f}").classes(
+                ui.label(spot_label).classes("text-sm text-slate-500 dark:text-slate-400")
-                    "text-sm text-slate-500 dark:text-slate-400"
+                ui.label(updated_label).classes("text-xs text-slate-500 dark:text-slate-400")
+                if workspace_id:
+                    ui.label(f"Workspace route: /{workspace_id}/hedge").classes(
+                        "text-xs text-slate-500 dark:text-slate-400"
                     )
+                else:
+                    ui.label(f"Demo spot reference: ${demo_spot_price():,.2f}").classes(
+                        "text-xs text-slate-500 dark:text-slate-400"
+                    )
+
+            with (
+                ui.card()
+                .classes(
+                    "w-full rounded-2xl border border-slate-200 bg-white shadow-sm dark:border-slate-800 dark:bg-slate-900"
+                )
+                .props("data-testid=strategy-builder-card")
+            ):
+                ui.label("Strategy Builder").classes("text-lg font-semibold text-slate-900 dark:text-slate-100")
+                ui.label(
+                    "Save a custom protective put or equal-weight two-leg ladder for reuse across hedge, backtests, and event comparison."
+                ).classes("text-sm text-slate-500 dark:text-slate-400")
+                builder_type_options = {"Protective put": "protective_put", "Two-leg ladder": "laddered_put"}
+                builder_name = ui.input("Template name", placeholder="Crash Guard 97").classes("w-full")
+                builder_type = ui.select(
+                    list(builder_type_options.keys()),
+                    value="Protective put",
+                    label="Strategy type",
+                ).classes("w-full")
+                builder_expiry_days = ui.number("Expiration days", value=365, min=30, step=30).classes("w-full")
+                builder_primary_strike = ui.number(
+                    "Primary strike (% of spot)",
+                    value=100,
+                    min=1,
+                    max=150,
+                    step=1,
+                ).classes("w-full")
+                builder_secondary_strike = ui.number(
+                    "Secondary strike (% of spot)",
+                    value=95,
+                    min=1,
+                    max=150,
+                    step=1,
+                ).classes("w-full")
+                ui.label("Two-leg ladders currently save with equal 50/50 weights.").classes(
+                    "text-xs text-slate-500 dark:text-slate-400"
+                )
+                builder_status = ui.label("").classes("text-sm text-slate-600 dark:text-slate-300")
+                save_template_button = ui.button("Save template").props("color=primary outline")
 
             summary = ui.card().classes(
                 "w-full rounded-2xl border border-slate-200 bg-white shadow-sm dark:border-slate-800 dark:bg-slate-900"
             )
 
-        charts_row = ui.row().classes("w-full gap-6 max-lg:flex-col")
+        with right_pane:
-        with charts_row:
+            scenario_results = ui.card().classes(
-            cost_chart = ui.echart(
+                "w-full rounded-2xl border border-slate-200 bg-white shadow-sm dark:border-slate-800 dark:bg-slate-900"
-                _cost_benefit_options(strategy_metrics(selected["strategy"], selected["scenario_pct"]))
+            )
-            ).classes(
+            with ui.row().classes("w-full gap-6 max-xl:flex-col"):
+                initial_metrics = strategy_metrics(selected["strategy"], selected["scenario_pct"], portfolio=portfolio)
+                cost_chart = ui.echart(_cost_benefit_options(initial_metrics)).classes(
                     "h-96 w-full rounded-2xl border border-slate-200 bg-white p-4 shadow-sm dark:border-slate-800 dark:bg-slate-900"
                 )
-            waterfall_chart = ui.echart(
+                waterfall_chart = ui.echart(_waterfall_options(initial_metrics)).classes(
-                _waterfall_options(strategy_metrics(selected["strategy"], selected["scenario_pct"]))
-            ).classes(
                     "h-96 w-full rounded-2xl border border-slate-200 bg-white p-4 shadow-sm dark:border-slate-800 dark:bg-slate-900"
                 )
 
+        syncing_controls = {"value": False}
+
+        def refresh_available_strategies() -> None:
+            strategies_state["items"] = template_service.catalog_items()
+            options = strategy_map()
+            syncing_controls["value"] = True
+            try:
+                selector.options = list(options.keys())
+                if selected["label"] not in options:
+                    first_label = next(iter(options))
+                    selected["label"] = first_label
+                    selected["strategy"] = options[first_label]
+                    selector.value = first_label
+                selector.update()
+            finally:
+                syncing_controls["value"] = False
+
         def render_summary() -> None:
-            metrics = strategy_metrics(selected["strategy"], selected["scenario_pct"])
+            metrics = strategy_metrics(selected["strategy"], selected["scenario_pct"], portfolio=portfolio)
             strategy = metrics["strategy"]
+
+            # Display mode-aware labels
+            if display_mode == "GLD":
+                weight_unit = "shares"
+                price_unit = "/share"
+                hedge_cost_unit = "/share"
+            else:
+                weight_unit = "oz"
+                price_unit = "/oz"
+                hedge_cost_unit = "/oz"
+
             summary.clear()
             with summary:
                 ui.label("Scenario Summary").classes("text-lg font-semibold text-slate-900 dark:text-slate-100")
-                with ui.grid(columns=2).classes("w-full gap-4 max-sm:grid-cols-1"):
+                ui.label(f"Selected template: {strategy['label']}").classes(
+                    "text-sm text-slate-500 dark:text-slate-400"
+                )
+                ui.label(strategy["description"]).classes("text-sm text-slate-600 dark:text-slate-300")
+                with ui.grid(columns=1).classes("w-full gap-4 sm:grid-cols-2 lg:grid-cols-1 xl:grid-cols-2"):
                     cards = [
-                        ("Scenario spot", f"${metrics['scenario_price']:,.2f}"),
+                        ("Start value", f"${portfolio['gold_value']:,.0f}"),
-                        ("Hedge cost", f"${strategy['estimated_cost']:,.2f}/oz"),
+                        ("Start price", f"${portfolio['spot_price']:,.2f}{price_unit}"),
-                        ("Unhedged equity", f"${metrics['unhedged_equity']:,.0f}"),
+                        ("Weight", f"{portfolio['gold_units']:,.0f} {weight_unit}"),
-                        ("Hedged equity", f"${metrics['hedged_equity']:,.0f}"),
+                        ("Loan amount", f"${portfolio['loan_amount']:,.0f}"),
+                        ("Margin call LTV", f"{portfolio['margin_call_ltv']:.1%}"),
+                        ("Monthly hedge budget", f"${portfolio['hedge_budget']:,.0f}"),
                     ]
                     for label, value in cards:
                         with ui.card().classes(
@@ -132,15 +282,38 @@ def hedge_page() -> None:
                         ):
                             ui.label(label).classes("text-sm text-slate-500 dark:text-slate-400")
                             ui.label(value).classes("text-2xl font-bold text-slate-900 dark:text-slate-100")
-                ui.label(strategy["description"]).classes("text-sm text-slate-600 dark:text-slate-300")
 
-            cost_chart.options = _cost_benefit_options(metrics)
+            scenario_results.clear()
+            with scenario_results:
+                ui.label("Scenario Results").classes("text-lg font-semibold text-slate-900 dark:text-slate-100")
+                with ui.grid(columns=2).classes("w-full gap-4 max-md:grid-cols-1"):
+                    result_cards = [
+                        ("Scenario spot", f"${metrics['scenario_price']:,.2f}{price_unit}"),
+                        ("Hedge cost", f"${float(strategy.get('estimated_cost', 0.0)):,.2f}{hedge_cost_unit}"),
+                        ("Unhedged equity", f"${metrics['unhedged_equity']:,.0f}"),
+                        ("Hedged equity", f"${metrics['hedged_equity']:,.0f}"),
+                        ("Net hedge benefit", f"${metrics['hedged_equity'] - metrics['unhedged_equity']:,.0f}"),
+                        ("Scenario move", f"{selected['scenario_pct']:+d}%"),
+                    ]
+                    for label, value in result_cards:
+                        with ui.card().classes(
+                            "rounded-xl border border-slate-200 bg-slate-50 p-4 shadow-none dark:border-slate-800 dark:bg-slate-950"
+                        ):
+                            ui.label(label).classes("text-sm text-slate-500 dark:text-slate-400")
+                            ui.label(value).classes("text-2xl font-bold text-slate-900 dark:text-slate-100")
+
+            cost_chart.options.clear()
+            cost_chart.options.update(_cost_benefit_options(metrics))
             cost_chart.update()
-            waterfall_chart.options = _waterfall_options(metrics)
+            waterfall_chart.options.clear()
+            waterfall_chart.options.update(_waterfall_options(metrics))
             waterfall_chart.update()
 
         def refresh_from_selector(event) -> None:
-            selected["strategy"] = event.value
+            if syncing_controls["value"]:
+                return
+            selected["label"] = str(event.value)
+            selected["strategy"] = strategy_map()[selected["label"]]
             render_summary()
 
         def refresh_from_slider(event) -> None:
@@ -149,6 +322,43 @@ def hedge_page() -> None:
             slider_value.set_text(f"Scenario move: {sign}{selected['scenario_pct']}%")
             render_summary()
 
+        def save_template() -> None:
+            builder_status.set_text("")
+            try:
+                builder_kind = builder_type_options[str(builder_type.value)]
+                strikes = (float(builder_primary_strike.value or 0.0) / 100.0,)
+                weights: tuple[float, ...] | None = None
+                if builder_kind == "laddered_put":
+                    strikes = (
+                        float(builder_primary_strike.value or 0.0) / 100.0,
+                        float(builder_secondary_strike.value or 0.0) / 100.0,
+                    )
+                    weights = (0.5, 0.5)
+                template = template_service.create_custom_template(
+                    display_name=str(builder_name.value or ""),
+                    template_kind=builder_kind,
+                    target_expiry_days=int(builder_expiry_days.value or 0),
+                    strike_pcts=strikes,
+                    weights=weights,
+                )
+            except (ValueError, KeyError) as exc:
+                builder_status.set_text(str(exc))
+                return
+            refresh_available_strategies()
+            selected["label"] = template.display_name
+            selected["strategy"] = template.slug
+            syncing_controls["value"] = True
+            try:
+                selector.value = template.display_name
+                selector.update()
+            finally:
+                syncing_controls["value"] = False
+            builder_status.set_text(
+                f"Saved template {template.display_name}. Reusable on hedge, backtests, and event comparison."
+            )
+            render_summary()
+
         selector.on_value_change(refresh_from_selector)
         slider.on_value_change(refresh_from_slider)
+        save_template_button.on_click(lambda: save_template())
         render_summary()

app/pages/options.py

@@ -5,63 +5,90 @@ from typing import Any
 from nicegui import ui
 
 from app.components import GreeksTable
-from app.pages.common import dashboard_page, option_chain, strategy_catalog
+from app.pages.common import dashboard_page, split_page_panes, strategy_catalog
+from app.services.runtime import get_data_service
 
 
 @ui.page("/options")
-def options_page() -> None:
+async def options_page() -> None:
-    chain = option_chain()
+    data_service = get_data_service()
-    expiries = sorted({row["expiry"] for row in chain})
+    expirations_data = await data_service.get_option_expirations("GLD")
-    strike_values = sorted({row["strike"] for row in chain})
+    expiries = list(expirations_data.get("expirations") or [])
-    selected_expiry = {"value": expiries[0]}
+    default_expiry = expiries[0] if expiries else None
-    strike_range = {"min": strike_values[0], "max": strike_values[-1]}
+    chain_data = await data_service.get_options_chain_for_expiry("GLD", default_expiry)
+
+    chain_state = {
+        "data": chain_data,
+        "rows": list(chain_data.get("rows") or [*chain_data.get("calls", []), *chain_data.get("puts", [])]),
+    }
+    selected_expiry = {"value": chain_data.get("selected_expiry") or default_expiry}
     selected_strategy = {"value": strategy_catalog()[0]["label"]}
     chosen_contracts: list[dict[str, Any]] = []
 
+    def strike_bounds(rows: list[dict[str, Any]]) -> tuple[float, float]:
+        strike_values = sorted({float(row["strike"]) for row in rows})
+        if not strike_values:
+            return 0.0, 0.0
+        return strike_values[0], strike_values[-1]
+
+    initial_min_strike, initial_max_strike = strike_bounds(chain_state["rows"])
+    strike_range = {"min": initial_min_strike, "max": initial_max_strike}
+
     with dashboard_page(
         "Options Chain",
         "Browse GLD contracts, filter by expiry and strike range, inspect Greeks, and attach contracts to hedge workflows.",
         "options",
     ):
-        with ui.row().classes("w-full gap-6 max-lg:flex-col"):
+        left_pane, right_pane = split_page_panes(
+            left_testid="options-left-pane",
+            right_testid="options-right-pane",
+        )
+
+        with left_pane:
             with ui.card().classes(
                 "w-full rounded-2xl border border-slate-200 bg-white shadow-sm dark:border-slate-800 dark:bg-slate-900"
             ):
                 ui.label("Filters").classes("text-lg font-semibold text-slate-900 dark:text-slate-100")
                 expiry_select = ui.select(expiries, value=selected_expiry["value"], label="Expiry").classes("w-full")
-                min_strike = ui.number(
+                min_strike = ui.number("Min strike", value=strike_range["min"], step=5).classes("w-full")
-                    "Min strike",
+                max_strike = ui.number("Max strike", value=strike_range["max"], step=5).classes("w-full")
-                    value=strike_range["min"],
-                    min=strike_values[0],
-                    max=strike_values[-1],
-                    step=5,
-                ).classes("w-full")
-                max_strike = ui.number(
-                    "Max strike",
-                    value=strike_range["max"],
-                    min=strike_values[0],
-                    max=strike_values[-1],
-                    step=5,
-                ).classes("w-full")
                 strategy_select = ui.select(
                     [item["label"] for item in strategy_catalog()],
                     value=selected_strategy["value"],
                     label="Add to hedge strategy",
                 ).classes("w-full")
 
+                source_html = ui.html("").classes("text-xs text-slate-500 dark:text-slate-400")
+                error_html = ui.html("").classes("text-xs text-amber-700 dark:text-amber-300")
+                loading_html = ui.html("").classes("text-xs text-sky-700 dark:text-sky-300")
+
             selection_card = ui.card().classes(
                 "w-full rounded-2xl border border-slate-200 bg-white shadow-sm dark:border-slate-800 dark:bg-slate-900"
             )
 
+        with right_pane:
             chain_table = ui.html("").classes("w-full")
+            with ui.row().classes("w-full gap-6 max-xl:flex-col"):
                 greeks = GreeksTable([])
+                quick_add = ui.card().classes(
+                    "w-full rounded-2xl border border-slate-200 bg-white shadow-sm dark:border-slate-800 dark:bg-slate-900"
+                )
 
-        def filtered_rows() -> list[dict]:
+        def sync_status() -> None:
+            current_data = chain_state["data"]
+            source_label = f"Source: {current_data.get('source', 'unknown')}"
+            if current_data.get("updated_at"):
+                source_label += f" · Updated {current_data['updated_at']}"
+            source_html.content = source_label
+            source_html.update()
+
+            error_message = current_data.get("error") or expirations_data.get("error")
+            error_html.content = f"Options data unavailable: {error_message}" if error_message else ""
+            error_html.update()
+
+        def filtered_rows() -> list[dict[str, Any]]:
             return [
-                row
+                row for row in chain_state["rows"] if strike_range["min"] <= float(row["strike"]) <= strike_range["max"]
-                for row in chain
-                if row["expiry"] == selected_expiry["value"]
-                and strike_range["min"] <= row["strike"] <= strike_range["max"]
             ]
 
         def render_selection() -> None:
@@ -74,19 +101,21 @@ def options_page() -> None:
                 if not chosen_contracts:
                     ui.label("No contracts added yet.").classes("text-sm text-slate-500 dark:text-slate-400")
                     return
+                with ui.column().classes("w-full gap-3"):
                     for contract in chosen_contracts[-3:]:
+                        with ui.card().classes(
+                            "rounded-xl border border-slate-200 bg-slate-50 p-4 shadow-none dark:border-slate-800 dark:bg-slate-950"
+                        ):
+                            ui.label(contract["symbol"]).classes("font-semibold text-slate-900 dark:text-slate-100")
                             ui.label(
-                        f"{contract['symbol']} · premium ${contract['premium']:.2f} · Δ {contract['delta']:+.3f}"
+                                f"Premium ${float(contract['premium']):.2f} · IV {float(contract.get('impliedVolatility', 0.0)):.1%}"
                             ).classes("text-sm text-slate-600 dark:text-slate-300")
 
-        def add_to_strategy(contract: dict) -> None:
+        def add_to_strategy(contract: dict[str, Any]) -> None:
             chosen_contracts.append(contract)
             render_selection()
             greeks.set_options(chosen_contracts[-6:])
-            ui.notify(
+            ui.notify(f"Added {contract['symbol']} to {selected_strategy['value']}", color="positive")
-                f"Added {contract['symbol']} to {selected_strategy['value']}",
-                color="positive",
-            )
 
         def render_chain() -> None:
             rows = filtered_rows()
@@ -100,6 +129,8 @@ def options_page() -> None:
                             <th class='px-4 py-3 text-left text-xs font-semibold uppercase tracking-wide text-slate-500 dark:text-slate-300'>Type</th>
                             <th class='px-4 py-3 text-left text-xs font-semibold uppercase tracking-wide text-slate-500 dark:text-slate-300'>Strike</th>
                             <th class='px-4 py-3 text-left text-xs font-semibold uppercase tracking-wide text-slate-500 dark:text-slate-300'>Bid / Ask</th>
+                            <th class='px-4 py-3 text-left text-xs font-semibold uppercase tracking-wide text-slate-500 dark:text-slate-300'>Last</th>
+                            <th class='px-4 py-3 text-left text-xs font-semibold uppercase tracking-wide text-slate-500 dark:text-slate-300'>IV</th>
                             <th class='px-4 py-3 text-left text-xs font-semibold uppercase tracking-wide text-slate-500 dark:text-slate-300'>Greeks</th>
                             <th class='px-4 py-3 text-left text-xs font-semibold uppercase tracking-wide text-slate-500 dark:text-slate-300'>Action</th>
                         </tr>
@@ -110,16 +141,18 @@ def options_page() -> None:
                         <tr class='border-b border-slate-200 dark:border-slate-800'>
                             <td class='px-4 py-3 font-medium text-slate-900 dark:text-slate-100'>{row['symbol']}</td>
                             <td class='px-4 py-3 text-slate-600 dark:text-slate-300'>{row['type'].upper()}</td>
-                            <td class='px-4 py-3 text-slate-600 dark:text-slate-300'>${row['strike']:.2f}</td>
+                            <td class='px-4 py-3 text-slate-600 dark:text-slate-300'>${float(row['strike']):.2f}</td>
-                            <td class='px-4 py-3 text-slate-600 dark:text-slate-300'>${row['bid']:.2f} / ${row['ask']:.2f}</td>
+                            <td class='px-4 py-3 text-slate-600 dark:text-slate-300'>${float(row['bid']):.2f} / ${float(row['ask']):.2f}</td>
-                            <td class='px-4 py-3 text-slate-600 dark:text-slate-300'>Δ {row['delta']:+.3f} · Γ {row['gamma']:.3f} · Θ {row['theta']:+.3f}</td>
+                            <td class='px-4 py-3 text-slate-600 dark:text-slate-300'>${float(row.get('lastPrice', row.get('premium', 0.0))):.2f}</td>
+                            <td class='px-4 py-3 text-slate-600 dark:text-slate-300'>{float(row.get('impliedVolatility', 0.0)):.1%}</td>
+                            <td class='px-4 py-3 text-slate-600 dark:text-slate-300'>Δ {float(row.get('delta', 0.0)):+.3f} · Γ {float(row.get('gamma', 0.0)):.3f} · Θ {float(row.get('theta', 0.0)):+.3f} · V {float(row.get('vega', 0.0)):.3f}</td>
                             <td class='px-4 py-3 text-sky-600 dark:text-sky-300'>Use quick-add buttons below</td>
                         </tr>
                 """ for row in rows)
                 + (
                     ""
                     if rows
-                    else "<tr><td colspan='6' class='px-4 py-6 text-center text-slate-500 dark:text-slate-400'>No contracts match the current filter.</td></tr>"
+                    else "<tr><td colspan='8' class='px-4 py-6 text-center text-slate-500 dark:text-slate-400'>No contracts match the current filter.</td></tr>"
                 )
                 + """
                     </tbody>
@@ -136,36 +169,55 @@ def options_page() -> None:
                 with ui.row().classes("w-full gap-2 max-sm:flex-col"):
                     for row in rows[:6]:
                         ui.button(
-                            f"Add {row['type'].upper()} {row['strike']:.0f}",
+                            f"Add {row['type'].upper()} {float(row['strike']):.0f}",
                             on_click=lambda _, contract=row: add_to_strategy(contract),
                         ).props("outline color=primary")
-            greeks.set_options(rows[:6])
+            greeks.set_options(chosen_contracts[-6:] if chosen_contracts else rows[:6])
 
-        quick_add = ui.card().classes(
+        async def load_expiry_chain(expiry: str | None) -> None:
-            "w-full rounded-2xl border border-slate-200 bg-white shadow-sm dark:border-slate-800 dark:bg-slate-900"
+            selected_expiry["value"] = expiry
+            loading_html.content = "Loading selected expiry…" if expiry else ""
+            loading_html.update()
+
+            next_chain = await data_service.get_options_chain_for_expiry("GLD", expiry)
+            chain_state["data"] = next_chain
+            chain_state["rows"] = list(
+                next_chain.get("rows") or [*next_chain.get("calls", []), *next_chain.get("puts", [])]
             )
 
+            min_value, max_value = strike_bounds(chain_state["rows"])
+            strike_range["min"] = min_value
+            strike_range["max"] = max_value
+            min_strike.value = min_value
+            max_strike.value = max_value
+
+            loading_html.content = ""
+            loading_html.update()
+            sync_status()
+            render_chain()
+
         def update_filters() -> None:
-            selected_expiry["value"] = expiry_select.value
+            strike_range["min"] = float(min_strike.value or 0.0)
-            strike_range["min"] = float(min_strike.value)
+            strike_range["max"] = float(max_strike.value or 0.0)
-            strike_range["max"] = float(max_strike.value)
             if strike_range["min"] > strike_range["max"]:
-                strike_range["min"], strike_range["max"] = (
+                strike_range["min"], strike_range["max"] = (strike_range["max"], strike_range["min"])
-                    strike_range["max"],
-                    strike_range["min"],
-                )
                 min_strike.value = strike_range["min"]
                 max_strike.value = strike_range["max"]
             render_chain()
 
-        expiry_select.on_value_change(lambda _: update_filters())
+        async def on_expiry_change(event: Any) -> None:
+            await load_expiry_chain(event.value)
+
+        expiry_select.on_value_change(on_expiry_change)
         min_strike.on_value_change(lambda _: update_filters())
         max_strike.on_value_change(lambda _: update_filters())
-        def on_strategy_change(event) -> None:
+
-            selected_strategy["value"] = event.value  # type: ignore[assignment]
+        def on_strategy_change(event: Any) -> None:
+            selected_strategy["value"] = event.value
             render_selection()
 
         strategy_select.on_value_change(on_strategy_change)
 
+        sync_status()
         render_selection()
         render_chain()

app/pages/overview.py

@@ -1,81 +1,501 @@
 from __future__ import annotations
 
+import logging
+from datetime import datetime, timezone
+from decimal import Decimal
+
+from fastapi import Request
+from fastapi.responses import RedirectResponse
 from nicegui import ui
 
 from app.components import PortfolioOverview
+from app.domain.portfolio_math import resolve_portfolio_spot_from_quote
+from app.models.ltv_history import LtvHistoryRepository
+from app.models.workspace import WORKSPACE_COOKIE, get_workspace_repository
 from app.pages.common import (
     dashboard_page,
-    portfolio_snapshot,
     quick_recommendations,
     recommendation_style,
+    split_page_panes,
     strategy_catalog,
 )
+from app.services.alerts import AlertService, build_portfolio_alert_context
+from app.services.ltv_history import LtvHistoryChartModel, LtvHistoryService
+from app.services.runtime import get_data_service
+from app.services.storage_costs import calculate_total_storage_cost
+from app.services.turnstile import load_turnstile_settings
+
+logger = logging.getLogger(__name__)
+
+_DEFAULT_CASH_BUFFER = 18_500.0
+
+
+def _resolve_overview_spot(
+    config, quote: dict[str, object], *, fallback_symbol: str | None = None
+) -> tuple[float, str, str]:
+    return resolve_portfolio_spot_from_quote(config, quote, fallback_symbol=fallback_symbol)
+
+
+def _format_timestamp(value: str | None) -> str:
+    if not value:
+        return "Unavailable"
+    try:
+        timestamp = datetime.fromisoformat(value.replace("Z", "+00:00"))
+    except ValueError:
+        return value
+    return timestamp.astimezone(timezone.utc).strftime("%Y-%m-%d %H:%M:%S UTC")
+
+
+def _alert_badge_classes(severity: str) -> str:
+    return {
+        "critical": "rounded-full bg-rose-100 px-3 py-1 text-xs font-semibold text-rose-700 dark:bg-rose-500/15 dark:text-rose-300",
+        "warning": "rounded-full bg-amber-100 px-3 py-1 text-xs font-semibold text-amber-700 dark:bg-amber-500/15 dark:text-amber-300",
+        "ok": "rounded-full bg-emerald-100 px-3 py-1 text-xs font-semibold text-emerald-700 dark:bg-emerald-500/15 dark:text-emerald-300",
+    }.get(severity, "rounded-full bg-slate-100 px-3 py-1 text-xs font-semibold text-slate-700")
+
+
+def _ltv_chart_options(model: LtvHistoryChartModel) -> dict:
+    return {
+        "tooltip": {"trigger": "axis", "valueFormatter": "function (value) { return value + '%'; }"},
+        "legend": {"data": ["LTV", "Margin threshold"]},
+        "xAxis": {"type": "category", "data": list(model.labels)},
+        "yAxis": {"type": "value", "name": "LTV %", "axisLabel": {"formatter": "{value}%"}},
+        "series": [
+            {
+                "name": "LTV",
+                "type": "line",
+                "smooth": True,
+                "data": list(model.ltv_values),
+                "lineStyle": {"width": 3},
+            },
+            {
+                "name": "Margin threshold",
+                "type": "line",
+                "data": list(model.threshold_values),
+                "lineStyle": {"type": "dashed", "width": 2},
+                "symbol": "none",
+            },
+        ],
+    }
+
+
+def _render_workspace_recovery(title: str, message: str) -> None:
+    with ui.column().classes("mx-auto mt-24 w-full max-w-2xl gap-6 px-6 text-center"):
+        ui.icon("folder_off").classes("mx-auto text-6xl text-slate-400")
+        ui.label(title).classes("text-3xl font-bold text-slate-900 dark:text-slate-50")
+        ui.label(message).classes("text-base text-slate-500 dark:text-slate-400")
+        with ui.row().classes("mx-auto gap-3"):
+            ui.link("Get started", "/").classes(
+                "rounded-lg bg-slate-900 px-5 py-3 text-sm font-semibold text-white no-underline dark:bg-slate-100 dark:text-slate-900"
+            )
+            ui.link("Go to welcome page", "/").classes(
+                "rounded-lg border border-slate-300 px-5 py-3 text-sm font-semibold text-slate-700 no-underline dark:border-slate-700 dark:text-slate-200"
+            )
 
 
 @ui.page("/")
-@ui.page("/overview")
+def welcome_page(request: Request):
-def overview_page() -> None:
+    repo = get_workspace_repository()
-    portfolio = portfolio_snapshot()
+    workspace_id = request.cookies.get(WORKSPACE_COOKIE, "")
+    if workspace_id and repo.workspace_exists(workspace_id):
+        return RedirectResponse(url=f"/{workspace_id}", status_code=307)
+    captcha_error = request.query_params.get("captcha_error") == "1"
+
+    with ui.column().classes("mx-auto mt-24 w-full max-w-3xl gap-8 px-6"):
+        with ui.card().classes(
+            "w-full rounded-3xl border border-slate-200 bg-white p-8 shadow-sm dark:border-slate-800 dark:bg-slate-900"
+        ):
+            ui.label("Vault Dashboard").classes("text-sm font-semibold uppercase tracking-[0.2em] text-sky-600")
+            ui.label("Create a private workspace URL").classes("text-4xl font-bold text-slate-900 dark:text-slate-50")
+            ui.label(
+                "Start with a workspace-scoped overview and settings area. Your portfolio defaults are stored server-side and your browser keeps a workspace cookie for quick return visits."
+            ).classes("text-base text-slate-500 dark:text-slate-400")
+            if captcha_error:
+                ui.label("CAPTCHA verification failed. Please retry the Turnstile challenge.").classes(
+                    "rounded-lg border border-rose-200 bg-rose-50 px-4 py-3 text-sm font-medium text-rose-700 dark:border-rose-900/60 dark:bg-rose-950/30 dark:text-rose-300"
+                )
+            with ui.row().classes("items-center gap-4 pt-4"):
+                turnstile = load_turnstile_settings()
+                if turnstile.uses_test_keys:
+                    ui.html("""<form method="post" action="/workspaces/bootstrap" class="flex items-center gap-4">
+                        <input type="hidden" name="cf-turnstile-response" value="test-token" />
+                        <button type="submit" class="rounded-lg bg-slate-900 px-5 py-3 text-sm font-semibold text-white no-underline dark:bg-slate-100 dark:text-slate-900">Get started</button>
+                    </form>""")
+                else:
+                    ui.add_body_html(
+                        '<script src="https://challenges.cloudflare.com/turnstile/v0/api.js" async defer></script>'
+                    )
+                    ui.html(f"""<form method="post" action="/workspaces/bootstrap" class="flex items-center gap-4">
+                        <div class="cf-turnstile" data-sitekey="{turnstile.site_key}"></div>
+                        <button type="submit" class="rounded-lg bg-slate-900 px-5 py-3 text-sm font-semibold text-white no-underline dark:bg-slate-100 dark:text-slate-900">Get started</button>
+                    </form>""")
+                ui.label("You can always create a fresh workspace later if a link is lost.").classes(
+                    "text-sm text-slate-500 dark:text-slate-400"
+                )
+
+
+@ui.page("/{workspace_id}")
+@ui.page("/{workspace_id}/overview")
+async def overview_page(workspace_id: str) -> None:
+    repo = get_workspace_repository()
+    if not repo.workspace_exists(workspace_id):
+        return RedirectResponse(url="/", status_code=307)
+
+    config = repo.load_portfolio_config(workspace_id)
+    data_service = get_data_service()
+    underlying = config.underlying or "GLD"
+    symbol = underlying
+    quote = await data_service.get_quote(symbol)
+    overview_spot_price, overview_source, overview_updated_at = _resolve_overview_spot(
+        config, quote, fallback_symbol=symbol
+    )
+    portfolio = build_portfolio_alert_context(
+        config,
+        spot_price=overview_spot_price,
+        source=overview_source,
+        updated_at=overview_updated_at,
+    )
+
+    # Fetch basis data for GLD/GC=F comparison
+    try:
+        basis_data = await data_service.get_basis_data()
+    except Exception:
+        logger.exception("Failed to fetch basis data")
+        basis_data = None
+    configured_gold_value = float(config.gold_value or 0.0)
+    portfolio["cash_buffer"] = max(float(portfolio["gold_value"]) - configured_gold_value, 0.0) + _DEFAULT_CASH_BUFFER
+    portfolio["hedge_budget"] = float(config.monthly_budget)
+
+    # Calculate storage costs for positions
+    positions = config.positions
+    current_values: dict[str, Decimal] = {}
+    for pos in positions:
+        # Use entry value as proxy for current value (would need live prices for accurate calc)
+        current_values[str(pos.id)] = pos.entry_value
+    total_annual_storage_cost = calculate_total_storage_cost(positions, current_values)
+    portfolio["annual_storage_cost"] = float(total_annual_storage_cost)
+    portfolio["storage_cost_pct"] = (
+        (float(total_annual_storage_cost) / float(portfolio["gold_value"]) * 100)
+        if portfolio["gold_value"] > 0
+        else 0.0
+    )
+
+    alert_status = AlertService().evaluate(config, portfolio)
+    ltv_history_service = LtvHistoryService(repository=LtvHistoryRepository(base_path=repo.base_path))
+    ltv_history_notice: str | None = None
+    try:
+        ltv_history = ltv_history_service.record_workspace_snapshot(workspace_id, portfolio)
+        ltv_chart_models = tuple(
+            ltv_history_service.chart_model(
+                ltv_history,
+                days=days,
+                current_margin_threshold=config.margin_threshold,
+            )
+            for days in (7, 30, 90)
+        )
+        ltv_history_csv = ltv_history_service.export_csv(ltv_history) if ltv_history else ""
+    except Exception:
+        logger.exception("Failed to prepare LTV history for workspace %s", workspace_id)
+        ltv_history = []
+        ltv_chart_models = ()
+        ltv_history_csv = ""
+        ltv_history_notice = "Historical LTV is temporarily unavailable due to a storage error."
+    display_mode = portfolio.get("display_mode", "XAU")
+
+    if portfolio["quote_source"] == "configured_entry_price":
+        if display_mode == "GLD":
+            quote_status = "Live quote source: configured entry price fallback (GLD shares) · Last updated Unavailable"
+        else:
+            quote_status = "Live quote source: configured entry price fallback · Last updated Unavailable"
+    else:
+        if display_mode == "GLD":
+            quote_status = (
+                f"Live quote source: {portfolio['quote_source']} (GLD share price) · "
+                f"Last updated {_format_timestamp(str(portfolio['quote_updated_at']))}"
+            )
+        else:
+            quote_status = (
+                f"Live quote source: {portfolio['quote_source']} · "
+                f"GLD share quote converted to ozt-equivalent spot · "
+                f"Last updated {_format_timestamp(str(portfolio['quote_updated_at']))}"
+            )
+
+    if display_mode == "GLD":
+        spot_caption = (
+            f"{symbol} share price via {portfolio['quote_source']}"
+            if portfolio["quote_source"] != "configured_entry_price"
+            else "Configured GLD share entry price"
+        )
+    else:
+        spot_caption = (
+            f"{symbol} share quote converted to USD/ozt via {portfolio['quote_source']}"
+            if portfolio["quote_source"] != "configured_entry_price"
+            else "Configured entry price fallback in USD/ozt"
+        )
 
     with dashboard_page(
         "Overview",
-        "Portfolio health, LTV risk, and quick strategy guidance for the current GLD-backed loan.",
+        f"Portfolio health, LTV risk, and quick strategy guidance for the current {underlying}-backed loan.",
         "overview",
+        workspace_id=workspace_id,
     ):
-        with ui.grid(columns=4).classes("w-full gap-4 max-lg:grid-cols-2 max-sm:grid-cols-1"):
+        with ui.row().classes("w-full items-center justify-between gap-4 max-md:flex-col max-md:items-start"):
+            ui.label(quote_status).classes("text-sm text-slate-500 dark:text-slate-400")
+            ui.label(
+                f"Active underlying: {underlying} · Configured collateral baseline: ${config.gold_value:,.0f} · Loan ${config.loan_amount:,.0f}"
+            ).classes("text-sm text-slate-500 dark:text-slate-400")
+
+        left_pane, right_pane = split_page_panes(
+            left_testid="overview-left-pane",
+            right_testid="overview-right-pane",
+        )
+
+        with left_pane:
+            # GLD/GC=F Basis Card
+            with ui.card().classes(
+                "w-full rounded-2xl border border-slate-200 bg-white shadow-sm dark:border-slate-800 dark:bg-slate-900"
+            ):
+                with ui.row().classes("w-full items-center justify-between gap-3"):
+                    ui.label("GLD/GC=F Basis").classes("text-lg font-semibold text-slate-900 dark:text-slate-100")
+                    if basis_data:
+                        basis_badge_class = {
+                            "green": "rounded-full bg-emerald-100 px-3 py-1 text-xs font-semibold text-emerald-700 dark:bg-emerald-500/15 dark:text-emerald-300",
+                            "yellow": "rounded-full bg-amber-100 px-3 py-1 text-xs font-semibold text-amber-700 dark:bg-amber-500/15 dark:text-amber-300",
+                            "red": "rounded-full bg-rose-100 px-3 py-1 text-xs font-semibold text-rose-700 dark:bg-rose-500/15 dark:text-rose-300",
+                        }.get(
+                            basis_data["basis_status"],
+                            "rounded-full bg-slate-100 px-3 py-1 text-xs font-semibold text-slate-700",
+                        )
+                        ui.label(f"{basis_data['basis_label']} ({basis_data['basis_bps']:+.1f} bps)").classes(
+                            basis_badge_class
+                        )
+
+                if basis_data:
+                    with ui.grid(columns=2).classes("w-full gap-4 mt-4"):
+                        # GLD Implied Spot
+                        with ui.card().classes(
+                            "rounded-xl border border-slate-200 bg-slate-50 p-4 shadow-none dark:border-slate-800 dark:bg-slate-950"
+                        ):
+                            ui.label("GLD Implied Spot").classes(
+                                "text-sm font-medium text-slate-500 dark:text-slate-400"
+                            )
+                            ui.label(f"${basis_data['gld_implied_spot']:,.2f}/oz").classes(
+                                "text-2xl font-bold text-slate-900 dark:text-slate-50"
+                            )
+                            ui.label(
+                                f"GLD ${basis_data['gld_price']:.2f} ÷ {basis_data['gld_ounces_per_share']:.4f} oz/share"
+                            ).classes("text-xs text-slate-500 dark:text-slate-400")
+
+                        # GC=F Adjusted
+                        with ui.card().classes(
+                            "rounded-xl border border-slate-200 bg-slate-50 p-4 shadow-none dark:border-slate-800 dark:bg-slate-950"
+                        ):
+                            ui.label("GC=F Adjusted").classes("text-sm font-medium text-slate-500 dark:text-slate-400")
+                            ui.label(f"${basis_data['gc_f_adjusted']:,.2f}/oz").classes(
+                                "text-2xl font-bold text-slate-900 dark:text-slate-50"
+                            )
+                            ui.label(
+                                f"GC=F ${basis_data['gc_f_price']:.2f} - ${basis_data['contango_estimate']:.0f} contango"
+                            ).classes("text-xs text-slate-500 dark:text-slate-400")
+
+                    # Basis explanation and after-hours notice
+                    with ui.row().classes("w-full items-start gap-2 mt-4"):
+                        ui.icon("info", size="xs").classes("text-slate-400 mt-0.5")
+                        ui.label(
+                            "Basis shows the premium/discount between GLD-implied gold and futures-adjusted spot. "
+                            "Green < 25 bps (normal), Yellow 25-50 bps (elevated), Red > 50 bps (unusual)."
+                        ).classes("text-xs text-slate-500 dark:text-slate-400")
+
+                    if basis_data["after_hours"]:
+                        with ui.row().classes("w-full items-start gap-2 mt-2"):
+                            ui.icon("schedule", size="xs").classes("text-amber-500 mt-0.5")
+                            ui.label(
+                                f"{basis_data['after_hours_note']} · GLD: {_format_timestamp(basis_data['gld_updated_at'])} · "
+                                f"GC=F: {_format_timestamp(basis_data['gc_f_updated_at'])}"
+                            ).classes("text-xs text-amber-700 dark:text-amber-300")
+
+                    # Warning for elevated basis
+                    if basis_data["basis_status"] == "red":
+                        ui.label(
+                            f"⚠️ Elevated basis detected: {basis_data['basis_bps']:+.1f} bps. "
+                            "This may indicate after-hours pricing gaps, physical stress, or arbitrage disruption."
+                        ).classes("text-sm font-medium text-rose-700 dark:text-rose-300 mt-3")
+                else:
+                    ui.label("Basis data temporarily unavailable").classes("text-sm text-slate-500 dark:text-slate-400")
+
+            with ui.card().classes(
+                "w-full rounded-2xl border border-slate-200 bg-white shadow-sm dark:border-slate-800 dark:bg-slate-900"
+            ):
+                with ui.row().classes("w-full items-center justify-between gap-3"):
+                    ui.label("Alert Status").classes("text-lg font-semibold text-slate-900 dark:text-slate-100")
+                    ui.label(alert_status.severity.upper()).classes(_alert_badge_classes(alert_status.severity))
+                ui.label(alert_status.message).classes("text-sm text-slate-600 dark:text-slate-300")
+                ui.label(
+                    f"Warning at {alert_status.warning_threshold:.0%} · Critical at {alert_status.critical_threshold:.0%} · "
+                    f"Email alerts {'enabled' if alert_status.email_alerts_enabled else 'disabled'}"
+                ).classes("text-sm text-slate-500 dark:text-slate-400")
+                if alert_status.history_notice:
+                    ui.label(alert_status.history_notice).classes("text-sm text-amber-700 dark:text-amber-300")
+                if alert_status.history:
+                    latest = alert_status.history[0]
+                    ui.label(
+                        f"Latest alert logged {_format_timestamp(latest.updated_at)} at collateral spot ${latest.spot_price:,.2f}"
+                    ).classes("text-xs text-slate-500 dark:text-slate-400")
+
+            with ui.card().classes(
+                "w-full rounded-2xl border border-slate-200 bg-white shadow-sm dark:border-slate-800 dark:bg-slate-900"
+            ):
+                ui.label("Portfolio Snapshot").classes("text-lg font-semibold text-slate-900 dark:text-slate-100")
+
+                # Display mode-aware labels
+                if display_mode == "GLD":
+                    spot_label = "GLD Share Price"
+                    spot_unit = "/share"
+                    margin_label = "Margin Call Share Price"
+                else:
+                    spot_label = "Collateral Spot Price"
+                    spot_unit = "/oz"
+                    margin_label = "Margin Call Price"
+
+                with ui.grid(columns=1).classes("w-full gap-4 sm:grid-cols-2 lg:grid-cols-1 xl:grid-cols-2"):
                     summary_cards = [
                         (
-                    "Spot Price",
+                            spot_label,
-                    f"${portfolio['spot_price']:,.2f}",
+                            f"${portfolio['spot_price']:,.2f}{spot_unit}",
-                    "GLD reference price",
+                            spot_caption,
                         ),
                         (
-                    "Margin Call Price",
+                            margin_label,
                             f"${portfolio['margin_call_price']:,.2f}",
-                    "Implied trigger level",
+                            "Implied trigger level from persisted portfolio settings",
                         ),
                         (
                             "Cash Buffer",
                             f"${portfolio['cash_buffer']:,.0f}",
-                    "Available liquidity",
+                            "Base liquidity plus unrealized gain cushion vs configured baseline",
                         ),
                         (
                             "Hedge Budget",
                             f"${portfolio['hedge_budget']:,.0f}",
-                    "Approved premium budget",
+                            "Monthly budget from saved settings",
+                        ),
+                        (
+                            "Storage Costs",
+                            f"${portfolio['annual_storage_cost']:,.2f}/yr ({portfolio['storage_cost_pct']:.2f}%)",
+                            "Annual vault storage for physical positions (GLD expense ratio baked into share price)",
                         ),
                     ]
                     for title, value, caption in summary_cards:
                         with ui.card().classes(
-                    "rounded-2xl border border-slate-200 bg-white shadow-sm dark:border-slate-800 dark:bg-slate-900"
+                            "rounded-xl border border-slate-200 bg-slate-50 p-4 shadow-none dark:border-slate-800 dark:bg-slate-950"
                         ):
                             ui.label(title).classes("text-sm font-medium text-slate-500 dark:text-slate-400")
-                    ui.label(value).classes("text-3xl font-bold text-slate-900 dark:text-slate-50")
+                            ui.label(value).classes("text-2xl font-bold text-slate-900 dark:text-slate-50")
                             ui.label(caption).classes("text-sm text-slate-500 dark:text-slate-400")
 
-        portfolio_view = PortfolioOverview(margin_call_ltv=portfolio["margin_call_ltv"])
+            with ui.card().classes(f"w-full rounded-2xl border shadow-sm {recommendation_style('info')}"):
+                ui.label("Quick Strategy Recommendations").classes(
+                    "text-lg font-semibold text-slate-900 dark:text-slate-100"
+                )
+                for rec in quick_recommendations(portfolio):
+                    with ui.card().classes(f"rounded-xl border shadow-none {recommendation_style(rec['tone'])}"):
+                        ui.label(rec["title"]).classes("text-base font-semibold text-slate-900 dark:text-slate-100")
+                        ui.label(rec["summary"]).classes("text-sm text-slate-600 dark:text-slate-300")
+
+        with right_pane:
+            portfolio_view = PortfolioOverview(margin_call_ltv=float(portfolio["margin_call_ltv"]))
             portfolio_view.update(portfolio)
 
-        with ui.row().classes("w-full gap-6 max-lg:flex-col"):
+            with ui.row().classes("w-full gap-6 max-xl:flex-col"):
                 with ui.card().classes(
                     "w-full rounded-2xl border border-slate-200 bg-white shadow-sm dark:border-slate-800 dark:bg-slate-900"
                 ):
                     with ui.row().classes("w-full items-center justify-between"):
-                    ui.label("Current LTV Status").classes("text-lg font-semibold text-slate-900 dark:text-slate-100")
+                        ui.label("Current LTV Status").classes(
-                    ui.label(f"Threshold {portfolio['margin_call_ltv'] * 100:.0f}%").classes(
+                            "text-lg font-semibold text-slate-900 dark:text-slate-100"
+                        )
+                        ui.label(f"Threshold {float(portfolio['margin_call_ltv']) * 100:.0f}%").classes(
                             "rounded-full bg-rose-100 px-3 py-1 text-xs font-semibold text-rose-700 dark:bg-rose-500/15 dark:text-rose-300"
                         )
                     ui.linear_progress(
-                    value=portfolio["ltv_ratio"] / portfolio["margin_call_ltv"],
+                        value=float(portfolio["ltv_ratio"]) / max(float(portfolio["margin_call_ltv"]), 0.01),
                         show_value=False,
                     ).props("color=warning track-color=grey-3 rounded")
                     ui.label(
-                    f"Current LTV is {portfolio['ltv_ratio'] * 100:.1f}% with a margin buffer of {(portfolio['margin_call_ltv'] - portfolio['ltv_ratio']) * 100:.1f} percentage points."
+                        f"Current LTV is {float(portfolio['ltv_ratio']) * 100:.1f}% with a margin buffer of {(float(portfolio['margin_call_ltv']) - float(portfolio['ltv_ratio'])) * 100:.1f} percentage points."
                     ).classes("text-sm text-slate-600 dark:text-slate-300")
                     ui.label(
                         "Warning: if GLD approaches the margin-call price, collateral remediation or hedge monetization will be required."
                     ).classes("text-sm font-medium text-amber-700 dark:text-amber-300")
 
+                with ui.card().classes(
+                    "w-full rounded-2xl border border-slate-200 bg-white shadow-sm dark:border-slate-800 dark:bg-slate-900"
+                ):
+                    with ui.row().classes(
+                        "w-full items-center justify-between gap-3 max-sm:flex-col max-sm:items-start"
+                    ):
+                        with ui.column().classes("gap-1"):
+                            ui.label("Historical LTV").classes(
+                                "text-lg font-semibold text-slate-900 dark:text-slate-100"
+                            )
+                            ui.label(
+                                "Stored workspace snapshots show how LTV trended against the current margin threshold over 7, 30, and 90 day windows."
+                            ).classes("text-sm text-slate-500 dark:text-slate-400")
+                        if ltv_history:
+                            ui.button(
+                                "Export CSV",
+                                icon="download",
+                                on_click=lambda: ui.download.content(
+                                    ltv_history_csv,
+                                    filename=f"{workspace_id}-ltv-history.csv",
+                                    media_type="text/csv",
+                                ),
+                            ).props("outline color=primary")
+                    if ltv_history_notice:
+                        ui.label(ltv_history_notice).classes("text-sm text-amber-700 dark:text-amber-300")
+                    elif ltv_history:
+                        with ui.grid(columns=1).classes("w-full gap-4 xl:grid-cols-3"):
+                            for chart_model, chart_testid in zip(
+                                ltv_chart_models,
+                                ("ltv-history-chart-7d", "ltv-history-chart-30d", "ltv-history-chart-90d"),
+                                strict=True,
+                            ):
+                                with ui.card().classes(
+                                    "rounded-xl border border-slate-200 bg-slate-50 p-4 shadow-none dark:border-slate-800 dark:bg-slate-950"
+                                ):
+                                    ui.label(chart_model.title).classes(
+                                        "text-base font-semibold text-slate-900 dark:text-slate-100"
+                                    )
+                                    ui.echart(_ltv_chart_options(chart_model)).props(
+                                        f"data-testid={chart_testid}"
+                                    ).classes("h-56 w-full")
+                    else:
+                        ui.label("No LTV snapshots recorded yet.").classes("text-sm text-slate-500 dark:text-slate-400")
+
+                with ui.card().classes(
+                    "w-full rounded-2xl border border-slate-200 bg-white shadow-sm dark:border-slate-800 dark:bg-slate-900"
+                ):
+                    ui.label("Recent Alert History").classes("text-lg font-semibold text-slate-900 dark:text-slate-100")
+                    if alert_status.history:
+                        for event in alert_status.history[:5]:
+                            with ui.row().classes(
+                                "w-full items-start justify-between gap-4 border-b border-slate-100 py-3 last:border-b-0 dark:border-slate-800"
+                            ):
+                                with ui.column().classes("gap-1"):
+                                    ui.label(event.message).classes(
+                                        "text-sm font-medium text-slate-900 dark:text-slate-100"
+                                    )
+                                    ui.label(
+                                        f"Logged {_format_timestamp(event.updated_at)} · Spot ${event.spot_price:,.2f} · LTV {event.ltv_ratio:.1%}"
+                                    ).classes("text-xs text-slate-500 dark:text-slate-400")
+                                ui.label(event.severity.upper()).classes(_alert_badge_classes(event.severity))
+                    elif alert_status.history_notice:
+                        ui.label(alert_status.history_notice).classes("text-sm text-amber-700 dark:text-amber-300")
+                    else:
+                        ui.label(
+                            "No alert history yet. Alerts will be logged once the warning threshold is crossed."
+                        ).classes("text-sm text-slate-500 dark:text-slate-400")
+
             with ui.card().classes(
                 "w-full rounded-2xl border border-slate-200 bg-white shadow-sm dark:border-slate-800 dark:bg-slate-900"
             ):
@@ -90,10 +510,3 @@ def overview_page() -> None:
                         ui.label(f"${strategy['estimated_cost']:.2f}/oz").classes(
                             "rounded-full bg-sky-100 px-3 py-1 text-xs font-semibold text-sky-700 dark:bg-sky-500/15 dark:text-sky-300"
                         )
-
-        ui.label("Quick Strategy Recommendations").classes("text-xl font-semibold text-slate-900 dark:text-slate-100")
-        with ui.grid(columns=3).classes("w-full gap-4 max-lg:grid-cols-1"):
-            for rec in quick_recommendations():
-                with ui.card().classes(f"rounded-2xl border shadow-sm {recommendation_style(rec['tone'])}"):
-                    ui.label(rec["title"]).classes("text-base font-semibold text-slate-900 dark:text-slate-100")
-                    ui.label(rec["summary"]).classes("text-sm text-slate-600 dark:text-slate-300")

app/pages/settings.py

@@ -1,73 +1,290 @@
 from __future__ import annotations
 
+import logging
+from datetime import date
+from decimal import Decimal
+from uuid import uuid4
+
+from fastapi.responses import RedirectResponse
 from nicegui import ui
 
-from app.pages.common import dashboard_page
+from app.domain.conversions import get_display_mode_options
-from app.models.portfolio import PortfolioConfig, get_portfolio_repository
+from app.models.portfolio import PortfolioConfig
+from app.models.position import Position
+from app.models.workspace import get_workspace_repository
+from app.pages.common import dashboard_page, split_page_panes
+from app.services.alerts import AlertService, build_portfolio_alert_context
+from app.services.settings_status import save_status_text
+from app.services.storage_costs import get_default_storage_cost_for_underlying
+
+logger = logging.getLogger(__name__)
 
 
-@ui.page("/settings")
+def _alert_badge_classes(severity: str) -> str:
-def settings_page():
+    return {
-    """Settings page with persistent portfolio configuration."""
+        "critical": "rounded-full bg-rose-100 px-3 py-1 text-xs font-semibold text-rose-700 dark:bg-rose-500/15 dark:text-rose-300",
-    # Load current configuration
+        "warning": "rounded-full bg-amber-100 px-3 py-1 text-xs font-semibold text-amber-700 dark:bg-amber-500/15 dark:text-amber-300",
-    repo = get_portfolio_repository()
+        "ok": "rounded-full bg-emerald-100 px-3 py-1 text-xs font-semibold text-emerald-700 dark:bg-emerald-500/15 dark:text-emerald-300",
-    config = repo.load()
+    }.get(severity, "rounded-full bg-slate-100 px-3 py-1 text-xs font-semibold text-slate-700")
+
+
+def _save_card_status_text(
+    last_saved_config: PortfolioConfig,
+    *,
+    preview_config: PortfolioConfig | None = None,
+    invalid: bool = False,
+    save_failed: bool = False,
+) -> str:
+    base = save_status_text(last_saved_config).replace("Saved:", "Last saved:", 1)
+    if save_failed:
+        return f"Save failed — {base}"
+    if invalid:
+        return f"Unsaved invalid changes — {base}"
+    if preview_config is not None and preview_config.to_dict() != last_saved_config.to_dict():
+        return f"Unsaved changes — {base}"
+    return base
+
+
+def _render_workspace_recovery() -> None:
+    with ui.column().classes("mx-auto mt-24 w-full max-w-2xl gap-6 px-6 text-center"):
+        ui.icon("folder_off").classes("mx-auto text-6xl text-slate-400")
+        ui.label("Workspace not found").classes("text-3xl font-bold text-slate-900 dark:text-slate-50")
+        ui.label(
+            "The requested workspace is unavailable. Start a new workspace or return to the welcome page."
+        ).classes("text-base text-slate-500 dark:text-slate-400")
+        with ui.row().classes("mx-auto gap-3"):
+            ui.link("Get started", "/").classes(
+                "rounded-lg bg-slate-900 px-5 py-3 text-sm font-semibold text-white no-underline dark:bg-slate-100 dark:text-slate-900"
+            )
+            ui.link("Go to welcome page", "/").classes(
+                "rounded-lg border border-slate-300 px-5 py-3 text-sm font-semibold text-slate-700 no-underline dark:border-slate-700 dark:text-slate-200"
+            )
+
+
+@ui.page("/{workspace_id}/settings")
+def settings_page(workspace_id: str) -> None:
+    """Settings page with workspace-scoped persistent portfolio configuration."""
+    workspace_repo = get_workspace_repository()
+    if not workspace_repo.workspace_exists(workspace_id):
+        return RedirectResponse(url="/", status_code=307)
+
+    config = workspace_repo.load_portfolio_config(workspace_id)
+    last_saved_config = config
+    alert_service = AlertService()
+
+    syncing_entry_basis = False
+
+    def as_positive_float(value: object) -> float | None:
+        try:
+            parsed = float(value)
+        except (TypeError, ValueError):
+            return None
+        return parsed if parsed > 0 else None
+
+    def as_non_negative_float(value: object) -> float | None:
+        try:
+            parsed = float(value)
+        except (TypeError, ValueError):
+            return None
+        return parsed if parsed >= 0 else None
+
+    def display_number_input_value(value: object) -> str:
+        try:
+            parsed = float(value)
+        except (TypeError, ValueError):
+            return ""
+        if parsed.is_integer():
+            return str(int(parsed))
+        return str(parsed)
+
+    def as_positive_int(value: object) -> int | None:
+        try:
+            parsed = float(value)
+        except (TypeError, ValueError):
+            return None
+        if parsed < 1 or not parsed.is_integer():
+            return None
+        return int(parsed)
+
+    def build_preview_config() -> PortfolioConfig:
+        parsed_loan_amount = as_non_negative_float(loan_amount.value)
+        if parsed_loan_amount is None:
+            raise ValueError("Loan amount must be zero or greater")
+
+        parsed_refresh_interval = as_positive_int(refresh_interval.value)
+        if parsed_refresh_interval is None:
+            raise ValueError("Refresh interval must be a whole number of seconds")
+
+        return PortfolioConfig(
+            gold_value=as_positive_float(gold_value.value),
+            entry_price=as_positive_float(entry_price.value),
+            gold_ounces=as_positive_float(gold_ounces.value),
+            entry_basis_mode=str(entry_basis_mode.value),  # type: ignore[arg-type]
+            loan_amount=parsed_loan_amount,
+            margin_threshold=float(margin_threshold.value),
+            monthly_budget=float(monthly_budget.value),
+            ltv_warning=float(ltv_warning.value),
+            primary_source=str(primary_source.value),
+            fallback_source=str(fallback_source.value),
+            refresh_interval=parsed_refresh_interval,
+            underlying=str(underlying.value),
+            display_mode=str(display_mode.value),  # type: ignore[arg-type]
+            volatility_spike=float(vol_alert.value),
+            spot_drawdown=float(price_alert.value),
+            email_alerts=bool(email_alerts.value),
+        )
 
     with dashboard_page(
         "Settings",
-        "Configure portfolio assumptions, preferred market data inputs, alert thresholds, and import/export behavior.",
+        "Configure portfolio assumptions, collateral entry basis, preferred market data inputs, and alert thresholds.",
         "settings",
+        workspace_id=workspace_id,
     ):
-        with ui.row().classes("w-full gap-6 max-lg:flex-col"):
+        left_pane, right_pane = split_page_panes(
+            left_testid="settings-left-pane",
+            right_testid="settings-right-pane",
+        )
+
+        with left_pane:
             with ui.card().classes(
                 "w-full rounded-2xl border border-slate-200 bg-white shadow-sm dark:border-slate-800 dark:bg-slate-900"
             ):
                 ui.label("Portfolio Parameters").classes("text-lg font-semibold text-slate-900 dark:text-slate-100")
+                ui.label(
+                    "Choose whether collateral entry is keyed by start value or by gold weight. The paired field is derived automatically from the entry price."
+                ).classes("text-sm text-slate-500 dark:text-slate-400")
+
+                entry_basis_mode = ui.select(
+                    {"value_price": "Start value + entry price", "weight": "Gold weight + entry price"},
+                    value=config.entry_basis_mode,
+                    label="Collateral entry basis",
+                ).classes("w-full")
+
+                entry_price = ui.number(
+                    "Entry price ($/oz)",
+                    value=config.entry_price,
+                    min=0.01,
+                    step=0.01,
+                ).classes("w-full")
 
                 gold_value = ui.number(
-                    "Gold collateral value ($)", 
+                    "Collateral start value ($)",
                     value=config.gold_value,
-                    min=0.01,  # Must be positive
+                    min=0.01,
-                    step=1000
+                    step=1000,
                 ).classes("w-full")
 
-                loan_amount = ui.number(
+                gold_ounces = ui.number(
-                    "Loan amount ($)", 
+                    "Gold weight (oz)",
-                    value=config.loan_amount, 
+                    value=config.gold_ounces,
-                    min=0, 
+                    min=0.0001,
-                    step=1000
+                    step=0.01,
                 ).classes("w-full")
 
+                loan_amount = (
+                    ui.input(
+                        "Loan amount ($)",
+                        value=display_number_input_value(config.loan_amount),
+                    )
+                    .props("type=number min=0 step=1000")
+                    .classes("w-full")
+                )
+
                 margin_threshold = ui.number(
                     "Margin call LTV threshold",
                     value=config.margin_threshold,
                     min=0.1,
                     max=0.95,
-                    step=0.01
+                    step=0.01,
                 ).classes("w-full")
 
                 monthly_budget = ui.number(
                     "Monthly hedge budget ($)",
                     value=config.monthly_budget,
                     min=0,
-                    step=500
+                    step=500,
                 ).classes("w-full")
 
-                # Show calculated values
+                derived_hint = ui.label().classes("text-sm text-slate-500 dark:text-slate-400")
-                with ui.row().classes("w-full gap-2 mt-4 p-4 bg-slate-50 dark:bg-slate-800 rounded-lg"):
+
+                with ui.row().classes("w-full gap-2 mt-4 rounded-lg bg-slate-50 p-4 dark:bg-slate-800"):
                     ui.label("Current LTV:").classes("font-medium")
-                    ltv_display = ui.label(f"{(config.loan_amount / config.gold_value * 100):.1f}%")
+                    ltv_display = ui.label()
 
-                    ui.label("Margin buffer:").classes("font-medium ml-4")
+                    ui.label("Margin buffer:").classes("ml-4 font-medium")
-                    buffer_display = ui.label(f"{((config.margin_threshold - config.loan_amount / config.gold_value) * 100):.1f}%")
+                    buffer_display = ui.label()
 
-                    ui.label("Margin call at:").classes("font-medium ml-4")
+                    ui.label("Margin call at:").classes("ml-4 font-medium")
-                    margin_price_display = ui.label(f"${(config.loan_amount / config.margin_threshold):,.2f}")
+                    margin_price_display = ui.label()
 
             with ui.card().classes(
                 "w-full rounded-2xl border border-slate-200 bg-white shadow-sm dark:border-slate-800 dark:bg-slate-900"
             ):
+                ui.label("Alert Thresholds").classes("text-lg font-semibold text-slate-900 dark:text-slate-100")
+                ltv_warning = ui.number(
+                    "LTV warning level",
+                    value=config.ltv_warning,
+                    min=0.1,
+                    max=0.95,
+                    step=0.01,
+                ).classes("w-full")
+                vol_alert = ui.number(
+                    "Volatility spike alert",
+                    value=config.volatility_spike,
+                    min=0.01,
+                    max=2.0,
+                    step=0.01,
+                ).classes("w-full")
+                price_alert = ui.number(
+                    "Spot drawdown alert (%)",
+                    value=config.spot_drawdown,
+                    min=0.1,
+                    max=50.0,
+                    step=0.5,
+                ).classes("w-full")
+                email_alerts = ui.switch("Email alerts", value=config.email_alerts)
+                ui.label("Defaults remain warn at 70% and critical at 75% unless you override them.").classes(
+                    "text-sm text-slate-500 dark:text-slate-400"
+                )
+
+        with right_pane:
+            with ui.card().classes(
+                "w-full rounded-2xl border border-slate-200 bg-white shadow-sm dark:border-slate-800 dark:bg-slate-900"
+            ):
+                ui.label("Display Mode").classes("text-lg font-semibold text-slate-900 dark:text-slate-100")
+                ui.label(
+                    "Choose how to view your portfolio: GLD shares (financial instrument view) or physical gold ounces."
+                ).classes("text-sm text-slate-500 dark:text-slate-400 mb-3")
+                display_mode = ui.select(
+                    {
+                        "GLD": "GLD Shares (show share prices directly)",
+                        "XAU": "Physical Gold (oz) (convert to gold ounces)",
+                    },
+                    value=config.display_mode,
+                    label="Display mode",
+                ).classes("w-full")
+
+                ui.separator().classes("my-4")
+
                 ui.label("Data Sources").classes("text-lg font-semibold text-slate-900 dark:text-slate-100")
+                underlying = ui.select(
+                    {
+                        "GLD": "SPDR Gold Shares ETF (live data via yfinance)",
+                        "GC=F": "Gold Futures (coming soon)",
+                    },
+                    value=config.underlying,
+                    label="Underlying instrument",
+                ).classes("w-full")
+
+                display_mode = ui.select(
+                    get_display_mode_options(),
+                    value=config.display_mode,
+                    label="Display Mode",
+                ).classes("w-full")
+                ui.label("Choose how to display positions and collateral values.").classes(
+                    "text-xs text-slate-500 dark:text-slate-400 -mt-2"
+                )
+
                 primary_source = ui.select(
                     ["yfinance", "ibkr", "alpaca"],
                     value=config.primary_source,
@@ -82,114 +299,452 @@ def settings_page():
                     "Refresh interval (seconds)",
                     value=config.refresh_interval,
                     min=1,
-                    step=1
+                    step=1,
                 ).classes("w-full")
 
-                def update_calculations():
+            # Position Management Card
-                    """Update calculated displays when values change."""
-                    try:
-                        gold = gold_value.value or 1  # Avoid division by zero
-                        loan = loan_amount.value or 0
-                        margin = margin_threshold.value or 0.75
-                        
-                        ltv = (loan / gold) * 100
-                        buffer = (margin - loan / gold) * 100
-                        margin_price = loan / margin if margin > 0 else 0
-                        
-                        ltv_display.set_text(f"{ltv:.1f}%")
-                        buffer_display.set_text(f"{buffer:.1f}%")
-                        margin_price_display.set_text(f"${margin_price:,.2f}")
-                    except Exception:
-                        pass  # Ignore calculation errors during editing
-                
-                # Connect update function to value changes
-                gold_value.on_value_change(update_calculations)
-                loan_amount.on_value_change(update_calculations)
-                margin_threshold.on_value_change(update_calculations)
-
-        with ui.row().classes("w-full gap-6 max-lg:flex-col"):
             with ui.card().classes(
                 "w-full rounded-2xl border border-slate-200 bg-white shadow-sm dark:border-slate-800 dark:bg-slate-900"
             ):
-                ui.label("Alert Thresholds").classes("text-lg font-semibold text-slate-900 dark:text-slate-100")
+                ui.label("Portfolio Positions").classes("text-lg font-semibold text-slate-900 dark:text-slate-100")
-                ltv_warning = ui.number(
+                ui.label(
-                    "LTV warning level", 
+                    "Manage individual position entries. Each position tracks its own entry date and price."
-                    value=config.ltv_warning, 
+                ).classes("text-sm text-slate-500 dark:text-slate-400")
-                    min=0.1, 
+
-                    max=0.95, 
+                # Position list container
-                    step=0.01
+                position_list_container = ui.column().classes("w-full gap-2 mt-3")
-                ).classes("w-full")
+
-                vol_alert = ui.number(
+                # Add position form (hidden by default)
-                    "Volatility spike alert", 
+                with (
-                    value=config.volatility_spike, 
+                    ui.dialog() as add_position_dialog,
-                    min=0.01, 
+                    ui.card().classes(
-                    max=2.0, 
+                        "w-full max-w-md rounded-2xl border border-slate-200 bg-white p-6 shadow-lg dark:border-slate-800 dark:bg-slate-900"
-                    step=0.01
+                    ),
-                ).classes("w-full")
+                ):
-                price_alert = ui.number(
+                    ui.label("Add New Position").classes(
-                    "Spot drawdown alert (%)", 
+                        "text-lg font-semibold text-slate-900 dark:text-slate-100 mb-4"
-                    value=config.spot_drawdown, 
-                    min=0.1, 
-                    max=50.0, 
-                    step=0.5
-                ).classes("w-full")
-                email_alerts = ui.switch(
-                    "Email alerts", 
-                    value=config.email_alerts
                     )
 
+                    pos_underlying = ui.select(
+                        {
+                            "GLD": "SPDR Gold Shares ETF",
+                            "XAU": "Physical Gold (oz)",
+                            "GC=F": "Gold Futures",
+                        },
+                        value="GLD",
+                        label="Underlying",
+                    ).classes("w-full")
+
+                    def update_storage_cost_default() -> None:
+                        """Update storage cost defaults based on underlying selection."""
+                        underlying = str(pos_underlying.value)
+                        default_basis, default_period = get_default_storage_cost_for_underlying(underlying)
+                        if default_basis is not None:
+                            pos_storage_cost_basis.value = float(default_basis)
+                            pos_storage_cost_period.value = default_period or "annual"
+                        else:
+                            pos_storage_cost_basis.value = 0.0
+                            pos_storage_cost_period.value = "annual"
+
+                    pos_underlying.on_value_change(lambda _: update_storage_cost_default())
+
+                    pos_quantity = ui.number(
+                        "Quantity",
+                        value=100.0,
+                        min=0.0001,
+                        step=0.01,
+                    ).classes("w-full")
+
+                    pos_unit = ui.select(
+                        {"oz": "Troy Ounces", "shares": "Shares", "g": "Grams", "contracts": "Contracts"},
+                        value="oz",
+                        label="Unit",
+                    ).classes("w-full")
+
+                    pos_entry_price = ui.number(
+                        "Entry Price ($/unit)",
+                        value=2150.0,
+                        min=0.01,
+                        step=0.01,
+                    ).classes("w-full")
+
+                    with ui.row().classes("w-full items-center gap-2"):
+                        ui.label("Entry Date").classes("text-sm font-medium")
+                        pos_entry_date = (
+                            ui.date(
+                                value=date.today().isoformat(),
+                            )
+                            .classes("w-full")
+                            .props("stack-label")
+                        )
+
+                    pos_notes = ui.textarea(
+                        label="Notes (optional)",
+                        placeholder="Add notes about this position...",
+                    ).classes("w-full")
+
+                    ui.separator().classes("my-3")
+                    ui.label("Storage Costs (optional)").classes(
+                        "text-sm font-semibold text-slate-700 dark:text-slate-300"
+                    )
+                    ui.label("For physical gold (XAU), defaults to 0.12% annual vault storage.").classes(
+                        "text-xs text-slate-500 dark:text-slate-400 mb-2"
+                    )
+
+                    pos_storage_cost_basis = ui.number(
+                        "Storage cost (% per year or fixed $)",
+                        value=0.0,
+                        min=0.0,
+                        step=0.01,
+                    ).classes("w-full")
+
+                    pos_storage_cost_period = ui.select(
+                        {"annual": "Annual", "monthly": "Monthly"},
+                        value="annual",
+                        label="Cost period",
+                    ).classes("w-full")
+
+                    ui.separator().classes("my-3")
+                    ui.label("Premium & Spread (optional)").classes(
+                        "text-sm font-semibold text-slate-700 dark:text-slate-300"
+                    )
+                    ui.label("For physical gold, accounts for dealer markup and bid/ask spread.").classes(
+                        "text-xs text-slate-500 dark:text-slate-400 mb-2"
+                    )
+
+                    pos_purchase_premium = ui.number(
+                        "Purchase premium over spot (%)",
+                        value=0.0,
+                        min=0.0,
+                        max=100.0,
+                        step=0.1,
+                    ).classes("w-full")
+
+                    pos_bid_ask_spread = ui.number(
+                        "Bid/ask spread on exit (%)",
+                        value=0.0,
+                        min=0.0,
+                        max=100.0,
+                        step=0.1,
+                    ).classes("w-full")
+
+                    with ui.row().classes("w-full gap-3 mt-4"):
+                        ui.button("Cancel", on_click=lambda: add_position_dialog.close()).props("outline")
+                        ui.button("Add Position", on_click=lambda: add_position_from_form()).props("color=primary")
+
+                def add_position_from_form() -> None:
+                    """Add a new position from the form."""
+                    try:
+                        underlying = str(pos_underlying.value)
+                        storage_cost_basis_val = float(pos_storage_cost_basis.value)
+                        storage_cost_basis = (
+                            Decimal(str(storage_cost_basis_val)) if storage_cost_basis_val > 0 else None
+                        )
+                        storage_cost_period = str(pos_storage_cost_period.value) if storage_cost_basis else None
+                        purchase_premium_val = float(pos_purchase_premium.value)
+                        purchase_premium = (
+                            Decimal(str(purchase_premium_val / 100)) if purchase_premium_val > 0 else None
+                        )
+                        bid_ask_spread_val = float(pos_bid_ask_spread.value)
+                        bid_ask_spread = Decimal(str(bid_ask_spread_val / 100)) if bid_ask_spread_val > 0 else None
+
+                        new_position = Position(
+                            id=uuid4(),
+                            underlying=underlying,
+                            quantity=Decimal(str(pos_quantity.value)),
+                            unit=str(pos_unit.value),
+                            entry_price=Decimal(str(pos_entry_price.value)),
+                            entry_date=date.fromisoformat(str(pos_entry_date.value)),
+                            entry_basis_mode="weight",
+                            purchase_premium=purchase_premium,
+                            bid_ask_spread=bid_ask_spread,
+                            notes=str(pos_notes.value or ""),
+                            storage_cost_basis=storage_cost_basis,
+                            storage_cost_period=storage_cost_period,
+                        )
+                        workspace_repo.add_position(workspace_id, new_position)
+                        add_position_dialog.close()
+                        render_positions()
+                        ui.notify("Position added successfully", color="positive")
+                    except Exception as e:
+                        logger.exception("Failed to add position")
+                        ui.notify(f"Failed to add position: {e}", color="negative")
+
+                def render_positions() -> None:
+                    """Render the list of positions."""
+                    position_list_container.clear()
+                    positions = workspace_repo.list_positions(workspace_id)
+
+                    if not positions:
+                        with position_list_container:
+                            ui.label("No positions yet. Click 'Add Position' to create one.").classes(
+                                "text-sm text-slate-500 dark:text-slate-400 italic"
+                            )
+                        return
+
+                    for pos in positions:
+                        with ui.card().classes(
+                            "w-full rounded-lg border border-slate-200 bg-slate-50 p-3 dark:border-slate-700 dark:bg-slate-800"
+                        ):
+                            with ui.row().classes("w-full items-start justify-between gap-3"):
+                                with ui.column().classes("gap-1"):
+                                    ui.label(f"{pos.underlying} · {float(pos.quantity):,.4f} {pos.unit}").classes(
+                                        "text-sm font-medium text-slate-900 dark:text-slate-100"
+                                    )
+                                    ui.label(
+                                        f"Entry: ${float(pos.entry_price):,.2f}/{pos.unit} · Date: {pos.entry_date}"
+                                    ).classes("text-xs text-slate-500 dark:text-slate-400")
+                                    if pos.notes:
+                                        ui.label(pos.notes).classes("text-xs text-slate-500 dark:text-slate-400 italic")
+                                    ui.label(f"Value: ${float(pos.entry_value):,.2f}").classes(
+                                        "text-xs font-semibold text-emerald-600 dark:text-emerald-400"
+                                    )
+                                    # Show storage cost if configured
+                                    if pos.storage_cost_basis is not None:
+                                        basis_val = float(pos.storage_cost_basis)
+                                        period = pos.storage_cost_period or "annual"
+                                        if basis_val < 1:
+                                            # Percentage
+                                            storage_label = f"{basis_val:.2f}% {period} storage"
+                                        else:
+                                            # Fixed amount
+                                            storage_label = f"${basis_val:,.2f} {period} storage"
+                                        ui.label(f"Storage: {storage_label}").classes(
+                                            "text-xs text-slate-500 dark:text-slate-400"
+                                        )
+                                with ui.row().classes("gap-1"):
+                                    ui.button(
+                                        icon="delete",
+                                        on_click=lambda p=pos: remove_position(p.id),
+                                    ).props(
+                                        "flat dense color=negative size=sm"
+                                    ).classes("self-start")
+
+                def remove_position(position_id) -> None:
+                    """Remove a position."""
+                    try:
+                        workspace_repo.remove_position(workspace_id, position_id)
+                        render_positions()
+                        ui.notify("Position removed", color="positive")
+                    except Exception as e:
+                        logger.exception("Failed to remove position")
+                        ui.notify(f"Failed to remove position: {e}", color="negative")
+
+                with ui.row().classes("w-full mt-3"):
+                    ui.button("Add Position", icon="add", on_click=lambda: add_position_dialog.open()).props(
+                        "color=primary"
+                    )
+
+                # Initial render
+                render_positions()
+
+            with ui.card().classes(
+                "w-full rounded-2xl border border-slate-200 bg-white shadow-sm dark:border-slate-800 dark:bg-slate-900"
+            ):
+                ui.label("Current Alert State").classes("text-lg font-semibold text-slate-900 dark:text-slate-100")
+                with ui.row().classes("w-full items-center justify-between gap-3"):
+                    alert_state_container = ui.row().classes("items-center")
+                    email_state_label = ui.label().classes("text-xs text-slate-500 dark:text-slate-400")
+                alert_message = ui.label().classes("text-sm text-slate-600 dark:text-slate-300")
+                alert_history_column = ui.column().classes("w-full gap-2")
+
             with ui.card().classes(
                 "w-full rounded-2xl border border-slate-200 bg-white shadow-sm dark:border-slate-800 dark:bg-slate-900"
             ):
                 ui.label("Export / Import").classes("text-lg font-semibold text-slate-900 dark:text-slate-100")
-                export_format = ui.select(
+                ui.select(["json", "csv", "yaml"], value="json", label="Export format").classes("w-full")
-                    ["json", "csv", "yaml"], 
-                    value="json", 
-                    label="Export format"
-                ).classes("w-full")
                 ui.switch("Include scenario history", value=True)
                 ui.switch("Include option selections", value=True)
+                with ui.row().classes("w-full gap-3 max-sm:flex-col"):
                     ui.button("Import settings", icon="upload").props("outline color=primary")
                     ui.button("Export settings", icon="download").props("outline color=primary")
 
-        def save_settings():
+            with ui.card().classes(
-            """Save settings with validation and persistence."""
+                "w-full rounded-2xl border border-slate-200 bg-white shadow-sm dark:border-slate-800 dark:bg-slate-900"
+            ):
+                ui.label("Save Workspace Settings").classes("text-lg font-semibold text-slate-900 dark:text-slate-100")
+                status = ui.label(_save_card_status_text(last_saved_config)).classes(
+                    "text-sm text-slate-500 dark:text-slate-400"
+                )
+                ui.button("Save settings", on_click=lambda: save_settings()).props("color=primary")
+
+        def apply_entry_basis_mode() -> None:
+            mode = str(entry_basis_mode.value or "value_price")
+            if mode == "weight":
+                gold_value.props("readonly")
+                gold_ounces.props(remove="readonly")
+                derived_hint.set_text(
+                    "Gold weight is the editable basis; start value is derived from weight × entry price."
+                )
+            else:
+                gold_ounces.props("readonly")
+                gold_value.props(remove="readonly")
+                derived_hint.set_text(
+                    "Start value is the editable basis; gold weight is derived from start value ÷ entry price."
+                )
+
+        def render_alert_state() -> None:
             try:
-                # Create new config from form values
+                preview_config = build_preview_config()
-                new_config = PortfolioConfig(
+            except (ValueError, TypeError) as exc:
-                    gold_value=float(gold_value.value),
+                alert_state_container.clear()
-                    loan_amount=float(loan_amount.value),
+                with alert_state_container:
-                    margin_threshold=float(margin_threshold.value),
+                    ui.label("INVALID").classes(_alert_badge_classes("critical"))
-                    monthly_budget=float(monthly_budget.value),
+                email_state_label.set_text("Fix validation errors to preview alert state")
-                    ltv_warning=float(ltv_warning.value),
+                alert_message.set_text(str(exc))
-                    primary_source=str(primary_source.value),
+                status.set_text(_save_card_status_text(last_saved_config, invalid=True))
-                    fallback_source=str(fallback_source.value),
+                alert_history_column.clear()
-                    refresh_interval=int(refresh_interval.value),
+                return
-                    volatility_spike=float(vol_alert.value),
-                    spot_drawdown=float(price_alert.value),
-                    email_alerts=bool(email_alerts.value),
-                )
 
-                # Save to repository
+            try:
-                repo.save(new_config)
+                alert_status = alert_service.evaluate(
-                
+                    preview_config,
-                status.set_text(
+                    build_portfolio_alert_context(
-                    f"Saved: gold=${new_config.gold_value:,.0f}, "
+                        preview_config,
-                    f"loan=${new_config.loan_amount:,.0f}, "
+                        spot_price=float(preview_config.entry_price or 0.0),
-                    f"LTV={new_config.current_ltv:.1%}, "
+                        source="settings-preview",
-                    f"margin={new_config.margin_threshold:.1%}, "
+                        updated_at="",
-                    f"buffer={new_config.margin_buffer:.1%}"
+                    ),
+                    persist=False,
                 )
+            except Exception:
+                logger.exception("Settings alert preview failed for workspace %s", workspace_id)
+                alert_state_container.clear()
+                with alert_state_container:
+                    ui.label("UNAVAILABLE").classes(_alert_badge_classes("critical"))
+                email_state_label.set_text("Preview unavailable due to an internal error")
+                alert_message.set_text(
+                    "Preview unavailable due to an internal error. Last saved settings remain unchanged."
+                )
+                status.set_text(_save_card_status_text(last_saved_config, preview_config=preview_config))
+                alert_history_column.clear()
+                return
+
+            alert_state_container.clear()
+            with alert_state_container:
+                ui.label(alert_status.severity.upper()).classes(_alert_badge_classes(alert_status.severity))
+            email_state_label.set_text(
+                f"Email alerts {'enabled' if alert_status.email_alerts_enabled else 'disabled'} · Warning {alert_status.warning_threshold:.0%} · Critical {alert_status.critical_threshold:.0%}"
+            )
+            alert_message.set_text(alert_status.message)
+            status.set_text(_save_card_status_text(last_saved_config, preview_config=preview_config))
+            alert_history_column.clear()
+            if alert_status.history_notice:
+                with alert_history_column:
+                    ui.label(alert_status.history_notice).classes("text-sm text-amber-700 dark:text-amber-300")
+            elif alert_status.history:
+                for event in alert_status.history[:5]:
+                    with alert_history_column:
+                        with ui.row().classes(
+                            "w-full items-start justify-between gap-3 rounded-lg bg-slate-50 p-3 dark:bg-slate-800"
+                        ):
+                            with ui.column().classes("gap-1"):
+                                ui.label(event.message).classes(
+                                    "text-sm font-medium text-slate-900 dark:text-slate-100"
+                                )
+                                ui.label(f"Spot ${event.spot_price:,.2f} · LTV {event.ltv_ratio:.1%}").classes(
+                                    "text-xs text-slate-500 dark:text-slate-400"
+                                )
+                            ui.label(event.severity.upper()).classes(_alert_badge_classes(event.severity))
+            else:
+                with alert_history_column:
+                    ui.label("No alert history yet.").classes("text-sm text-slate-500 dark:text-slate-400")
+
+        def update_entry_basis(*_args: object) -> None:
+            nonlocal syncing_entry_basis
+            apply_entry_basis_mode()
+            if syncing_entry_basis:
+                return
+
+            price = as_positive_float(entry_price.value)
+            if price is None:
+                update_calculations()
+                return
+
+            syncing_entry_basis = True
+            try:
+                mode = str(entry_basis_mode.value or "value_price")
+                if mode == "weight":
+                    ounces = as_positive_float(gold_ounces.value)
+                    if ounces is not None:
+                        gold_value.value = round(ounces * price, 2)
+                else:
+                    start_value = as_positive_float(gold_value.value)
+                    if start_value is not None:
+                        gold_ounces.value = round(start_value / price, 6)
+            finally:
+                syncing_entry_basis = False
+
+            update_calculations()
+
+        def update_calculations(*_args: object) -> None:
+            price = as_positive_float(entry_price.value)
+            collateral_value = as_positive_float(gold_value.value)
+            ounces = as_positive_float(gold_ounces.value)
+            loan = as_non_negative_float(loan_amount.value)
+            margin = as_positive_float(margin_threshold.value)
+
+            if collateral_value is not None and collateral_value > 0 and loan is not None:
+                ltv = (loan / collateral_value) * 100
+                ltv_display.set_text(f"{ltv:.1f}%")
+                if margin is not None:
+                    buffer = (margin - loan / collateral_value) * 100
+                    buffer_display.set_text(f"{buffer:.1f}%")
+                else:
+                    buffer_display.set_text("—")
+            else:
+                ltv_display.set_text("—")
+                buffer_display.set_text("—")
+
+            if loan is not None and margin is not None and ounces is not None and ounces > 0:
+                margin_price_display.set_text(f"${loan / (margin * ounces):,.2f}/oz")
+            elif (
+                loan is not None
+                and margin is not None
+                and price is not None
+                and collateral_value is not None
+                and collateral_value > 0
+            ):
+                implied_ounces = collateral_value / price
+                margin_price_display.set_text(f"${loan / (margin * implied_ounces):,.2f}/oz")
+            else:
+                margin_price_display.set_text("—")
+
+            render_alert_state()
+
+        for element in (entry_basis_mode, entry_price, gold_value, gold_ounces):
+            element.on_value_change(update_entry_basis)
+        for element in (
+            loan_amount,
+            margin_threshold,
+            monthly_budget,
+            ltv_warning,
+            vol_alert,
+            price_alert,
+            email_alerts,
+            primary_source,
+            fallback_source,
+            refresh_interval,
+            display_mode,
+        ):
+            element.on_value_change(update_calculations)
+
+        apply_entry_basis_mode()
+        update_entry_basis()
+
+        def save_settings() -> None:
+            nonlocal last_saved_config
+            try:
+                new_config = build_preview_config()
+                workspace_repo.save_portfolio_config(workspace_id, new_config)
+                last_saved_config = new_config
+                render_alert_state()
+                status.set_text(_save_card_status_text(last_saved_config))
                 ui.notify("Settings saved successfully", color="positive")
-                
             except ValueError as e:
+                status.set_text(_save_card_status_text(last_saved_config, invalid=True))
                 ui.notify(f"Validation error: {e}", color="negative")
-            except Exception as e:
+            except Exception:
-                ui.notify(f"Failed to save: {e}", color="negative")
+                logger.exception("Failed to save settings for workspace %s", workspace_id)
-
+                status.set_text(_save_card_status_text(last_saved_config, save_failed=True))
-        with ui.row().classes("w-full items-center justify-between gap-4 mt-6"):
+                ui.notify("Failed to save settings. Check logs for details.", color="negative")
-            status = ui.label(
-                f"Current: gold=${config.gold_value:,.0f}, loan=${config.loan_amount:,.0f}, "
-                f"current LTV={config.current_ltv:.1%}"
-            ).classes("text-sm text-slate-500 dark:text-slate-400")
-            ui.button("Save settings", on_click=save_settings).props("color=primary")

app/services/alerts.py

@@ -0,0 +1,155 @@
+"""Alert evaluation and history persistence."""
+
+from __future__ import annotations
+
+import logging
+from dataclasses import dataclass
+from decimal import Decimal
+from typing import Mapping
+
+from app.domain.portfolio_math import build_alert_context
+from app.models.alerts import AlertEvent, AlertHistoryLoadError, AlertHistoryRepository, AlertStatus
+from app.models.portfolio import PortfolioConfig
+from app.services.boundary_values import boundary_decimal
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass(frozen=True, slots=True)
+class AlertEvaluationInput:
+    ltv_ratio: Decimal
+    spot_price: Decimal
+    updated_at: str
+    warning_threshold: Decimal
+    critical_threshold: Decimal
+    email_alerts_enabled: bool
+
+
+def _normalize_alert_evaluation_input(
+    config: PortfolioConfig,
+    portfolio: Mapping[str, object],
+) -> AlertEvaluationInput:
+    return AlertEvaluationInput(
+        ltv_ratio=boundary_decimal(
+            portfolio.get("ltv_ratio"),
+            field_name="portfolio.ltv_ratio",
+        ),
+        spot_price=boundary_decimal(
+            portfolio.get("spot_price"),
+            field_name="portfolio.spot_price",
+        ),
+        updated_at=str(portfolio.get("quote_updated_at", "")),
+        warning_threshold=boundary_decimal(
+            config.ltv_warning,
+            field_name="config.ltv_warning",
+        ),
+        critical_threshold=boundary_decimal(
+            config.margin_threshold,
+            field_name="config.margin_threshold",
+        ),
+        email_alerts_enabled=bool(config.email_alerts),
+    )
+
+
+def _ratio_text(value: Decimal) -> str:
+    return f"{float(value):.1%}"
+
+
+def build_portfolio_alert_context(
+    config: PortfolioConfig,
+    *,
+    spot_price: float,
+    source: str,
+    updated_at: str,
+) -> dict[str, float | str]:
+    return build_alert_context(
+        config,
+        spot_price=spot_price,
+        source=source,
+        updated_at=updated_at,
+    )
+
+
+class AlertService:
+    def __init__(self, history_path=None) -> None:
+        self.repository = AlertHistoryRepository(history_path=history_path)
+
+    def evaluate(
+        self, config: PortfolioConfig, portfolio: Mapping[str, object], *, persist: bool = True
+    ) -> AlertStatus:
+        history: list[AlertEvent] = []
+        history_unavailable = False
+        history_notice: str | None = None
+        try:
+            history = self.repository.load()
+        except AlertHistoryLoadError as exc:
+            history_unavailable = True
+            history_notice = (
+                "Alert history is temporarily unavailable due to a storage error. New alerts are not being recorded."
+            )
+            logger.warning("Alert history unavailable at %s: %s", exc.history_path, exc)
+
+        evaluation = _normalize_alert_evaluation_input(config, portfolio)
+
+        if evaluation.ltv_ratio >= evaluation.critical_threshold:
+            severity = "critical"
+            message = (
+                f"Current LTV {_ratio_text(evaluation.ltv_ratio)} is above the critical threshold of "
+                f"{_ratio_text(evaluation.critical_threshold)}."
+            )
+        elif evaluation.ltv_ratio >= evaluation.warning_threshold:
+            severity = "warning"
+            message = (
+                f"Current LTV {_ratio_text(evaluation.ltv_ratio)} is above the warning threshold of "
+                f"{_ratio_text(evaluation.warning_threshold)}."
+            )
+        else:
+            severity = "ok"
+            message = "LTV is within configured thresholds."
+
+        preview_history: list[AlertEvent] = []
+        if severity != "ok":
+            event = AlertEvent(
+                severity=severity,
+                message=message,
+                ltv_ratio=float(evaluation.ltv_ratio),
+                warning_threshold=float(evaluation.warning_threshold),
+                critical_threshold=float(evaluation.critical_threshold),
+                spot_price=float(evaluation.spot_price),
+                updated_at=evaluation.updated_at,
+                email_alerts_enabled=evaluation.email_alerts_enabled,
+            )
+            if persist:
+                if not history_unavailable and self._should_record(history, event):
+                    history.append(event)
+                    self.repository.save(history)
+            else:
+                preview_history = [event]
+
+        if not persist:
+            resolved_history = preview_history
+        elif history_unavailable:
+            resolved_history = []
+        elif severity != "ok":
+            resolved_history = list(reversed(self.repository.load()))
+        else:
+            resolved_history = history
+
+        return AlertStatus(
+            severity=severity,
+            message=message,
+            ltv_ratio=float(evaluation.ltv_ratio),
+            warning_threshold=float(evaluation.warning_threshold),
+            critical_threshold=float(evaluation.critical_threshold),
+            email_alerts_enabled=evaluation.email_alerts_enabled,
+            history=resolved_history,
+            history_unavailable=history_unavailable,
+            history_notice=history_notice,
+        )
+
+    @staticmethod
+    def _should_record(history: list[AlertEvent], event: AlertEvent) -> bool:
+        if not history:
+            return True
+        latest = history[-1]
+        return latest.severity != event.severity

app/services/backtesting/__init__.py

@@ -0,0 +1,12 @@
+"""Backtesting services and historical market-data adapters."""
+
+from .comparison import EventComparisonService
+from .historical_provider import SyntheticHistoricalProvider, YFinanceHistoricalPriceSource
+from .service import BacktestService
+
+__all__ = [
+    "BacktestService",
+    "EventComparisonService",
+    "SyntheticHistoricalProvider",
+    "YFinanceHistoricalPriceSource",
+]

app/services/backtesting/comparison.py

@@ -0,0 +1,222 @@
+from __future__ import annotations
+
+from datetime import timedelta
+
+from app.domain.backtesting_math import materialize_backtest_portfolio_state
+from app.models.backtest import (
+    BacktestPortfolioState,
+    BacktestScenario,
+    EventComparisonRanking,
+    EventComparisonReport,
+    ProviderRef,
+    TemplateRef,
+)
+from app.models.event_preset import EventPreset
+from app.services.backtesting.fixture_source import FixtureBoundSyntheticHistoricalProvider
+from app.services.backtesting.historical_provider import (
+    DailyClosePoint,
+    SyntheticHistoricalProvider,
+)
+from app.services.backtesting.input_normalization import normalize_historical_scenario_inputs
+from app.services.backtesting.service import BacktestService
+from app.services.event_presets import EventPresetService
+from app.services.strategy_templates import StrategyTemplateService
+
+
+class EventComparisonService:
+    def __init__(
+        self,
+        provider: SyntheticHistoricalProvider | FixtureBoundSyntheticHistoricalProvider | None = None,
+        template_service: StrategyTemplateService | None = None,
+        event_preset_service: EventPresetService | None = None,
+        backtest_service: BacktestService | None = None,
+    ) -> None:
+        self.provider = provider or SyntheticHistoricalProvider()
+        self.template_service = template_service or StrategyTemplateService()
+        self.event_preset_service = event_preset_service or EventPresetService()
+        self.backtest_service = backtest_service or BacktestService(
+            provider=self.provider,
+            template_service=self.template_service,
+        )
+
+    def compare_event(
+        self,
+        *,
+        preset_slug: str,
+        initial_portfolio: BacktestPortfolioState,
+        template_slugs: tuple[str, ...] | None = None,
+        provider_ref: ProviderRef | None = None,
+    ) -> EventComparisonReport:
+        preset = self.event_preset_service.get_preset(preset_slug)
+        scenario = self.materialize_scenario(
+            preset,
+            initial_portfolio=initial_portfolio,
+            template_slugs=template_slugs,
+            provider_ref=provider_ref,
+        )
+        return self._compare_materialized_event(preset=preset, scenario=scenario)
+
+    def compare_event_from_inputs(
+        self,
+        *,
+        preset_slug: str,
+        underlying_units: float,
+        loan_amount: float,
+        margin_call_ltv: float,
+        template_slugs: tuple[str, ...] | None = None,
+        currency: str = "USD",
+        cash_balance: float = 0.0,
+        financing_rate: float = 0.0,
+        provider_ref: ProviderRef | None = None,
+    ) -> EventComparisonReport:
+        normalized_inputs = normalize_historical_scenario_inputs(
+            underlying_units=underlying_units,
+            loan_amount=loan_amount,
+            margin_call_ltv=margin_call_ltv,
+            currency=currency,
+            cash_balance=cash_balance,
+            financing_rate=financing_rate,
+        )
+        preset = self.event_preset_service.get_preset(preset_slug)
+        scenario = self.preview_scenario_from_inputs(
+            preset_slug=preset_slug,
+            underlying_units=normalized_inputs.underlying_units,
+            loan_amount=normalized_inputs.loan_amount,
+            margin_call_ltv=normalized_inputs.margin_call_ltv,
+            template_slugs=template_slugs,
+            currency=normalized_inputs.currency,
+            cash_balance=normalized_inputs.cash_balance,
+            financing_rate=normalized_inputs.financing_rate,
+            provider_ref=provider_ref,
+        )
+        return self._compare_materialized_event(preset=preset, scenario=scenario)
+
+    def preview_scenario_from_inputs(
+        self,
+        *,
+        preset_slug: str,
+        underlying_units: float,
+        loan_amount: float,
+        margin_call_ltv: float,
+        template_slugs: tuple[str, ...] | None = None,
+        currency: str = "USD",
+        cash_balance: float = 0.0,
+        financing_rate: float = 0.0,
+        provider_ref: ProviderRef | None = None,
+    ) -> BacktestScenario:
+        normalized_inputs = normalize_historical_scenario_inputs(
+            underlying_units=underlying_units,
+            loan_amount=loan_amount,
+            margin_call_ltv=margin_call_ltv,
+            currency=currency,
+            cash_balance=cash_balance,
+            financing_rate=financing_rate,
+        )
+        preset = self.event_preset_service.get_preset(preset_slug)
+        history = self._load_preset_history(preset)
+        entry_spot = history[0].close
+        initial_portfolio = materialize_backtest_portfolio_state(
+            symbol=preset.symbol,
+            underlying_units=normalized_inputs.underlying_units,
+            entry_spot=entry_spot,
+            loan_amount=normalized_inputs.loan_amount,
+            margin_call_ltv=normalized_inputs.margin_call_ltv,
+            currency=normalized_inputs.currency,
+            cash_balance=normalized_inputs.cash_balance,
+            financing_rate=normalized_inputs.financing_rate,
+        )
+        return self.materialize_scenario(
+            preset,
+            initial_portfolio=initial_portfolio,
+            template_slugs=template_slugs,
+            provider_ref=provider_ref,
+            history=history,
+        )
+
+    def materialize_scenario(
+        self,
+        preset: EventPreset,
+        *,
+        initial_portfolio: BacktestPortfolioState,
+        template_slugs: tuple[str, ...] | None = None,
+        provider_ref: ProviderRef | None = None,
+        history: list[DailyClosePoint] | None = None,
+    ) -> BacktestScenario:
+        selected_template_slugs = (
+            tuple(preset.scenario_overrides.default_template_slugs) if template_slugs is None else tuple(template_slugs)
+        )
+        if not selected_template_slugs:
+            raise ValueError("Event comparison requires at least one template slug")
+
+        resolved_history = self._load_preset_history(preset) if history is None else history
+        if not resolved_history:
+            raise ValueError("Event comparison history must not be empty")
+        scenario_portfolio = materialize_backtest_portfolio_state(
+            symbol=preset.symbol,
+            underlying_units=initial_portfolio.underlying_units,
+            entry_spot=resolved_history[0].close,
+            loan_amount=initial_portfolio.loan_amount,
+            margin_call_ltv=initial_portfolio.margin_call_ltv,
+            currency=initial_portfolio.currency,
+            cash_balance=initial_portfolio.cash_balance,
+            financing_rate=initial_portfolio.financing_rate,
+        )
+        template_refs = tuple(
+            TemplateRef(slug=slug, version=self.template_service.get_template(slug).version)
+            for slug in selected_template_slugs
+        )
+        return BacktestScenario(
+            scenario_id=f"event-{preset.slug}",
+            display_name=preset.display_name,
+            symbol=preset.symbol,
+            start_date=resolved_history[0].date,
+            end_date=resolved_history[-1].date,
+            initial_portfolio=scenario_portfolio,
+            template_refs=template_refs,
+            provider_ref=provider_ref
+            or ProviderRef(
+                provider_id=self.provider.provider_id,
+                pricing_mode=self.provider.pricing_mode,
+            ),
+        )
+
+    def _compare_materialized_event(self, *, preset: EventPreset, scenario: BacktestScenario) -> EventComparisonReport:
+        run_result = self.backtest_service.run_scenario(scenario)
+        ranked_results = sorted(
+            run_result.template_results,
+            key=lambda result: (
+                result.summary_metrics.margin_call_days_hedged,
+                result.summary_metrics.max_ltv_hedged,
+                result.summary_metrics.total_hedge_cost,
+                -result.summary_metrics.end_value_hedged_net,
+                result.template_slug,
+            ),
+        )
+        rankings = tuple(
+            EventComparisonRanking(
+                rank=index,
+                template_slug=result.template_slug,
+                template_name=result.template_name,
+                survived_margin_call=not result.summary_metrics.margin_threshold_breached_hedged,
+                margin_call_days_hedged=result.summary_metrics.margin_call_days_hedged,
+                max_ltv_hedged=result.summary_metrics.max_ltv_hedged,
+                hedge_cost=result.summary_metrics.total_hedge_cost,
+                final_equity=result.summary_metrics.end_value_hedged_net,
+                result=result,
+            )
+            for index, result in enumerate(ranked_results, start=1)
+        )
+        return EventComparisonReport(
+            event_preset=preset,
+            scenario=scenario,
+            rankings=rankings,
+            run_result=run_result,
+        )
+
+    def _load_preset_history(self, preset: EventPreset) -> list[DailyClosePoint]:
+        requested_start = preset.window_start - timedelta(days=preset.scenario_overrides.lookback_days or 0)
+        requested_end = preset.window_end + timedelta(days=preset.scenario_overrides.recovery_days or 0)
+        history = self.provider.load_history(preset.symbol, requested_start, requested_end)
+        if not history:
+            raise ValueError(f"No historical prices found for event preset: {preset.slug}")
+        return history

app/services/backtesting/databento_source.py

@@ -0,0 +1,388 @@
+"""Databento historical price source for backtesting."""
+
+from __future__ import annotations
+
+import hashlib
+import json
+import logging
+from dataclasses import dataclass
+from datetime import date, timedelta
+from pathlib import Path
+from typing import TYPE_CHECKING, Any
+
+from app.services.backtesting.historical_provider import DailyClosePoint
+
+if TYPE_CHECKING:
+    import databento as db
+    import pandas as pd
+else:
+    db = None
+    pd = None
+
+DATABENTO_AVAILABLE = False
+
+logger = logging.getLogger(__name__)
+
+# Try to import databento, gracefully degrade if not available
+try:
+    import databento as _db
+    import pandas as _pd
+
+    db = _db
+    pd = _pd
+    DATABENTO_AVAILABLE = True
+except ImportError:
+    pass
+
+
+@dataclass
+class DatabentoSourceConfig:
+    """Configuration for Databento data source."""
+
+    api_key: str | None = None  # Falls back to DATABENTO_API_KEY env var
+    cache_dir: Path = Path(".cache/databento")
+    dataset: str = "XNAS.BASIC"
+    schema: str = "ohlcv-1d"
+    stype_in: str = "raw_symbol"
+
+    # Re-download threshold
+    max_cache_age_days: int = 30
+
+    def __post_init__(self) -> None:
+        # Ensure cache_dir is a Path
+        if isinstance(self.cache_dir, str):
+            object.__setattr__(self, "cache_dir", Path(self.cache_dir))
+
+
+@dataclass(frozen=True)
+class DatabentoCacheKey:
+    """Cache key for Databento data."""
+
+    dataset: str
+    symbol: str
+    schema: str
+    start_date: date
+    end_date: date
+
+    def cache_path(self, cache_dir: Path) -> Path:
+        key_str = f"{self.dataset}_{self.symbol}_{self.schema}_{self.start_date}_{self.end_date}"
+        key_hash = hashlib.sha256(key_str.encode()).hexdigest()[:16]
+        return cache_dir / f"dbn_{key_hash}.parquet"
+
+    def metadata_path(self, cache_dir: Path) -> Path:
+        key_str = f"{self.dataset}_{self.symbol}_{self.schema}_{self.start_date}_{self.end_date}"
+        key_hash = hashlib.sha256(key_str.encode()).hexdigest()[:16]
+        return cache_dir / f"dbn_{key_hash}_meta.json"
+
+
+class DatabentoHistoricalPriceSource:
+    """Databento-based historical price source for backtesting.
+
+    This provider fetches historical daily OHLCV data from Databento's API
+    and caches it locally to minimize API calls and costs.
+
+    Key features:
+    - Smart caching with configurable age threshold
+    - Cost estimation before fetching
+    - Symbol-to-dataset resolution (GLD→XNAS.BASIC, GC=F→GLBX.MDP3)
+    - Parquet storage for fast loading
+
+    Example usage:
+        source = DatabentoHistoricalPriceSource()
+        prices = source.load_daily_closes("GLD", date(2024, 1, 1), date(2024, 1, 31))
+    """
+
+    def __init__(self, config: DatabentoSourceConfig | None = None) -> None:
+        if not DATABENTO_AVAILABLE:
+            raise RuntimeError("databento package required: pip install databento>=0.30.0")
+
+        self.config = config or DatabentoSourceConfig()
+        self.config.cache_dir.mkdir(parents=True, exist_ok=True)
+        self._client: Any = None  # db.Historical
+
+    @property
+    def client(self) -> Any:
+        """Get or create Databento client."""
+        if self._client is None:
+            if db is None:
+                raise RuntimeError("databento package not installed")
+            self._client = db.Historical(key=self.config.api_key)
+        return self._client
+
+    def _load_from_cache(self, key: DatabentoCacheKey) -> list[DailyClosePoint] | None:
+        """Load cached data if available and fresh."""
+        cache_file = key.cache_path(self.config.cache_dir)
+        meta_file = key.metadata_path(self.config.cache_dir)
+
+        if not cache_file.exists() or not meta_file.exists():
+            return None
+
+        try:
+            with open(meta_file) as f:
+                meta = json.load(f)
+
+            # Check dataset and symbol match (for cache invalidation)
+            if meta.get("dataset") != key.dataset or meta.get("symbol") != key.symbol:
+                return None
+
+            cache_age = (date.today() - date.fromisoformat(meta["download_date"])).days
+            if cache_age > self.config.max_cache_age_days:
+                return None
+
+            if meta.get("start_date") != key.start_date.isoformat() or meta.get("end_date") != key.end_date.isoformat():
+                return None
+
+            if meta.get("dataset") != key.dataset or meta.get("symbol") != key.symbol:
+                return None
+
+            # Load parquet and convert
+
+            df = pd.read_parquet(cache_file)
+            return self._df_to_daily_points(df)
+        except Exception:
+            return None
+
+    def _save_to_cache(self, key: DatabentoCacheKey, df: Any, cost_usd: float = 0.0) -> None:
+        """Save data to cache."""
+        if pd is None:
+            return
+
+        cache_file = key.cache_path(self.config.cache_dir)
+        meta_file = key.metadata_path(self.config.cache_dir)
+
+        df.to_parquet(cache_file, index=False)
+
+        meta = {
+            "download_date": date.today().isoformat(),
+            "dataset": key.dataset,
+            "symbol": key.symbol,
+            "schema": key.schema,
+            "start_date": key.start_date.isoformat(),
+            "end_date": key.end_date.isoformat(),
+            "rows": len(df),
+            "cost_usd": cost_usd,
+        }
+        with open(meta_file, "w") as f:
+            json.dump(meta, f, indent=2)
+
+    def _fetch_from_databento(self, key: DatabentoCacheKey) -> Any:
+        """Fetch data from Databento API."""
+        data = self.client.timeseries.get_range(
+            dataset=key.dataset,
+            symbols=key.symbol,
+            schema=key.schema,
+            start=key.start_date.isoformat(),
+            end=(key.end_date + timedelta(days=1)).isoformat(),  # Exclusive end
+            stype_in=self.config.stype_in,
+        )
+        return data.to_df()
+
+    def _df_to_daily_points(self, df: Any) -> list[DailyClosePoint]:
+        """Convert DataFrame to DailyClosePoint list with OHLC data."""
+        from app.services.backtesting.historical_provider import DailyClosePoint
+
+        if pd is None:
+            return []
+
+        def parse_price(raw_val: Any) -> float | None:
+            """Parse Databento price (int64 scaled by 1e9)."""
+            if raw_val is None or (isinstance(raw_val, float) and pd.isna(raw_val)):
+                return None
+            if isinstance(raw_val, (int, float)):
+                return float(raw_val) / 1e9 if raw_val > 1e9 else float(raw_val)
+            return float(raw_val) if raw_val else None
+
+        points = []
+        for idx, row in df.iterrows():
+            # Databento ohlcv schema has ts_event as timestamp
+            ts = row.get("ts_event", row.get("ts_recv", idx))
+            if hasattr(ts, "date"):
+                row_date = ts.date()
+            else:
+                # Parse ISO date string
+                ts_str = str(ts)
+                row_date = date.fromisoformat(ts_str[:10])
+
+            close = parse_price(row.get("close"))
+            low = parse_price(row.get("low"))
+            high = parse_price(row.get("high"))
+            open_price = parse_price(row.get("open"))
+
+            if close and close > 0:
+                points.append(
+                    DailyClosePoint(
+                        date=row_date,
+                        close=close,
+                        low=low,
+                        high=high,
+                        open=open_price,
+                    )
+                )
+
+        return sorted(points, key=lambda p: p.date)
+
+    from app.services.backtesting.historical_provider import DailyClosePoint
+
+    def load_daily_closes(self, symbol: str, start_date: date, end_date: date) -> list[DailyClosePoint]:
+        """Load daily closing prices from Databento (with caching).
+
+        Args:
+            symbol: Trading symbol (GLD, GC=F, XAU)
+            start_date: Inclusive start date
+            end_date: Inclusive end date
+
+        Returns:
+            List of DailyClosePoint sorted by date
+        """
+        # Map symbols to datasets
+        dataset = self._resolve_dataset(symbol)
+        databento_symbol = self._resolve_symbol(symbol)
+
+        key = DatabentoCacheKey(
+            dataset=dataset,
+            symbol=databento_symbol,
+            schema=self.config.schema,
+            start_date=start_date,
+            end_date=end_date,
+        )
+
+        # Try cache first
+        cached = self._load_from_cache(key)
+        if cached is not None:
+            return cached
+
+        # Fetch from Databento
+        df = self._fetch_from_databento(key)
+
+        # Get cost estimate (approximate)
+        try:
+            cost_usd = self.get_cost_estimate(symbol, start_date, end_date)
+        except Exception:
+            cost_usd = 0.0
+
+        # Cache results
+        self._save_to_cache(key, df, cost_usd)
+
+        return self._df_to_daily_points(df)
+
+    def _resolve_dataset(self, symbol: str) -> str:
+        """Resolve symbol to Databento dataset."""
+        symbol_upper = symbol.upper()
+        if symbol_upper in ("GLD", "GLDM", "IAU"):
+            return "XNAS.BASIC"  # ETFs on Nasdaq
+        elif symbol_upper in ("GC=F", "GC", "GOLD"):
+            return "GLBX.MDP3"  # CME gold futures
+        elif symbol_upper == "XAU":
+            return "XNAS.BASIC"  # Treat as GLD proxy
+        else:
+            return self.config.dataset  # Use configured default
+
+    def _resolve_symbol(self, symbol: str) -> str:
+        """Resolve vault-dash symbol to Databento symbol."""
+        symbol_upper = symbol.upper()
+        if symbol_upper == "XAU":
+            return "GLD"  # Proxy XAU via GLD prices
+        elif symbol_upper == "GC=F":
+            return "GC"  # Use parent symbol for continuous contracts
+        return symbol_upper
+
+    def get_cost_estimate(self, symbol: str, start_date: date, end_date: date) -> float:
+        """Estimate cost in USD for a data request.
+
+        Args:
+            symbol: Trading symbol
+            start_date: Start date
+            end_date: End date
+
+        Returns:
+            Estimated cost in USD
+        """
+        dataset = self._resolve_dataset(symbol)
+        databento_symbol = self._resolve_symbol(symbol)
+
+        try:
+            cost = self.client.metadata.get_cost(
+                dataset=dataset,
+                symbols=databento_symbol,
+                schema=self.config.schema,
+                start=start_date.isoformat(),
+                end=(end_date + timedelta(days=1)).isoformat(),
+            )
+            return float(cost)
+        except Exception:
+            return 0.0  # Return 0 if cost estimation fails
+
+    def get_available_range(self, symbol: str) -> tuple[date | None, date | None]:
+        """Get the available date range for a symbol from Databento.
+
+        Args:
+            symbol: Trading symbol
+
+        Returns:
+            Tuple of (start_date, end_date) or (None, None) if unavailable
+        """
+        # Note: Databento availability depends on the dataset
+        # For now, return None to indicate we should try fetching
+        return None, None
+
+    def get_cache_stats(self) -> dict[str, Any]:
+        """Get cache statistics."""
+        cache_dir = self.config.cache_dir
+        if not cache_dir.exists():
+            return {"status": "empty", "entries": [], "file_count": 0, "total_size_bytes": 0}
+
+        entries = []
+        total_size = 0
+        file_count = 0
+
+        for meta_file in cache_dir.glob("*_meta.json"):
+            try:
+                with open(meta_file) as f:
+                    meta = json.load(f)
+                entries.append(
+                    {
+                        "symbol": meta.get("symbol"),
+                        "dataset": meta.get("dataset"),
+                        "start_date": meta.get("start_date"),
+                        "end_date": meta.get("end_date"),
+                        "download_date": meta.get("download_date"),
+                        "rows": meta.get("rows"),
+                        "cost_usd": meta.get("cost_usd"),
+                    }
+                )
+                total_size += meta_file.stat().st_size
+                file_count += 1
+            except Exception:
+                continue
+
+        # Count parquet files too
+        for parquet_file in cache_dir.glob("dbn_*.parquet"):
+            total_size += parquet_file.stat().st_size
+            file_count += 1
+
+        return {
+            "status": "populated" if entries else "empty",
+            "entries": entries,
+            "file_count": file_count,
+            "total_size_bytes": total_size,
+        }
+
+    def clear_cache(self) -> int:
+        """Clear all cache files.
+
+        Returns:
+            Number of files deleted.
+        """
+        cache_dir = self.config.cache_dir
+        if not cache_dir.exists():
+            return 0
+
+        count = 0
+        for cache_file in cache_dir.glob("dbn_*.parquet"):
+            cache_file.unlink()
+            count += 1
+        for meta_file in cache_dir.glob("dbn_*_meta.json"):
+            meta_file.unlink()
+            count += 1
+
+        return count

app/services/backtesting/fixture_source.py

@@ -0,0 +1,98 @@
+from __future__ import annotations
+
+from dataclasses import dataclass
+from datetime import date
+from enum import StrEnum
+from typing import Any
+
+from app.services.backtesting.historical_provider import DailyClosePoint, SyntheticHistoricalProvider
+
+SEEDED_GLD_2024_FIXTURE_HISTORY: tuple[DailyClosePoint, ...] = (
+    DailyClosePoint(date=date(2024, 1, 2), close=100.0),
+    DailyClosePoint(date=date(2024, 1, 3), close=96.0),
+    DailyClosePoint(date=date(2024, 1, 4), close=92.0),
+    DailyClosePoint(date=date(2024, 1, 5), close=88.0),
+    DailyClosePoint(date=date(2024, 1, 8), close=85.0),
+)
+
+
+class WindowPolicy(StrEnum):
+    EXACT = "exact"
+    BOUNDED = "bounded"
+
+
+@dataclass(frozen=True)
+class SharedHistoricalFixtureSource:
+    feature_label: str
+    supported_symbol: str
+    history: tuple[DailyClosePoint, ...]
+    window_policy: WindowPolicy
+
+    @property
+    def start_date(self) -> date:
+        return self.history[0].date
+
+    @property
+    def end_date(self) -> date:
+        return self.history[-1].date
+
+    def load_daily_closes(self, symbol: str, start_date: date, end_date: date) -> list[DailyClosePoint]:
+        if start_date > end_date:
+            raise ValueError("start_date must be on or before end_date")
+        normalized_symbol = symbol.strip().upper()
+        if normalized_symbol != self.supported_symbol.strip().upper():
+            raise ValueError(
+                f"{self.feature_label} deterministic fixture data only supports {self.supported_symbol} on this page"
+            )
+        if self.window_policy is WindowPolicy.EXACT:
+            if start_date != self.start_date or end_date != self.end_date:
+                raise ValueError(
+                    f"{self.feature_label} deterministic fixture data only supports {self.supported_symbol} "
+                    f"on the seeded {self.start_date.isoformat()} through {self.end_date.isoformat()} window"
+                )
+        else:
+            if start_date < self.start_date or end_date > self.end_date:
+                raise ValueError(
+                    f"{self.feature_label} deterministic fixture data only supports the seeded "
+                    f"{self.start_date.isoformat()} through {self.end_date.isoformat()} window. "
+                    f"For dates outside this range, please use Databento or Yahoo Finance data source."
+                )
+        return [point for point in self.history if start_date <= point.date <= end_date]
+
+
+class FixtureBoundSyntheticHistoricalProvider:
+    def __init__(self, base_provider: SyntheticHistoricalProvider, source: SharedHistoricalFixtureSource) -> None:
+        self.base_provider = base_provider
+        self.source = source
+
+    def load_history(self, symbol: str, start_date: date, end_date: date) -> list[DailyClosePoint]:
+        rows = self.source.load_daily_closes(symbol, start_date, end_date)
+        return sorted(rows, key=lambda row: row.date)
+
+    def __getattr__(self, name: str) -> Any:
+        return getattr(self.base_provider, name)
+
+
+def build_backtest_ui_fixture_source() -> SharedHistoricalFixtureSource:
+    return SharedHistoricalFixtureSource(
+        feature_label="BT-001A",
+        supported_symbol="GLD",
+        history=SEEDED_GLD_2024_FIXTURE_HISTORY,
+        window_policy=WindowPolicy.BOUNDED,
+    )
+
+
+def build_event_comparison_fixture_source() -> SharedHistoricalFixtureSource:
+    return SharedHistoricalFixtureSource(
+        feature_label="BT-003A",
+        supported_symbol="GLD",
+        history=SEEDED_GLD_2024_FIXTURE_HISTORY,
+        window_policy=WindowPolicy.BOUNDED,
+    )
+
+
+def bind_fixture_source(
+    base_provider: SyntheticHistoricalProvider,
+    source: SharedHistoricalFixtureSource,
+) -> FixtureBoundSyntheticHistoricalProvider:
+    return FixtureBoundSyntheticHistoricalProvider(base_provider=base_provider, source=source)

app/services/backtesting/historical_provider.py

@@ -0,0 +1,560 @@
+from __future__ import annotations
+
+from dataclasses import dataclass
+from datetime import date, timedelta
+from math import isfinite
+from typing import Protocol, cast
+
+from app.models.backtest import ProviderRef
+
+try:
+    import yfinance as yf
+except ImportError:  # pragma: no cover - optional in tests
+    yf = None
+
+from app.core.pricing.black_scholes import BlackScholesInputs, OptionType, black_scholes_price_and_greeks
+from app.models.strategy_template import TemplateLeg
+
+
+@dataclass(frozen=True)
+class DailyClosePoint:
+    date: date
+    close: float
+    low: float | None = None  # Day's low for margin call evaluation
+    high: float | None = None  # Day's high
+    open: float | None = None  # Day's open
+
+    def __post_init__(self) -> None:
+        if self.close <= 0:
+            raise ValueError("close must be positive")
+        if self.low is not None and self.low <= 0:
+            raise ValueError("low must be positive")
+        if self.high is not None and self.high <= 0:
+            raise ValueError("high must be positive")
+        if self.open is not None and self.open <= 0:
+            raise ValueError("open must be positive")
+
+
+@dataclass(frozen=True)
+class SyntheticOptionQuote:
+    position_id: str
+    leg_id: str
+    spot: float
+    strike: float
+    expiry: date
+    quantity: float
+    mark: float
+
+    def __post_init__(self) -> None:
+        for field_name in ("position_id", "leg_id"):
+            value = getattr(self, field_name)
+            if not isinstance(value, str) or not value:
+                raise ValueError(f"{field_name} is required")
+        for field_name in ("spot", "strike", "quantity", "mark"):
+            value = getattr(self, field_name)
+            if not isinstance(value, (int, float)) or isinstance(value, bool) or not isfinite(float(value)):
+                raise TypeError(f"{field_name} must be a finite number")
+        if self.spot <= 0:
+            raise ValueError("spot must be positive")
+        if self.strike <= 0:
+            raise ValueError("strike must be positive")
+        if self.quantity <= 0:
+            raise ValueError("quantity must be positive")
+        if self.mark < 0:
+            raise ValueError("mark must be non-negative")
+
+
+@dataclass(frozen=True)
+class DailyOptionSnapshot:
+    contract_key: str
+    symbol: str
+    snapshot_date: date
+    expiry: date
+    option_type: str
+    strike: float
+    mid: float
+
+    def __post_init__(self) -> None:
+        if not self.contract_key:
+            raise ValueError("contract_key is required")
+        if not self.symbol:
+            raise ValueError("symbol is required")
+        if self.option_type not in {"put", "call"}:
+            raise ValueError("unsupported option_type")
+        if self.strike <= 0:
+            raise ValueError("strike must be positive")
+        if self.mid < 0:
+            raise ValueError("mid must be non-negative")
+
+
+@dataclass
+class HistoricalOptionPosition:
+    position_id: str
+    leg_id: str
+    contract_key: str
+    option_type: str
+    strike: float
+    expiry: date
+    quantity: float
+    entry_price: float
+    current_mark: float
+    last_mark_date: date
+    source_snapshot_date: date
+
+    def __post_init__(self) -> None:
+        for field_name in ("position_id", "leg_id", "contract_key"):
+            value = getattr(self, field_name)
+            if not isinstance(value, str) or not value:
+                raise ValueError(f"{field_name} is required")
+        if self.option_type not in {"put", "call"}:
+            raise ValueError("unsupported option_type")
+        for field_name in ("strike", "quantity", "entry_price", "current_mark"):
+            value = getattr(self, field_name)
+            if not isinstance(value, (int, float)) or isinstance(value, bool) or not isfinite(float(value)):
+                raise TypeError(f"{field_name} must be a finite number")
+        if self.strike <= 0:
+            raise ValueError("strike must be positive")
+        if self.quantity <= 0:
+            raise ValueError("quantity must be positive")
+        if self.entry_price < 0:
+            raise ValueError("entry_price must be non-negative")
+        if self.current_mark < 0:
+            raise ValueError("current_mark must be non-negative")
+
+
+@dataclass(frozen=True)
+class HistoricalOptionMark:
+    contract_key: str
+    mark: float
+    source: str
+    is_active: bool
+    realized_cashflow: float = 0.0
+    warning: str | None = None
+
+    def __post_init__(self) -> None:
+        if not self.contract_key:
+            raise ValueError("contract_key is required")
+        for field_name in ("mark", "realized_cashflow"):
+            value = getattr(self, field_name)
+            if not isinstance(value, (int, float)) or isinstance(value, bool) or not isfinite(float(value)):
+                raise TypeError(f"{field_name} must be a finite number")
+        if self.mark < 0:
+            raise ValueError("mark must be non-negative")
+        if self.realized_cashflow < 0:
+            raise ValueError("realized_cashflow must be non-negative")
+
+
+class HistoricalPriceSource(Protocol):
+    def load_daily_closes(self, symbol: str, start_date: date, end_date: date) -> list[DailyClosePoint]:
+        raise NotImplementedError
+
+
+class OptionSnapshotSource(Protocol):
+    def load_option_chain(self, symbol: str, snapshot_date: date) -> list[DailyOptionSnapshot]:
+        raise NotImplementedError
+
+
+class BacktestHistoricalProvider(Protocol):
+    provider_id: str
+    pricing_mode: str
+
+    def load_history(self, symbol: str, start_date: date, end_date: date) -> list[DailyClosePoint]:
+        raise NotImplementedError
+
+    def validate_provider_ref(self, provider_ref: ProviderRef) -> None:
+        raise NotImplementedError
+
+    def open_position(
+        self,
+        *,
+        symbol: str,
+        leg: TemplateLeg,
+        position_id: str,
+        quantity: float,
+        as_of_date: date,
+        spot: float,
+        trading_days: list[DailyClosePoint],
+    ) -> HistoricalOptionPosition:
+        raise NotImplementedError
+
+    def mark_position(
+        self,
+        position: HistoricalOptionPosition,
+        *,
+        symbol: str,
+        as_of_date: date,
+        spot: float,
+    ) -> HistoricalOptionMark:
+        raise NotImplementedError
+
+
+class YFinanceHistoricalPriceSource:
+    @staticmethod
+    def _normalize_daily_close_row(
+        *, row_date: object, close: object, low: object = None, high: object = None, open_price: object = None
+    ) -> DailyClosePoint | None:
+        if close is None:
+            return None
+        if not hasattr(row_date, "date"):
+            raise TypeError(f"historical row date must support .date(), got {type(row_date)!r}")
+        if isinstance(close, (int, float)):
+            normalized_close = float(close)
+        else:
+            raise TypeError(f"close must be numeric, got {type(close)!r}")
+        if not isfinite(normalized_close):
+            raise ValueError("historical close must be finite")
+
+        # Parse optional OHLC fields
+        def parse_optional(val: object) -> float | None:
+            if val is None:
+                return None
+            if isinstance(val, (int, float)):
+                result = float(val)
+                return result if isfinite(result) and result > 0 else None
+            return None
+
+        return DailyClosePoint(
+            date=row_date.date(),
+            close=normalized_close,
+            low=parse_optional(low),
+            high=parse_optional(high),
+            open=parse_optional(open_price),
+        )
+
+    def load_daily_closes(self, symbol: str, start_date: date, end_date: date) -> list[DailyClosePoint]:
+        if yf is None:
+            raise RuntimeError("yfinance is required to load historical backtest prices")
+        ticker = yf.Ticker(symbol)
+        inclusive_end_date = end_date + timedelta(days=1)
+        history = ticker.history(start=start_date.isoformat(), end=inclusive_end_date.isoformat(), interval="1d")
+        rows: list[DailyClosePoint] = []
+        for index, row in history.iterrows():
+            point = self._normalize_daily_close_row(
+                row_date=index,
+                close=row.get("Close"),
+                low=row.get("Low"),
+                high=row.get("High"),
+                open_price=row.get("Open"),
+            )
+            if point is not None:
+                rows.append(point)
+        return rows
+
+
+class SyntheticHistoricalProvider:
+    provider_id = "synthetic_v1"
+    pricing_mode = "synthetic_bs_mid"
+
+    def __init__(
+        self,
+        source: HistoricalPriceSource | None = None,
+        implied_volatility: float = 0.16,
+        risk_free_rate: float = 0.045,
+    ) -> None:
+        if implied_volatility <= 0:
+            raise ValueError("implied_volatility must be positive")
+        self.source = source or YFinanceHistoricalPriceSource()
+        self.implied_volatility = implied_volatility
+        self.risk_free_rate = risk_free_rate
+
+    def load_history(self, symbol: str, start_date: date, end_date: date) -> list[DailyClosePoint]:
+        rows = self.source.load_daily_closes(symbol, start_date, end_date)
+        filtered = [row for row in rows if start_date <= row.date <= end_date]
+        return sorted(filtered, key=lambda row: row.date)
+
+    def validate_provider_ref(self, provider_ref: ProviderRef) -> None:
+        if provider_ref.provider_id != self.provider_id or provider_ref.pricing_mode != self.pricing_mode:
+            raise ValueError(
+                "Unsupported provider/pricing combination for synthetic MVP engine: "
+                f"{provider_ref.provider_id}/{provider_ref.pricing_mode}"
+            )
+
+    def resolve_expiry(self, trading_days: list[DailyClosePoint], as_of_date: date, target_expiry_days: int) -> date:
+        target_date = date.fromordinal(as_of_date.toordinal() + target_expiry_days)
+        for day in trading_days:
+            if day.date >= target_date:
+                return day.date
+        return target_date
+
+    def open_position(
+        self,
+        *,
+        symbol: str,
+        leg: TemplateLeg,
+        position_id: str,
+        quantity: float,
+        as_of_date: date,
+        spot: float,
+        trading_days: list[DailyClosePoint],
+    ) -> HistoricalOptionPosition:
+        expiry = self.resolve_expiry(trading_days, as_of_date, leg.target_expiry_days)
+        strike = spot * leg.strike_rule.value
+        quote = self.price_option(
+            position_id=position_id,
+            leg=leg,
+            spot=spot,
+            strike=strike,
+            expiry=expiry,
+            quantity=quantity,
+            valuation_date=as_of_date,
+        )
+        return HistoricalOptionPosition(
+            position_id=position_id,
+            leg_id=leg.leg_id,
+            contract_key=f"{symbol}-{expiry.isoformat()}-{leg.option_type}-{strike:.4f}",
+            option_type=leg.option_type,
+            strike=strike,
+            expiry=expiry,
+            quantity=quantity,
+            entry_price=quote.mark,
+            current_mark=quote.mark,
+            last_mark_date=as_of_date,
+            source_snapshot_date=as_of_date,
+        )
+
+    def mark_position(
+        self,
+        position: HistoricalOptionPosition,
+        *,
+        symbol: str,
+        as_of_date: date,
+        spot: float,
+    ) -> HistoricalOptionMark:
+        if as_of_date >= position.expiry:
+            intrinsic = self.intrinsic_value(option_type=position.option_type, spot=spot, strike=position.strike)
+            return HistoricalOptionMark(
+                contract_key=position.contract_key,
+                mark=0.0,
+                source="intrinsic_expiry",
+                is_active=False,
+                realized_cashflow=intrinsic * position.quantity,
+            )
+
+        quote = self.price_option_by_type(
+            position_id=position.position_id,
+            leg_id=position.leg_id,
+            option_type=position.option_type,
+            spot=spot,
+            strike=position.strike,
+            expiry=position.expiry,
+            quantity=position.quantity,
+            valuation_date=as_of_date,
+        )
+        position.current_mark = quote.mark
+        position.last_mark_date = as_of_date
+        return HistoricalOptionMark(
+            contract_key=position.contract_key,
+            mark=quote.mark,
+            source="synthetic_bs_mid",
+            is_active=True,
+        )
+
+    def price_option(
+        self,
+        *,
+        position_id: str,
+        leg: TemplateLeg,
+        spot: float,
+        strike: float,
+        expiry: date,
+        quantity: float,
+        valuation_date: date,
+    ) -> SyntheticOptionQuote:
+        return self.price_option_by_type(
+            position_id=position_id,
+            leg_id=leg.leg_id,
+            option_type=leg.option_type,
+            spot=spot,
+            strike=strike,
+            expiry=expiry,
+            quantity=quantity,
+            valuation_date=valuation_date,
+        )
+
+    def price_option_by_type(
+        self,
+        *,
+        position_id: str,
+        leg_id: str,
+        option_type: str,
+        spot: float,
+        strike: float,
+        expiry: date,
+        quantity: float,
+        valuation_date: date,
+    ) -> SyntheticOptionQuote:
+        remaining_days = max(1, expiry.toordinal() - valuation_date.toordinal())
+        mark = black_scholes_price_and_greeks(
+            BlackScholesInputs(
+                spot=spot,
+                strike=strike,
+                time_to_expiry=remaining_days / 365.0,
+                risk_free_rate=self.risk_free_rate,
+                volatility=self.implied_volatility,
+                option_type=cast(OptionType, option_type),
+                valuation_date=valuation_date,
+            )
+        ).price
+        return SyntheticOptionQuote(
+            position_id=position_id,
+            leg_id=leg_id,
+            spot=spot,
+            strike=strike,
+            expiry=expiry,
+            quantity=quantity,
+            mark=mark,
+        )
+
+    @staticmethod
+    def intrinsic_value(*, option_type: str, spot: float, strike: float) -> float:
+        if option_type == "put":
+            return max(strike - spot, 0.0)
+        if option_type == "call":
+            return max(spot - strike, 0.0)
+        raise ValueError(f"Unsupported option type: {option_type}")
+
+
+class EmptyOptionSnapshotSource:
+    def load_option_chain(self, symbol: str, snapshot_date: date) -> list[DailyOptionSnapshot]:
+        return []
+
+
+class DailyOptionsSnapshotProvider:
+    provider_id = "daily_snapshots_v1"
+    pricing_mode = "snapshot_mid"
+
+    def __init__(
+        self,
+        price_source: HistoricalPriceSource | None = None,
+        snapshot_source: OptionSnapshotSource | None = None,
+    ) -> None:
+        self.price_source = price_source or YFinanceHistoricalPriceSource()
+        self.snapshot_source = snapshot_source or EmptyOptionSnapshotSource()
+
+    def load_history(self, symbol: str, start_date: date, end_date: date) -> list[DailyClosePoint]:
+        rows = self.price_source.load_daily_closes(symbol, start_date, end_date)
+        filtered = [row for row in rows if start_date <= row.date <= end_date]
+        return sorted(filtered, key=lambda row: row.date)
+
+    def validate_provider_ref(self, provider_ref: ProviderRef) -> None:
+        if provider_ref.provider_id != self.provider_id or provider_ref.pricing_mode != self.pricing_mode:
+            raise ValueError(
+                "Unsupported provider/pricing combination for historical snapshot engine: "
+                f"{provider_ref.provider_id}/{provider_ref.pricing_mode}"
+            )
+
+    def open_position(
+        self,
+        *,
+        symbol: str,
+        leg: TemplateLeg,
+        position_id: str,
+        quantity: float,
+        as_of_date: date,
+        spot: float,
+        trading_days: list[DailyClosePoint],
+    ) -> HistoricalOptionPosition:
+        del trading_days  # selection must use only the entry-day snapshot, not future state
+        selected_snapshot = self._select_entry_snapshot(symbol=symbol, leg=leg, as_of_date=as_of_date, spot=spot)
+        return HistoricalOptionPosition(
+            position_id=position_id,
+            leg_id=leg.leg_id,
+            contract_key=selected_snapshot.contract_key,
+            option_type=selected_snapshot.option_type,
+            strike=selected_snapshot.strike,
+            expiry=selected_snapshot.expiry,
+            quantity=quantity,
+            entry_price=selected_snapshot.mid,
+            current_mark=selected_snapshot.mid,
+            last_mark_date=as_of_date,
+            source_snapshot_date=as_of_date,
+        )
+
+    def mark_position(
+        self,
+        position: HistoricalOptionPosition,
+        *,
+        symbol: str,
+        as_of_date: date,
+        spot: float,
+    ) -> HistoricalOptionMark:
+        if as_of_date >= position.expiry:
+            intrinsic = SyntheticHistoricalProvider.intrinsic_value(
+                option_type=position.option_type,
+                spot=spot,
+                strike=position.strike,
+            )
+            return HistoricalOptionMark(
+                contract_key=position.contract_key,
+                mark=0.0,
+                source="intrinsic_expiry",
+                is_active=False,
+                realized_cashflow=intrinsic * position.quantity,
+            )
+
+        exact_snapshot = next(
+            (
+                snapshot
+                for snapshot in self.snapshot_source.load_option_chain(symbol, as_of_date)
+                if snapshot.contract_key == position.contract_key
+            ),
+            None,
+        )
+        if exact_snapshot is not None:
+            position.current_mark = exact_snapshot.mid
+            position.last_mark_date = as_of_date
+            return HistoricalOptionMark(
+                contract_key=position.contract_key,
+                mark=exact_snapshot.mid,
+                source="snapshot_mid",
+                is_active=True,
+            )
+
+        if position.current_mark < 0:
+            raise ValueError(f"Missing historical mark for {position.contract_key} on {as_of_date.isoformat()}")
+        return HistoricalOptionMark(
+            contract_key=position.contract_key,
+            mark=position.current_mark,
+            source="carry_forward",
+            is_active=True,
+            warning=(
+                f"Missing historical mark for {position.contract_key} on {as_of_date.isoformat()}; "
+                f"carrying forward prior mark from {position.last_mark_date.isoformat()}."
+            ),
+        )
+
+    def _select_entry_snapshot(
+        self,
+        *,
+        symbol: str,
+        leg: TemplateLeg,
+        as_of_date: date,
+        spot: float,
+    ) -> DailyOptionSnapshot:
+        target_expiry = date.fromordinal(as_of_date.toordinal() + leg.target_expiry_days)
+        target_strike = spot * leg.strike_rule.value
+        chain = [
+            snapshot
+            for snapshot in self.snapshot_source.load_option_chain(symbol, as_of_date)
+            if snapshot.symbol.strip().upper() == symbol.strip().upper() and snapshot.option_type == leg.option_type
+        ]
+        eligible_expiries = [snapshot for snapshot in chain if snapshot.expiry >= target_expiry]
+        if not eligible_expiries:
+            raise ValueError(
+                f"No eligible historical option snapshots found for {symbol} on {as_of_date.isoformat()} "
+                f"at or beyond target expiry {target_expiry.isoformat()}"
+            )
+        selected_expiry = min(
+            eligible_expiries,
+            key=lambda snapshot: ((snapshot.expiry - target_expiry).days, snapshot.expiry),
+        ).expiry
+        expiry_matches = [snapshot for snapshot in eligible_expiries if snapshot.expiry == selected_expiry]
+        return min(
+            expiry_matches, key=lambda snapshot: self._strike_sort_key(snapshot.strike, target_strike, leg.option_type)
+        )
+
+    @staticmethod
+    def _strike_sort_key(strike: float, target_strike: float, option_type: str) -> tuple[float, float]:
+        if option_type == "put":
+            return (abs(strike - target_strike), -strike)
+        return (abs(strike - target_strike), strike)

app/services/backtesting/input_normalization.py

@@ -0,0 +1,51 @@
+from __future__ import annotations
+
+from dataclasses import dataclass
+
+from app.services.boundary_values import boundary_decimal
+
+
+@dataclass(frozen=True, slots=True)
+class NormalizedHistoricalScenarioInputs:
+    underlying_units: float
+    loan_amount: float
+    margin_call_ltv: float
+    currency: str = "USD"
+    cash_balance: float = 0.0
+    financing_rate: float = 0.0
+
+
+def normalize_historical_scenario_inputs(
+    *,
+    underlying_units: object,
+    loan_amount: object,
+    margin_call_ltv: object,
+    currency: object = "USD",
+    cash_balance: object = 0.0,
+    financing_rate: object = 0.0,
+) -> NormalizedHistoricalScenarioInputs:
+    normalized_currency = str(currency).strip().upper()
+    if not normalized_currency:
+        raise ValueError("Currency is required")
+
+    units = float(boundary_decimal(underlying_units, field_name="underlying_units"))
+    normalized_loan_amount = float(boundary_decimal(loan_amount, field_name="loan_amount"))
+    ltv = float(boundary_decimal(margin_call_ltv, field_name="margin_call_ltv"))
+    normalized_cash_balance = float(boundary_decimal(cash_balance, field_name="cash_balance"))
+    normalized_financing_rate = float(boundary_decimal(financing_rate, field_name="financing_rate"))
+
+    if units <= 0:
+        raise ValueError("Underlying units must be positive")
+    if normalized_loan_amount < 0:
+        raise ValueError("Loan amount must be non-negative")
+    if not 0 < ltv < 1:
+        raise ValueError("Margin call LTV must be between 0 and 1")
+
+    return NormalizedHistoricalScenarioInputs(
+        underlying_units=units,
+        loan_amount=normalized_loan_amount,
+        margin_call_ltv=ltv,
+        currency=normalized_currency,
+        cash_balance=normalized_cash_balance,
+        financing_rate=normalized_financing_rate,
+    )

app/services/backtesting/jobs.py

@@ -0,0 +1,359 @@
+"""Async backtest job execution with progress tracking.
+
+This module provides a non-blocking backtest execution system:
+1. Jobs are submitted and run in background threads
+2. Progress is tracked with stages (validating, fetching_prices, calculating, complete)
+3. UI polls for status updates
+4. Results are cached for retrieval
+"""
+
+from __future__ import annotations
+
+import logging
+import threading
+import uuid
+from dataclasses import dataclass, field
+from datetime import date, datetime
+from enum import Enum
+from typing import TYPE_CHECKING, Any
+
+if TYPE_CHECKING:
+    from app.services.backtesting.ui_service import BacktestPageService
+
+logger = logging.getLogger(__name__)
+
+
+class JobStatus(str, Enum):
+    """Status of a backtest job."""
+
+    PENDING = "pending"
+    RUNNING = "running"
+    COMPLETE = "complete"
+    FAILED = "failed"
+
+
+class JobStage(str, Enum):
+    """Execution stages with user-friendly labels."""
+
+    VALIDATING = "validating"
+    FETCHING_PRICES = "fetching_prices"
+    CALCULATING = "calculating"
+    COMPLETE = "complete"
+    FAILED = "failed"
+
+    @property
+    def label(self) -> str:
+        """Human-readable stage label."""
+        labels = {
+            JobStage.VALIDATING: "Validating inputs...",
+            JobStage.FETCHING_PRICES: "Fetching historical prices...",
+            JobStage.CALCULATING: "Running backtest calculations...",
+            JobStage.COMPLETE: "Complete",
+            JobStage.FAILED: "Failed",
+        }
+        return labels.get(self, self.value)
+
+
+@dataclass
+class BacktestJob:
+    """Represents a backtest job with progress tracking."""
+
+    job_id: str
+    status: JobStatus = JobStatus.PENDING
+    stage: JobStage = JobStage.VALIDATING
+    progress: int = 0  # 0-100
+    message: str = ""
+    result: dict[str, Any] | None = None
+    error: str | None = None
+    created_at: datetime = field(default_factory=datetime.utcnow)
+    completed_at: datetime | None = None
+
+    def to_dict(self) -> dict[str, Any]:
+        """Serialize job for JSON response."""
+        return {
+            "job_id": self.job_id,
+            "status": self.status.value,
+            "stage": self.stage.value,
+            "stage_label": self.stage.label,
+            "progress": self.progress,
+            "message": self.message,
+            "has_result": self.result is not None,
+            "error": self.error,
+            "created_at": self.created_at.isoformat(),
+            "completed_at": self.completed_at.isoformat() if self.completed_at else None,
+        }
+
+
+class BacktestJobStore:
+    """In-memory store for backtest jobs.
+
+    Jobs are stored in a dict keyed by workspace_id -> job_id.
+    Each workspace only has one active job at a time (latest replaces previous).
+    """
+
+    def __init__(self) -> None:
+        self._jobs: dict[str, BacktestJob] = {}  # workspace_id -> job
+        self._results: dict[str, dict[str, Any]] = {}  # job_id -> result
+        self._lock = threading.Lock()
+
+    def create_job(self, workspace_id: str) -> BacktestJob:
+        """Create a new job for a workspace, replacing any existing one."""
+        job = BacktestJob(job_id=str(uuid.uuid4()))
+        with self._lock:
+            self._jobs[workspace_id] = job
+        logger.info(f"Created job {job.job_id} for workspace {workspace_id}")
+        return job
+
+    def get_job(self, workspace_id: str) -> BacktestJob | None:
+        """Get the current job for a workspace."""
+        with self._lock:
+            return self._jobs.get(workspace_id)
+
+    def update_job(
+        self,
+        workspace_id: str,
+        *,
+        status: JobStatus | None = None,
+        stage: JobStage | None = None,
+        progress: int | None = None,
+        message: str | None = None,
+        result: dict[str, Any] | None = None,
+        error: str | None = None,
+    ) -> None:
+        """Update job state."""
+        with self._lock:
+            job = self._jobs.get(workspace_id)
+            if not job:
+                return
+            if status:
+                job.status = status
+            if stage:
+                job.stage = stage
+            if progress is not None:
+                job.progress = progress
+            if message is not None:
+                job.message = message
+            if result is not None:
+                job.result = result
+                self._results[job.job_id] = result
+            if error:
+                job.error = error
+            if stage == JobStage.COMPLETE or stage == JobStage.FAILED:
+                job.completed_at = datetime.utcnow()
+
+    def get_result(self, job_id: str) -> dict[str, Any] | None:
+        """Get cached result by job ID."""
+        with self._lock:
+            return self._results.get(job_id)
+
+    def clear_job(self, workspace_id: str) -> None:
+        """Remove job from store."""
+        with self._lock:
+            if workspace_id in self._jobs:
+                del self._jobs[workspace_id]
+
+
+# Global job store singleton
+job_store = BacktestJobStore()
+
+
+def run_backtest_job(
+    workspace_id: str,
+    job: BacktestJob,
+    service: "BacktestPageService",
+    symbol: str,
+    start_date: date,
+    end_date: date,
+    template_slug: str,
+    underlying_units: float,
+    loan_amount: float,
+    margin_call_ltv: float,
+    data_source: str,
+) -> None:
+    """Execute backtest in background thread with progress updates.
+
+    This function runs in a background thread and updates the job state
+    as it progresses through stages.
+    """
+    try:
+        # Stage 1: Validating
+        job_store.update_job(
+            workspace_id,
+            status=JobStatus.RUNNING,
+            stage=JobStage.VALIDATING,
+            progress=10,
+            message="Validating inputs...",
+        )
+
+        # Stage 2: Fetching prices
+        job_store.update_job(
+            workspace_id,
+            stage=JobStage.FETCHING_PRICES,
+            progress=30,
+            message=f"Fetching prices for {symbol}...",
+        )
+
+        # Run the backtest (this includes price fetching)
+        result = service.run_read_only_scenario(
+            symbol=symbol,
+            start_date=start_date,
+            end_date=end_date,
+            template_slug=template_slug,
+            underlying_units=underlying_units,
+            loan_amount=loan_amount,
+            margin_call_ltv=margin_call_ltv,
+            data_source=data_source,
+        )
+
+        # Stage 3: Calculating (already done by run_read_only_scenario)
+        job_store.update_job(
+            workspace_id,
+            stage=JobStage.CALCULATING,
+            progress=70,
+            message="Processing results...",
+        )
+
+        # Convert result to dict for serialization
+        # BacktestPageRunResult has: scenario, run_result, entry_spot, data_source, data_cost_usd
+        template_results = result.run_result.template_results
+        first_template = template_results[0] if template_results else None
+        summary = first_template.summary_metrics if first_template else None
+
+        result_dict = {
+            "scenario_id": result.scenario.scenario_id,
+            "scenario_name": result.scenario.display_name,
+            "symbol": result.scenario.symbol,
+            "start_date": result.scenario.start_date.isoformat(),
+            "end_date": result.scenario.end_date.isoformat(),
+            "entry_spot": result.entry_spot,
+            "underlying_units": result.scenario.initial_portfolio.underlying_units,
+            "loan_amount": result.scenario.initial_portfolio.loan_amount,
+            "margin_call_ltv": result.scenario.initial_portfolio.margin_call_ltv,
+            "data_source": result.data_source,
+            "data_cost_usd": result.data_cost_usd,
+            # Summary metrics from first template result
+            "start_value": summary.start_value if summary else 0.0,
+            "end_value_hedged_net": summary.end_value_hedged_net if summary else 0.0,
+            "total_hedge_cost": summary.total_hedge_cost if summary else 0.0,
+            "max_ltv_hedged": summary.max_ltv_hedged if summary else 0.0,
+            "max_ltv_unhedged": summary.max_ltv_unhedged if summary else 0.0,
+            "margin_call_days_hedged": summary.margin_call_days_hedged if summary else 0,
+            "margin_call_days_unhedged": summary.margin_call_days_unhedged if summary else 0,
+            "margin_threshold_breached_hedged": summary.margin_threshold_breached_hedged if summary else False,
+            "margin_threshold_breached_unhedged": summary.margin_threshold_breached_unhedged if summary else False,
+            # Template results with full daily path
+            "template_results": [
+                {
+                    "template_slug": tr.template_slug,
+                    "template_name": tr.template_name,
+                    "summary_metrics": {
+                        "start_value": tr.summary_metrics.start_value,
+                        "end_value_hedged_net": tr.summary_metrics.end_value_hedged_net,
+                        "total_hedge_cost": tr.summary_metrics.total_hedge_cost,
+                        "max_ltv_hedged": tr.summary_metrics.max_ltv_hedged,
+                        "max_ltv_unhedged": tr.summary_metrics.max_ltv_unhedged,
+                        "margin_call_days_hedged": tr.summary_metrics.margin_call_days_hedged,
+                        "margin_call_days_unhedged": tr.summary_metrics.margin_call_days_unhedged,
+                    },
+                    "daily_path": [
+                        {
+                            "date": dp.date.isoformat(),
+                            "spot_close": dp.spot_close,
+                            "spot_open": dp.spot_open if dp.spot_open is not None else dp.spot_close,
+                            "spot_low": dp.spot_low if dp.spot_low is not None else dp.spot_close,
+                            "spot_high": dp.spot_high if dp.spot_high is not None else dp.spot_close,
+                            "underlying_value": dp.underlying_value,
+                            "option_market_value": dp.option_market_value,
+                            "net_portfolio_value": dp.net_portfolio_value,
+                            "option_contracts": dp.option_contracts,
+                            "ltv_hedged": dp.ltv_hedged,
+                            "ltv_unhedged": dp.ltv_unhedged,
+                            "margin_call_hedged": dp.margin_call_hedged,
+                            "margin_call_unhedged": dp.margin_call_unhedged,
+                        }
+                        for dp in tr.daily_path
+                    ],
+                }
+                for tr in template_results
+            ],
+        }
+
+        # Stage 4: Complete
+        job_store.update_job(
+            workspace_id,
+            status=JobStatus.COMPLETE,
+            stage=JobStage.COMPLETE,
+            progress=100,
+            message="Backtest complete!",
+            result=result_dict,
+        )
+
+        logger.info(f"Job {job.job_id} completed successfully")
+
+    except Exception as e:
+        logger.exception(f"Job {job.job_id} failed: {e}")
+        error_msg = str(e)
+
+        # Check for Databento API errors
+        if "data_start_before_available_start" in error_msg:
+            import re
+
+            match = re.search(r"available start of dataset [^(]+\('([^']+)'", error_msg)
+            if match:
+                available_start = match.group(1).split()[0]
+                error_msg = (
+                    f"Data not available before {available_start}. Please set start date to {available_start} or later."
+                )
+            else:
+                error_msg = "Selected start date is before data is available for this dataset."
+        elif "BentoClientError" in error_msg or "422" in error_msg:
+            error_msg = f"Data source error: {error_msg}"
+
+        job_store.update_job(
+            workspace_id,
+            status=JobStatus.FAILED,
+            stage=JobStage.FAILED,
+            progress=0,
+            error=error_msg,
+        )
+
+
+def start_backtest_job(
+    workspace_id: str,
+    service: "BacktestPageService",
+    symbol: str,
+    start_date: date,
+    end_date: date,
+    template_slug: str,
+    underlying_units: float,
+    loan_amount: float,
+    margin_call_ltv: float,
+    data_source: str,
+) -> BacktestJob:
+    """Start a backtest job in a background thread.
+
+    Returns immediately with the job ID. The job runs in the background
+    and can be polled for status.
+    """
+    job = job_store.create_job(workspace_id)
+
+    thread = threading.Thread(
+        target=run_backtest_job,
+        kwargs={
+            "workspace_id": workspace_id,
+            "job": job,
+            "service": service,
+            "symbol": symbol,
+            "start_date": start_date,
+            "end_date": end_date,
+            "template_slug": template_slug,
+            "underlying_units": underlying_units,
+            "loan_amount": loan_amount,
+            "margin_call_ltv": margin_call_ltv,
+            "data_source": data_source,
+        },
+        daemon=True,
+    )
+    thread.start()
+
+    return job

app/services/backtesting/service.py

@@ -0,0 +1,73 @@
+from __future__ import annotations
+
+from math import isclose
+
+from app.backtesting.engine import SyntheticBacktestEngine
+from app.models.backtest import BacktestRunResult, BacktestScenario
+from app.models.strategy_template import StrategyTemplate
+from app.services.backtesting.historical_provider import BacktestHistoricalProvider, SyntheticHistoricalProvider
+from app.services.strategy_templates import StrategyTemplateService
+
+
+class BacktestService:
+    ENTRY_SPOT_ABS_TOLERANCE = 0.01
+    ENTRY_SPOT_REL_TOLERANCE = 1e-6
+
+    def __init__(
+        self,
+        provider: BacktestHistoricalProvider | None = None,
+        template_service: StrategyTemplateService | None = None,
+    ) -> None:
+        self.provider = provider or SyntheticHistoricalProvider()
+        self.template_service = template_service or StrategyTemplateService()
+        self.engine = SyntheticBacktestEngine(self.provider)
+
+    def run_scenario(self, scenario: BacktestScenario) -> BacktestRunResult:
+        self.provider.validate_provider_ref(scenario.provider_ref)
+        scenario_symbol = scenario.symbol.strip().upper()
+        history = self.provider.load_history(scenario_symbol, scenario.start_date, scenario.end_date)
+        if not history:
+            raise ValueError("No historical prices found for scenario window")
+        if history[0].date != scenario.start_date:
+            raise ValueError(
+                "Scenario start_date must match the first available historical price point for "
+                "entry_timing='scenario_start_close'"
+            )
+        if not isclose(
+            scenario.initial_portfolio.entry_spot,
+            history[0].close,
+            rel_tol=self.ENTRY_SPOT_REL_TOLERANCE,
+            abs_tol=self.ENTRY_SPOT_ABS_TOLERANCE,
+        ):
+            raise ValueError(
+                "initial_portfolio.entry_spot must match the first historical close used for entry "
+                "when entry_timing='scenario_start_close'"
+            )
+
+        template_results = []
+        for template_ref in scenario.template_refs:
+            template = self.template_service.get_template(template_ref.slug)
+            if template.version != template_ref.version:
+                raise ValueError(
+                    f"Template version mismatch for {template_ref.slug}: expected {template_ref.version}, got {template.version}"
+                )
+            template_symbol = template.underlying_symbol.strip().upper()
+            if template_symbol not in {scenario_symbol, "*"}:
+                raise ValueError(f"Template {template.slug} does not support symbol {scenario_symbol}")
+            self._validate_template_for_mvp(template)
+            template_results.append(self.engine.run_template(scenario, template, history))
+
+        return BacktestRunResult(scenario_id=scenario.scenario_id, template_results=tuple(template_results))
+
+    def _validate_template_for_mvp(self, template: StrategyTemplate) -> None:
+        provider_label = (
+            "historical snapshot engine" if self.provider.pricing_mode == "snapshot_mid" else "synthetic MVP engine"
+        )
+        if template.contract_mode != "continuous_units":
+            raise ValueError(f"Unsupported contract_mode for {provider_label}: {template.contract_mode}")
+        if template.roll_policy.policy_type != "hold_to_expiry":
+            raise ValueError(f"Unsupported roll_policy for {provider_label}: {template.roll_policy.policy_type}")
+        if template.entry_policy.entry_timing != "scenario_start_close":
+            raise ValueError(f"Unsupported entry_timing for {provider_label}: {template.entry_policy.entry_timing}")
+        if template.entry_policy.stagger_days is not None:
+            raise ValueError(f"Unsupported entry_policy configuration for {provider_label}")

app/services/backtesting/ui_service.py

@@ -0,0 +1,388 @@
+from __future__ import annotations
+
+from copy import copy
+from dataclasses import dataclass
+from datetime import date
+from math import isclose
+from typing import Any
+
+from app.backtesting.engine import SyntheticBacktestEngine
+from app.domain.backtesting_math import materialize_backtest_portfolio_state
+from app.models.backtest import (
+    BacktestRunResult,
+    BacktestScenario,
+    ProviderRef,
+    TemplateRef,
+)
+from app.services.backtesting.databento_source import DatabentoHistoricalPriceSource, DatabentoSourceConfig
+from app.services.backtesting.fixture_source import (
+    FixtureBoundSyntheticHistoricalProvider,
+    build_backtest_ui_fixture_source,
+)
+from app.services.backtesting.historical_provider import (
+    DailyClosePoint,
+    SyntheticHistoricalProvider,
+    YFinanceHistoricalPriceSource,
+)
+from app.services.backtesting.input_normalization import normalize_historical_scenario_inputs
+from app.services.backtesting.service import BacktestService
+from app.services.strategy_templates import StrategyTemplateService
+
+SUPPORTED_BACKTEST_PAGE_SYMBOLS = ("GLD", "GC", "XAU")
+SUPPORTED_DATABENTO_BACKTEST_PAGE_SYMBOLS = ("GLD", "XAU")
+
+
+def _validate_initial_collateral(underlying_units: float, entry_spot: float, loan_amount: float) -> None:
+    initial_collateral_value = underlying_units * entry_spot
+    if loan_amount >= initial_collateral_value:
+        raise ValueError(
+            "Historical scenario starts undercollateralized: "
+            f"loan ${loan_amount:,.0f} exceeds initial collateral ${initial_collateral_value:,.0f} "
+            f"at entry spot ${entry_spot:,.2f}. Reduce loan amount or increase underlying units."
+        )
+
+
+@dataclass(frozen=True)
+class BacktestPageRunResult:
+    scenario: BacktestScenario
+    run_result: BacktestRunResult
+    entry_spot: float
+    data_source: str = "synthetic"
+    data_cost_usd: float = 0.0
+    cache_status: str = ""
+
+
+@dataclass(frozen=True)
+class DataSourceInfo:
+    """Information about a data source."""
+
+    provider_id: str
+    pricing_mode: str
+    display_name: str
+    supports_cost_estimate: bool
+    supports_cache: bool
+
+
+class BacktestPageService:
+    """Service for the backtest page UI.
+
+    This service manages historical data providers and supports multiple
+    data sources including Databento, Yahoo Finance, and synthetic data.
+    """
+
+    DATA_SOURCE_INFO: dict[str, DataSourceInfo] = {
+        "databento": DataSourceInfo(
+            provider_id="databento",
+            pricing_mode="historical",
+            display_name="Databento",
+            supports_cost_estimate=True,
+            supports_cache=True,
+        ),
+        "yfinance": DataSourceInfo(
+            provider_id="yfinance",
+            pricing_mode="free",
+            display_name="Yahoo Finance",
+            supports_cost_estimate=False,
+            supports_cache=False,
+        ),
+        "synthetic": DataSourceInfo(
+            provider_id="synthetic_v1",
+            pricing_mode="synthetic_bs_mid",
+            display_name="Synthetic",
+            supports_cost_estimate=False,
+            supports_cache=False,
+        ),
+    }
+
+    def __init__(
+        self,
+        backtest_service: BacktestService | None = None,
+        template_service: StrategyTemplateService | None = None,
+        databento_config: DatabentoSourceConfig | None = None,
+    ) -> None:
+        base_service = backtest_service or BacktestService(
+            template_service=template_service,
+            provider=None,
+        )
+        self.template_service = template_service or base_service.template_service
+        self.databento_config = databento_config
+        # Use the injected provider if available, otherwise create a new one
+        base_provider = base_service.provider
+        if base_provider is None:
+            base_provider = SyntheticHistoricalProvider()
+        fixture_provider = FixtureBoundSyntheticHistoricalProvider(
+            base_provider=base_provider,  # type: ignore[arg-type]
+            source=build_backtest_ui_fixture_source(),
+        )
+        self.backtest_service = copy(base_service)
+        self.backtest_service.provider = fixture_provider
+        self.backtest_service.template_service = self.template_service
+        self.backtest_service.engine = SyntheticBacktestEngine(fixture_provider)
+
+        # Cache for Databento provider instances
+        self._databento_provider: DatabentoHistoricalPriceSource | None = None
+        self._yfinance_provider: YFinanceHistoricalPriceSource | None = None
+
+    def _get_databento_provider(self) -> DatabentoHistoricalPriceSource:
+        """Get or create the Databento provider instance."""
+        if self._databento_provider is None:
+            self._databento_provider = DatabentoHistoricalPriceSource(config=self.databento_config)
+        return self._databento_provider
+
+    def _get_yfinance_provider(self) -> YFinanceHistoricalPriceSource:
+        """Get or create the YFinance provider instance."""
+        if self._yfinance_provider is None:
+            self._yfinance_provider = YFinanceHistoricalPriceSource()
+        return self._yfinance_provider
+
+    @staticmethod
+    def validate_data_source_support(symbol: str, data_source: str) -> None:
+        normalized_symbol = symbol.strip().upper()
+        if data_source == "databento" and normalized_symbol not in SUPPORTED_DATABENTO_BACKTEST_PAGE_SYMBOLS:
+            raise ValueError(
+                "Databento backtests currently support GLD and XAU only. "
+                "GC futures remain unavailable on the backtest page until contract mapping is wired."
+            )
+
+    def get_historical_prices(
+        self, symbol: str, start_date: date, end_date: date, data_source: str
+    ) -> list[DailyClosePoint]:
+        """Load historical prices from the specified data source.
+
+        Args:
+            symbol: Trading symbol (GLD, GC, XAU)
+            start_date: Start date
+            end_date: End date
+            data_source: One of "databento", "yfinance", "synthetic"
+
+        Returns:
+            List of daily close points sorted by date
+        """
+        self.validate_data_source_support(symbol, data_source)
+        if data_source == "databento":
+            return self._get_databento_provider().load_daily_closes(symbol, start_date, end_date)
+        elif data_source == "yfinance":
+            return self._get_yfinance_provider().load_daily_closes(symbol, start_date, end_date)
+        else:
+            # Use synthetic fixture data
+            return self.backtest_service.provider.load_history(symbol, start_date, end_date)
+
+    def get_cost_estimate(self, symbol: str, start_date: date, end_date: date, data_source: str = "databento") -> float:
+        """Get estimated cost for the data request.
+
+        Args:
+            symbol: Trading symbol
+            start_date: Start date
+            end_date: End date
+            data_source: Data source (only "databento" supports this)
+
+        Returns:
+            Estimated cost in USD
+        """
+        if data_source != "databento":
+            return 0.0
+
+        self.validate_data_source_support(symbol, data_source)
+
+        try:
+            provider = self._get_databento_provider()
+            return provider.get_cost_estimate(symbol, start_date, end_date)
+        except Exception:
+            return 0.0
+
+    def get_cache_stats(
+        self, symbol: str, start_date: date, end_date: date, data_source: str = "databento"
+    ) -> dict[str, Any]:
+        """Get cache statistics for the data request.
+
+        Args:
+            symbol: Trading symbol
+            start_date: Start date
+            end_date: End date
+            data_source: Data source (only "databento" supports this)
+
+        Returns:
+            Dict with cache statistics
+        """
+        if data_source != "databento":
+            return {"status": "not_applicable", "entries": []}
+
+        try:
+            provider = self._get_databento_provider()
+            return provider.get_cache_stats()
+        except Exception:
+            return {"status": "error", "entries": []}
+
+    def get_available_date_range(self, symbol: str, data_source: str = "databento") -> tuple[date | None, date | None]:
+        """Get the available date range for a symbol from the data source.
+
+        Args:
+            symbol: Trading symbol
+            data_source: Data source (only "databento" supports this)
+
+        Returns:
+            Tuple of (start_date, end_date) or (None, None) if unavailable
+        """
+        if data_source != "databento":
+            return None, None
+
+        self.validate_data_source_support(symbol, data_source)
+
+        try:
+            provider = self._get_databento_provider()
+            return provider.get_available_range(symbol)
+        except Exception:
+            return None, None
+
+    def template_options(self, symbol: str = "GLD") -> list[dict[str, str | int]]:
+        return [
+            {
+                "label": template.display_name,
+                "slug": template.slug,
+                "version": template.version,
+                "description": template.description,
+            }
+            for template in self.template_service.list_active_templates(symbol)
+        ]
+
+    def derive_entry_spot(self, symbol: str, start_date: date, end_date: date, data_source: str) -> float:
+        history = self.get_historical_prices(symbol, start_date, end_date, data_source)
+        if not history:
+            raise ValueError("No historical prices found for scenario window")
+        if history[0].date != start_date:
+            raise ValueError(
+                "Scenario start date must match the first available historical close for entry-at-start backtests"
+            )
+        return history[0].close
+
+    def validate_preview_inputs(
+        self,
+        *,
+        symbol: str,
+        start_date: date,
+        end_date: date,
+        template_slug: str,
+        underlying_units: float,
+        loan_amount: float,
+        margin_call_ltv: float,
+        entry_spot: float | None = None,
+        data_source: str,
+    ) -> float:
+        normalized_symbol = symbol.strip().upper()
+        if not normalized_symbol:
+            raise ValueError("Symbol is required")
+        if normalized_symbol not in SUPPORTED_BACKTEST_PAGE_SYMBOLS:
+            raise ValueError(f"Backtests support symbols: {', '.join(SUPPORTED_BACKTEST_PAGE_SYMBOLS)}")
+        self.validate_data_source_support(normalized_symbol, data_source)
+        if start_date > end_date:
+            raise ValueError("Start date must be on or before end date")
+        normalized_inputs = normalize_historical_scenario_inputs(
+            underlying_units=underlying_units,
+            loan_amount=loan_amount,
+            margin_call_ltv=margin_call_ltv,
+        )
+        if not template_slug:
+            raise ValueError("Template selection is required")
+
+        self.template_service.get_template(template_slug)
+        derived_entry_spot = self.derive_entry_spot(normalized_symbol, start_date, end_date, data_source)
+        if entry_spot is not None and not isclose(
+            entry_spot,
+            derived_entry_spot,
+            rel_tol=BacktestService.ENTRY_SPOT_REL_TOLERANCE,
+            abs_tol=BacktestService.ENTRY_SPOT_ABS_TOLERANCE,
+        ):
+            raise ValueError(
+                f"Supplied entry spot ${entry_spot:,.2f} does not match derived historical entry spot ${derived_entry_spot:,.2f}"
+            )
+        _validate_initial_collateral(
+            normalized_inputs.underlying_units,
+            derived_entry_spot,
+            normalized_inputs.loan_amount,
+        )
+        return derived_entry_spot
+
+    def run_read_only_scenario(
+        self,
+        *,
+        symbol: str,
+        start_date: date,
+        end_date: date,
+        template_slug: str,
+        underlying_units: float,
+        loan_amount: float,
+        margin_call_ltv: float,
+        data_source: str = "synthetic",
+    ) -> BacktestPageRunResult:
+        normalized_symbol = symbol.strip().upper()
+        entry_spot = self.validate_preview_inputs(
+            symbol=normalized_symbol,
+            start_date=start_date,
+            end_date=end_date,
+            template_slug=template_slug,
+            underlying_units=underlying_units,
+            loan_amount=loan_amount,
+            margin_call_ltv=margin_call_ltv,
+            data_source=data_source,
+        )
+        normalized_inputs = normalize_historical_scenario_inputs(
+            underlying_units=underlying_units,
+            loan_amount=loan_amount,
+            margin_call_ltv=margin_call_ltv,
+        )
+        template = self.template_service.get_template(template_slug)
+        initial_portfolio = materialize_backtest_portfolio_state(
+            symbol=normalized_symbol,
+            underlying_units=normalized_inputs.underlying_units,
+            entry_spot=entry_spot,
+            loan_amount=normalized_inputs.loan_amount,
+            margin_call_ltv=normalized_inputs.margin_call_ltv,
+        )
+
+        # Fetch historical prices using the specified data source
+        history = self.get_historical_prices(normalized_symbol, start_date, end_date, data_source)
+        if not history:
+            raise ValueError("No historical prices found for scenario window")
+        if history[0].date != start_date:
+            raise ValueError(
+                "Scenario start date must match the first available historical close for entry-at-start backtests"
+            )
+
+        # Use the fixture provider's ID for the scenario (for pricing mode)
+        # The actual price data comes from the specified data_source
+        provider_id = self.backtest_service.provider.provider_id
+        pricing_mode = self.backtest_service.provider.pricing_mode
+
+        scenario = BacktestScenario(
+            scenario_id=(
+                f"{normalized_symbol.lower()}-{start_date.isoformat()}-{end_date.isoformat()}-{template.slug}"
+            ),
+            display_name=f"{normalized_symbol} backtest {start_date.isoformat()} → {end_date.isoformat()}",
+            symbol=normalized_symbol,
+            start_date=start_date,
+            end_date=end_date,
+            initial_portfolio=initial_portfolio,
+            template_refs=(TemplateRef(slug=template.slug, version=template.version),),
+            provider_ref=ProviderRef(
+                provider_id=provider_id,
+                pricing_mode=pricing_mode,
+            ),
+        )
+
+        # Get cost estimate for Databento
+        data_cost_usd = 0.0
+        if data_source == "databento":
+            data_cost_usd = self.get_cost_estimate(normalized_symbol, start_date, end_date, data_source)
+
+        # Run the backtest engine directly with pre-fetched history
+        # This bypasses the fixture provider in BacktestService.run_scenario
+        template_result = self.backtest_service.engine.run_template(scenario, template, history)
+        run_result = BacktestRunResult(scenario_id=scenario.scenario_id, template_results=(template_result,))
+
+        return BacktestPageRunResult(
+            scenario=scenario,
+            run_result=run_result,
+            entry_spot=entry_spot,
+            data_source=data_source,
+            data_cost_usd=data_cost_usd,
+        )

app/services/boundary_values.py

@@ -0,0 +1,25 @@
+from __future__ import annotations
+
+from decimal import Decimal, InvalidOperation
+
+from app.domain.units import decimal_from_float, to_decimal
+
+
+def boundary_decimal(value: object, *, field_name: str) -> Decimal:
+    if value is None:
+        raise ValueError(f"{field_name} must be present")
+    if isinstance(value, bool):
+        raise TypeError(f"{field_name} must be numeric, got bool")
+    if isinstance(value, float):
+        return decimal_from_float(value)
+    if isinstance(value, (Decimal, int)):
+        return to_decimal(value)
+    if isinstance(value, str):
+        stripped = value.strip()
+        if not stripped:
+            raise ValueError(f"{field_name} must be present")
+        try:
+            return to_decimal(stripped)
+        except InvalidOperation as exc:
+            raise ValueError(f"{field_name} must be numeric, got {value!r}") from exc
+    raise TypeError(f"{field_name} must be numeric, got {type(value)!r}")

app/services/cache.py

@@ -35,8 +35,9 @@ class CacheService:
             return
 
         try:
+            if self.url:
                 self._client = RedisClient.from_url(self.url, decode_responses=True)  # type: ignore[misc]
-            await self._client.ping()
+            await self._client.ping()  # type: ignore[union-attr]
             logger.info("Connected to Redis cache")
         except Exception as exc:  # pragma: no cover - network dependent
             logger.warning("Redis unavailable, cache disabled: %s", exc)
@@ -70,3 +71,18 @@ class CacheService:
         if isinstance(value, datetime):
             return value.isoformat()
         raise TypeError(f"Object of type {type(value).__name__} is not JSON serializable")
+
+
+# Global cache instance
+_cache_instance: CacheService | None = None
+
+
+def get_cache() -> CacheService:
+    """Get or create global cache instance."""
+    global _cache_instance
+    if _cache_instance is None:
+        import os
+
+        redis_url = os.environ.get("REDIS_URL")
+        _cache_instance = CacheService(redis_url)
+    return _cache_instance

app/services/data_service.py

@@ -4,9 +4,12 @@ from __future__ import annotations
 
 import asyncio
 import logging
-from datetime import UTC, datetime
+import math
+from datetime import date, datetime, timezone
 from typing import Any
 
+from app.core.calculations import option_row_greeks
+from app.domain.instruments import gld_ounces_per_share
 from app.services.cache import CacheService
 from app.strategies.engine import StrategySelectionEngine
 
@@ -21,9 +24,15 @@ except ImportError:  # pragma: no cover - optional dependency
 class DataService:
     """Fetches portfolio and market data, using Redis when available."""
 
-    def __init__(self, cache: CacheService, default_symbol: str = "GLD") -> None:
+    def __init__(self, cache: CacheService, default_underlying: str = "GLD") -> None:
         self.cache = cache
-        self.default_symbol = default_symbol
+        self.default_underlying = default_underlying
+        self.gc_f_symbol = "GC=F"  # COMEX Gold Futures
+
+    @property
+    def default_symbol(self) -> str:
+        """Backward compatibility alias for default_underlying."""
+        return self.default_underlying
 
     async def get_portfolio(self, symbol: str | None = None) -> dict[str, Any]:
         ticker = (symbol or self.default_symbol).upper()
@@ -40,63 +49,403 @@ class DataService:
             "portfolio_value": round(quote["price"] * 1000, 2),
             "loan_amount": 600_000.0,
             "ltv_ratio": round(600_000.0 / max(quote["price"] * 1000, 1), 4),
-            "updated_at": datetime.now(UTC).isoformat(),
+            "updated_at": datetime.now(timezone.utc).isoformat(),
             "source": quote["source"],
         }
         await self.cache.set_json(cache_key, portfolio)
         return portfolio
 
     async def get_quote(self, symbol: str) -> dict[str, Any]:
-        cache_key = f"quote:{symbol}"
+        """Fetch quote for the given symbol, routing to appropriate data source.
+
+        For GLD: fetches from yfinance (ETF share price)
+        For GC=F: fetches from yfinance (futures price) or returns placeholder
+        """
+        normalized_symbol = symbol.upper()
+        cache_key = f"quote:{normalized_symbol}"
         cached = await self.cache.get_json(cache_key)
         if cached and isinstance(cached, dict):
-            return cached
+            try:
+                normalized_cached = self._normalize_quote_payload(cached, normalized_symbol)
+            except ValueError:
+                normalized_cached = None
+            if normalized_cached is not None:
+                if normalized_cached != cached:
+                    await self.cache.set_json(cache_key, normalized_cached)
+                return normalized_cached
+
+        # Route based on underlying
+        if normalized_symbol == "GC=F":
+            quote = self._normalize_quote_payload(await self._fetch_gc_futures(), normalized_symbol)
+        else:
+            quote = self._normalize_quote_payload(await self._fetch_quote(normalized_symbol), normalized_symbol)
 
-        quote = await self._fetch_quote(symbol)
         await self.cache.set_json(cache_key, quote)
         return quote
 
-    async def get_options_chain(self, symbol: str | None = None) -> dict[str, Any]:
+    async def get_option_expirations(self, symbol: str | None = None) -> dict[str, Any]:
-        ticker = (symbol or self.default_symbol).upper()
+        ticker_symbol = (symbol or self.default_underlying).upper()
-        cache_key = f"options:{ticker}"
+        cache_key = f"options:{ticker_symbol}:expirations"
 
         cached = await self.cache.get_json(cache_key)
         if cached and isinstance(cached, dict):
-            return cached
+            malformed_list_shape = (
+                not isinstance(cached.get("expirations"), list) and cached.get("expirations") is not None
+            )
+            try:
+                normalized_cached = self._normalize_option_expirations_payload(cached, ticker_symbol)
+            except ValueError as exc:
+                logger.warning("Discarding cached option expirations payload for %s: %s", ticker_symbol, exc)
+                normalized_cached = None
+            if malformed_list_shape:
+                logger.warning("Discarding malformed cached option expirations payload for %s", ticker_symbol)
+                normalized_cached = None
+            if normalized_cached is not None:
+                if normalized_cached != cached:
+                    await self.cache.set_json(cache_key, normalized_cached)
+                return normalized_cached
 
-        quote = await self.get_quote(ticker)
+        # GC=F options not yet implemented - return placeholder
-        base_price = quote["price"]
+        if ticker_symbol == "GC=F":
-        options_chain = {
+            quote = await self.get_quote(ticker_symbol)
-            "symbol": ticker,
+            payload = self._fallback_option_expirations(
-            "updated_at": datetime.now(UTC).isoformat(),
+                ticker_symbol,
-            "calls": [
+                quote,
+                source="placeholder",
+                error="Options data for GC=F coming soon",
+            )
+            await self.cache.set_json(cache_key, payload)
+            return payload
+
+        quote = await self.get_quote(ticker_symbol)
+        if yf is None:
+            payload = self._fallback_option_expirations(
+                ticker_symbol,
+                quote,
+                source="fallback",
+                error="yfinance is not installed",
+            )
+            await self.cache.set_json(cache_key, payload)
+            return payload
+
+        try:
+            ticker = yf.Ticker(ticker_symbol)
+            expirations = await asyncio.to_thread(lambda: list(ticker.options or []))
+            if not expirations:
+                payload = self._fallback_option_expirations(
+                    ticker_symbol,
+                    quote,
+                    source="fallback",
+                    error="No option expirations returned by yfinance",
+                )
+                await self.cache.set_json(cache_key, payload)
+                return payload
+
+            payload = self._normalize_option_expirations_payload(
                 {
-                    "strike": round(base_price * 1.05, 2),
+                    "symbol": ticker_symbol,
-                    "premium": round(base_price * 0.03, 2),
+                    "updated_at": datetime.now(timezone.utc).isoformat(),
-                    "expiry": "2026-06-19",
+                    "expirations": expirations,
+                    "underlying_price": quote["price"],
+                    "source": "yfinance",
                 },
+                ticker_symbol,
+            )
+            await self.cache.set_json(cache_key, payload)
+            return payload
+        except Exception as exc:  # pragma: no cover - network dependent
+            logger.warning("Failed to fetch option expirations for %s from yfinance: %s", ticker_symbol, exc)
+            payload = self._fallback_option_expirations(
+                ticker_symbol,
+                quote,
+                source="fallback",
+                error=str(exc),
+            )
+            await self.cache.set_json(cache_key, payload)
+            return payload
+
+    async def get_options_chain_for_expiry(
+        self, symbol: str | None = None, expiry: str | None = None
+    ) -> dict[str, Any]:
+        ticker_symbol = (symbol or self.default_underlying).upper()
+        expirations_data = await self.get_option_expirations(ticker_symbol)
+        expirations = list(expirations_data.get("expirations") or [])
+        target_expiry = expiry or (expirations[0] if expirations else None)
+        quote = await self.get_quote(ticker_symbol)
+
+        if not target_expiry:
+            return self._fallback_options_chain(
+                ticker_symbol,
+                quote,
+                expirations=expirations,
+                selected_expiry=None,
+                source=expirations_data.get("source", quote.get("source", "fallback")),
+                error=expirations_data.get("error"),
+            )
+
+        cache_key = f"options:{ticker_symbol}:{target_expiry}"
+        cached = await self.cache.get_json(cache_key)
+        if cached and isinstance(cached, dict):
+            malformed_list_shape = any(
+                not isinstance(cached.get(field), list) and cached.get(field) is not None
+                for field in ("expirations", "calls", "puts", "rows")
+            )
+            try:
+                normalized_cached = self._normalize_options_chain_payload(cached, ticker_symbol)
+            except ValueError as exc:
+                logger.warning(
+                    "Discarding cached options chain payload for %s %s: %s", ticker_symbol, target_expiry, exc
+                )
+                normalized_cached = None
+            if malformed_list_shape:
+                logger.warning(
+                    "Discarding malformed cached options chain payload for %s %s", ticker_symbol, target_expiry
+                )
+                normalized_cached = None
+            if normalized_cached is not None:
+                if normalized_cached != cached:
+                    await self.cache.set_json(cache_key, normalized_cached)
+                return normalized_cached
+
+        # GC=F options not yet implemented - return placeholder
+        if ticker_symbol == "GC=F":
+            payload = self._fallback_options_chain(
+                ticker_symbol,
+                quote,
+                expirations=expirations,
+                selected_expiry=target_expiry,
+                source="placeholder",
+                error="Options data for GC=F coming soon",
+            )
+            await self.cache.set_json(cache_key, payload)
+            return payload
+
+        if yf is None:
+            payload = self._fallback_options_chain(
+                ticker_symbol,
+                quote,
+                expirations=expirations,
+                selected_expiry=target_expiry,
+                source="fallback",
+                error="yfinance is not installed",
+            )
+            await self.cache.set_json(cache_key, payload)
+            return payload
+
+        try:
+            ticker = yf.Ticker(ticker_symbol)
+            chain = await asyncio.to_thread(ticker.option_chain, target_expiry)
+            calls = self._normalize_option_rows(chain.calls, ticker_symbol, target_expiry, "call", quote["price"])
+            puts = self._normalize_option_rows(chain.puts, ticker_symbol, target_expiry, "put", quote["price"])
+
+            if not calls and not puts:
+                payload = self._fallback_options_chain(
+                    ticker_symbol,
+                    quote,
+                    expirations=expirations,
+                    selected_expiry=target_expiry,
+                    source="fallback",
+                    error="No option contracts returned by yfinance",
+                )
+                await self.cache.set_json(cache_key, payload)
+                return payload
+
+            payload = self._normalize_options_chain_payload(
                 {
-                    "strike": round(base_price * 1.10, 2),
+                    "symbol": ticker_symbol,
-                    "premium": round(base_price * 0.02, 2),
+                    "selected_expiry": target_expiry,
-                    "expiry": "2026-09-18",
+                    "updated_at": datetime.now(timezone.utc).isoformat(),
+                    "expirations": expirations,
+                    "calls": calls,
+                    "puts": puts,
+                    "rows": sorted(calls + puts, key=lambda row: (row["strike"], row["type"])),
+                    "underlying_price": quote["price"],
+                    "source": "yfinance",
                 },
-            ],
+                ticker_symbol,
-            "puts": [
+            )
-                {
+            await self.cache.set_json(cache_key, payload)
-                    "strike": round(base_price * 0.95, 2),
+            return payload
-                    "premium": round(base_price * 0.028, 2),
+        except Exception as exc:  # pragma: no cover - network dependent
-                    "expiry": "2026-06-19",
+            logger.warning(
-                },
+                "Failed to fetch options chain for %s %s from yfinance: %s", ticker_symbol, target_expiry, exc
-                {
+            )
-                    "strike": round(base_price * 0.90, 2),
+            payload = self._fallback_options_chain(
-                    "premium": round(base_price * 0.018, 2),
+                ticker_symbol,
-                    "expiry": "2026-09-18",
+                quote,
-                },
+                expirations=expirations,
-            ],
+                selected_expiry=target_expiry,
-            "source": quote["source"],
+                source="fallback",
+                error=str(exc),
+            )
+            await self.cache.set_json(cache_key, payload)
+            return payload
+
+    async def get_options_chain(self, symbol: str | None = None) -> dict[str, Any]:
+        ticker_symbol = (symbol or self.default_symbol).upper()
+        expirations_data = await self.get_option_expirations(ticker_symbol)
+        expirations = list(expirations_data.get("expirations") or [])
+        if not expirations:
+            quote = await self.get_quote(ticker_symbol)
+            return self._fallback_options_chain(
+                ticker_symbol,
+                quote,
+                expirations=[],
+                selected_expiry=None,
+                source=expirations_data.get("source", quote.get("source", "fallback")),
+                error=expirations_data.get("error"),
+            )
+        return await self.get_options_chain_for_expiry(ticker_symbol, expirations[0])
+
+    async def get_gc_futures(self) -> dict[str, Any]:
+        """Fetch GC=F (COMEX Gold Futures) quote.
+
+        Returns a quote dict similar to get_quote but for gold futures.
+        Falls back gracefully if GC=F is unavailable.
+        """
+        cache_key = f"quote:{self.gc_f_symbol}"
+        cached = await self.cache.get_json(cache_key)
+        if cached and isinstance(cached, dict):
+            try:
+                normalized_cached = self._normalize_quote_payload(cached, self.gc_f_symbol)
+            except ValueError:
+                normalized_cached = None
+            if normalized_cached is not None:
+                if normalized_cached != cached:
+                    await self.cache.set_json(cache_key, normalized_cached)
+                return normalized_cached
+
+        quote = self._normalize_quote_payload(await self._fetch_gc_futures(), self.gc_f_symbol)
+        await self.cache.set_json(cache_key, quote)
+        return quote
+
+    async def _fetch_gc_futures(self) -> dict[str, Any]:
+        """Fetch GC=F from yfinance with graceful fallback."""
+        if yf is None:
+            return self._fallback_gc_futures(source="fallback", error="yfinance is not installed")
+
+        try:
+            ticker = yf.Ticker(self.gc_f_symbol)
+            history = await asyncio.to_thread(ticker.history, period="5d", interval="1d")
+            if history.empty:
+                return self._fallback_gc_futures(source="fallback", error="No history returned for GC=F")
+
+            closes = history["Close"]
+            last = float(closes.iloc[-1])
+            previous = float(closes.iloc[-2]) if len(closes) > 1 else last
+            change = round(last - previous, 4)
+            change_percent = round((change / previous) * 100, 4) if previous else 0.0
+
+            # Try to get more recent price from fast_info if available
+            try:
+                fast_price = ticker.fast_info.get("lastPrice", last)
+                if fast_price and fast_price > 0:
+                    last = float(fast_price)
+            except Exception:
+                pass  # Keep history close if fast_info unavailable
+
+            return {
+                "symbol": self.gc_f_symbol,
+                "price": round(last, 4),
+                "quote_unit": "ozt",  # Gold futures are per troy ounce
+                "change": change,
+                "change_percent": change_percent,
+                "updated_at": datetime.now(timezone.utc).isoformat(),
+                "source": "yfinance",
+            }
+        except Exception as exc:  # pragma: no cover - network dependent
+            logger.warning("Failed to fetch %s from yfinance: %s", self.gc_f_symbol, exc)
+            return self._fallback_gc_futures(source="fallback", error=str(exc))
+
+    @staticmethod
+    def _fallback_gc_futures(source: str, error: str | None = None) -> dict[str, Any]:
+        """Fallback GC=F quote when live data unavailable."""
+        payload = {
+            "symbol": "GC=F",
+            "price": 2700.0,  # Fallback estimate
+            "quote_unit": "ozt",
+            "change": 0.0,
+            "change_percent": 0.0,
+            "updated_at": datetime.now(timezone.utc).isoformat(),
+            "source": source,
+        }
+        if error:
+            payload["error"] = error
+        return payload
+
+    async def get_basis_data(self) -> dict[str, Any]:
+        """Get GLD/GC=F basis data for comparison.
+
+        Returns:
+            Dict with GLD implied spot, GC=F adjusted price, basis in bps, and status info.
+        """
+        gld_quote = await self.get_quote("GLD")
+        gc_f_quote = await self.get_gc_futures()
+
+        # Use current date for GLD ounces calculation
+        ounces_per_share = float(gld_ounces_per_share(date.today()))
+
+        # GLD implied spot = GLD_price / ounces_per_share
+        gld_price = gld_quote.get("price", 0.0)
+        gld_implied_spot = gld_price / ounces_per_share if ounces_per_share > 0 and gld_price > 0 else 0.0
+
+        # GC=F adjusted = (GC=F - contango_estimate) / 10 for naive comparison
+        # But actually GC=F is already per oz, so we just adjust for contango
+        gc_f_price = gc_f_quote.get("price", 0.0)
+        contango_estimate = 10.0  # Typical contango ~$10/oz
+        gc_f_adjusted = gc_f_price - contango_estimate if gc_f_price > 0 else 0.0
+
+        # Basis in bps = (GLD_implied_spot / GC=F_adjusted - 1) * 10000
+        basis_bps = 0.0
+        if gc_f_adjusted > 0 and gld_implied_spot > 0:
+            basis_bps = (gld_implied_spot / gc_f_adjusted - 1) * 10000
+
+        # Determine basis status
+        abs_basis = abs(basis_bps)
+        if abs_basis < 25:
+            basis_status = "green"
+            basis_label = "Normal"
+        elif abs_basis < 50:
+            basis_status = "yellow"
+            basis_label = "Elevated"
+        else:
+            basis_status = "red"
+            basis_label = "Warning"
+
+        # After-hours check: compare timestamps
+        gld_updated = gld_quote.get("updated_at", "")
+        gc_f_updated = gc_f_quote.get("updated_at", "")
+        after_hours = False
+        after_hours_note = ""
+
+        try:
+            gld_time = datetime.fromisoformat(gld_updated.replace("Z", "+00:00"))
+            gc_f_time = datetime.fromisoformat(gc_f_updated.replace("Z", "+00:00"))
+            # If GC=F updated much more recently, likely after-hours
+            time_diff = (gc_f_time - gld_time).total_seconds()
+            if time_diff > 3600:  # More than 1 hour difference
+                after_hours = True
+                after_hours_note = "GLD quote may be stale (after-hours)"
+        except Exception:
+            pass
+
+        return {
+            "gld_implied_spot": round(gld_implied_spot, 2),
+            "gld_price": round(gld_price, 2),
+            "gld_ounces_per_share": round(ounces_per_share, 4),
+            "gc_f_price": round(gc_f_price, 2),
+            "gc_f_adjusted": round(gc_f_adjusted, 2),
+            "contango_estimate": contango_estimate,
+            "basis_bps": round(basis_bps, 1),
+            "basis_status": basis_status,
+            "basis_label": basis_label,
+            "after_hours": after_hours,
+            "after_hours_note": after_hours_note,
+            "gld_updated_at": gld_updated,
+            "gc_f_updated_at": gc_f_updated,
+            "gld_source": gld_quote.get("source", "unknown"),
+            "gc_f_source": gc_f_quote.get("source", "unknown"),
         }
-        await self.cache.set_json(cache_key, options_chain)
-        return options_chain
 
     async def get_strategies(self, symbol: str | None = None) -> dict[str, Any]:
         ticker = (symbol or self.default_symbol).upper()
@@ -105,7 +454,7 @@ class DataService:
 
         return {
             "symbol": ticker,
-            "updated_at": datetime.now(UTC).isoformat(),
+            "updated_at": datetime.now(timezone.utc).isoformat(),
             "paper_parameters": {
                 "portfolio_value": engine.portfolio_value,
                 "loan_amount": engine.loan_amount,
@@ -140,22 +489,257 @@ class DataService:
             return {
                 "symbol": symbol,
                 "price": round(last, 4),
+                "quote_unit": "share",
                 "change": change,
                 "change_percent": change_percent,
-                "updated_at": datetime.now(UTC).isoformat(),
+                "updated_at": datetime.now(timezone.utc).isoformat(),
                 "source": "yfinance",
             }
         except Exception as exc:  # pragma: no cover - network dependent
             logger.warning("Failed to fetch %s from yfinance: %s", symbol, exc)
             return self._fallback_quote(symbol, source="fallback")
 
+    def _fallback_option_expirations(
+        self,
+        symbol: str,
+        quote: dict[str, Any],
+        *,
+        source: str,
+        error: str | None = None,
+    ) -> dict[str, Any]:
+        payload = {
+            "symbol": symbol,
+            "updated_at": datetime.now(timezone.utc).isoformat(),
+            "expirations": [],
+            "underlying_price": quote["price"],
+            "source": source,
+        }
+        if error:
+            payload["error"] = error
+        return payload
+
+    def _fallback_options_chain(
+        self,
+        symbol: str,
+        quote: dict[str, Any],
+        *,
+        expirations: list[str],
+        selected_expiry: str | None,
+        source: str,
+        error: str | None = None,
+    ) -> dict[str, Any]:
+        options_chain = {
+            "symbol": symbol,
+            "selected_expiry": selected_expiry,
+            "updated_at": datetime.now(timezone.utc).isoformat(),
+            "expirations": expirations,
+            "calls": [],
+            "puts": [],
+            "rows": [],
+            "underlying_price": quote["price"],
+            "source": source,
+        }
+        if error:
+            options_chain["error"] = error
+        return options_chain
+
+    @staticmethod
+    def _normalize_option_expirations_payload(payload: dict[str, Any], symbol: str) -> dict[str, Any]:
+        """Normalize option expirations payload to explicit contract.
+
+        This is the named boundary adapter between external provider/cache
+        payloads and internal option expirations handling. It ensures:
+
+        - symbol is always present and uppercased
+        - expirations is always a list (empty if None/missing)
+        - Explicit symbol mismatches are rejected (fail-closed)
+
+        Args:
+            payload: Raw expirations dict from cache or provider
+            symbol: Expected symbol (used as fallback if missing from payload)
+
+        Returns:
+            Normalized expirations dict with explicit symbol and list type
+
+        Raises:
+            ValueError: If payload symbol explicitly conflicts with requested symbol
+        """
+        normalized: dict[str, Any] = dict(payload)
+        normalized_symbol = symbol.upper()
+
+        # Ensure symbol is always present and normalized.
+        # Missing symbol is repaired from the requested key; explicit mismatches are rejected.
+        raw_symbol = normalized.get("symbol", normalized_symbol)
+        normalized_payload_symbol = str(raw_symbol).upper() if raw_symbol is not None else normalized_symbol
+        if raw_symbol is not None and normalized_payload_symbol != normalized_symbol:
+            raise ValueError(
+                f"Option expirations symbol mismatch: expected {normalized_symbol}, got {normalized_payload_symbol}"
+            )
+        normalized["symbol"] = normalized_payload_symbol
+
+        # Ensure expirations is always a list
+        expirations = normalized.get("expirations")
+        if not isinstance(expirations, list):
+            logger.warning(
+                "Repairing malformed option expirations payload for %s: expirations was %r",
+                normalized_symbol,
+                type(expirations).__name__,
+            )
+            normalized["expirations"] = []
+
+        return normalized
+
+    @staticmethod
+    def _normalize_options_chain_payload(payload: dict[str, Any], symbol: str) -> dict[str, Any]:
+        """Normalize options chain payload to explicit contract.
+
+        This is the named boundary adapter between external provider/cache
+        payloads and internal options chain handling. It ensures:
+
+        - symbol is always present and uppercased
+        - calls, puts, rows, and expirations are always lists (empty if None/missing)
+        - Explicit symbol mismatches are rejected (fail-closed)
+
+        Args:
+            payload: Raw options chain dict from cache or provider
+            symbol: Expected symbol (used as fallback if missing from payload)
+
+        Returns:
+            Normalized options chain dict with explicit symbol and list types
+
+        Raises:
+            ValueError: If payload symbol explicitly conflicts with requested symbol
+        """
+        normalized: dict[str, Any] = dict(payload)
+        normalized_symbol = symbol.upper()
+
+        # Ensure symbol is always present and normalized.
+        # Missing symbol is repaired from the requested key; explicit mismatches are rejected.
+        raw_symbol = normalized.get("symbol", normalized_symbol)
+        normalized_payload_symbol = str(raw_symbol).upper() if raw_symbol is not None else normalized_symbol
+        if raw_symbol is not None and normalized_payload_symbol != normalized_symbol:
+            raise ValueError(
+                f"Options chain symbol mismatch: expected {normalized_symbol}, got {normalized_payload_symbol}"
+            )
+        normalized["symbol"] = normalized_payload_symbol
+
+        # Ensure list fields are always lists
+        for field in ("expirations", "calls", "puts", "rows"):
+            if not isinstance(normalized.get(field), list):
+                logger.warning(
+                    "Repairing malformed options chain payload for %s: %s was %r",
+                    normalized_symbol,
+                    field,
+                    type(normalized.get(field)).__name__,
+                )
+                normalized[field] = []
+
+        return normalized
+
+    def _normalize_option_rows(
+        self,
+        frame: Any,
+        symbol: str,
+        expiry: str,
+        option_type: str,
+        underlying_price: float,
+    ) -> list[dict[str, Any]]:
+        if frame is None or getattr(frame, "empty", True):
+            return []
+
+        rows: list[dict[str, Any]] = []
+        for item in frame.to_dict(orient="records"):
+            strike = self._safe_float(item.get("strike"))
+            if strike <= 0:
+                continue
+
+            bid = self._safe_float(item.get("bid"))
+            ask = self._safe_float(item.get("ask"))
+            last_price = self._safe_float(item.get("lastPrice"))
+            implied_volatility = self._safe_float(item.get("impliedVolatility"))
+            contract_symbol = str(item.get("contractSymbol") or "").strip()
+
+            row = {
+                "contractSymbol": contract_symbol,
+                "symbol": contract_symbol or f"{symbol} {expiry} {option_type.upper()} {strike:.2f}",
+                "strike": strike,
+                "bid": bid,
+                "ask": ask,
+                "premium": last_price or self._midpoint(bid, ask),
+                "lastPrice": last_price,
+                "impliedVolatility": implied_volatility,
+                "expiry": expiry,
+                "type": option_type,
+                "openInterest": int(self._safe_float(item.get("openInterest"))),
+                "volume": int(self._safe_float(item.get("volume"))),
+            }
+            row.update(option_row_greeks(row, underlying_price))
+            rows.append(row)
+        return rows
+
+    @staticmethod
+    def _safe_float(value: Any) -> float:
+        try:
+            result = float(value)
+        except (TypeError, ValueError):
+            return 0.0
+        return 0.0 if math.isnan(result) else result
+
+    @staticmethod
+    def _midpoint(bid: float, ask: float) -> float:
+        if bid > 0 and ask > 0:
+            return round((bid + ask) / 2, 4)
+        return max(bid, ask, 0.0)
+
+    @staticmethod
+    def _normalize_quote_payload(payload: dict[str, Any], symbol: str) -> dict[str, Any]:
+        """Normalize provider/cache quote payload to explicit contract.
+
+        This is the named boundary adapter between external float-heavy provider
+        payloads and internal quote handling. It ensures:
+
+        - symbol is always present and uppercased
+        - GLD quotes have explicit quote_unit='share' metadata
+        - Non-GLD symbols pass through without auto-assigned units
+
+        Fail-closed: missing/invalid fields are preserved for upstream handling
+        rather than silently defaulted. Type conversion is not performed here.
+
+        Args:
+            payload: Raw quote dict from cache or provider (float-heavy)
+            symbol: Expected symbol (used as fallback if missing from payload)
+
+        Returns:
+            Normalized quote dict with explicit symbol and GLD quote_unit
+        """
+        normalized: dict[str, Any] = dict(payload)
+        normalized_symbol = symbol.upper()
+
+        # Ensure symbol is always present and normalized.
+        # Missing symbol is repaired from the requested key; explicit mismatches are rejected.
+        raw_symbol = normalized.get("symbol", normalized_symbol)
+        normalized_payload_symbol = str(raw_symbol).upper() if raw_symbol is not None else normalized_symbol
+        if raw_symbol is not None and normalized_payload_symbol != normalized_symbol:
+            raise ValueError(
+                f"Quote payload symbol mismatch: expected {normalized_symbol}, got {normalized_payload_symbol}"
+            )
+        normalized["symbol"] = normalized_payload_symbol
+
+        # Add explicit quote_unit for GLD (CORE-002A/B compatibility)
+        # Repair missing or empty unit metadata, but preserve explicit non-empty values
+        if normalized["symbol"] == "GLD" and not normalized.get("quote_unit"):
+            normalized["quote_unit"] = "share"
+
+        return normalized
+
     @staticmethod
     def _fallback_quote(symbol: str, source: str) -> dict[str, Any]:
         return {
             "symbol": symbol,
             "price": 215.0,
+            "quote_unit": "share",
             "change": 0.0,
             "change_percent": 0.0,
-            "updated_at": datetime.now(UTC).isoformat(),
+            "updated_at": datetime.now(timezone.utc).isoformat(),
             "source": source,
         }

app/services/event_comparison_ui.py

@@ -0,0 +1,310 @@
+from __future__ import annotations
+
+from dataclasses import dataclass
+
+from app.models.backtest import BacktestScenario, EventComparisonRanking, EventComparisonReport
+from app.services.backtesting.comparison import EventComparisonService
+from app.services.backtesting.fixture_source import bind_fixture_source, build_event_comparison_fixture_source
+from app.services.backtesting.historical_provider import SyntheticHistoricalProvider
+from app.services.backtesting.input_normalization import normalize_historical_scenario_inputs
+from app.services.event_presets import EventPresetService
+from app.services.strategy_templates import StrategyTemplateService
+
+SUPPORTED_EVENT_COMPARISON_SYMBOL = "GLD"
+
+
+def _validate_initial_collateral(underlying_units: float, entry_spot: float, loan_amount: float) -> None:
+    initial_collateral_value = underlying_units * entry_spot
+    if loan_amount >= initial_collateral_value:
+        raise ValueError(
+            "Historical scenario starts undercollateralized: "
+            f"loan ${loan_amount:,.0f} exceeds initial collateral ${initial_collateral_value:,.0f} "
+            f"at entry spot ${entry_spot:,.2f}. Reduce loan amount or increase underlying units."
+        )
+
+
+EventComparisonFixtureHistoricalPriceSource = build_event_comparison_fixture_source
+
+
+@dataclass(frozen=True)
+class EventComparisonChartSeries:
+    name: str
+    values: tuple[float, ...]
+
+
+@dataclass(frozen=True)
+class EventComparisonChartModel:
+    dates: tuple[str, ...]
+    series: tuple[EventComparisonChartSeries, ...]
+
+
+@dataclass(frozen=True)
+class EventComparisonDrilldownRow:
+    date: str
+    spot_close: float
+    net_portfolio_value: float
+    option_market_value: float
+    realized_option_cashflow: float
+    ltv_unhedged: float
+    ltv_hedged: float
+    margin_call_hedged: bool
+    active_position_ids: tuple[str, ...]
+
+
+@dataclass(frozen=True)
+class EventComparisonDrilldownModel:
+    rank: int
+    template_slug: str
+    template_name: str
+    survived_margin_call: bool
+    margin_call_days_hedged: int
+    total_option_payoff_realized: float
+    hedge_cost: float
+    final_equity: float
+    worst_ltv_hedged: float
+    worst_ltv_date: str | None
+    breach_dates: tuple[str, ...]
+    rows: tuple[EventComparisonDrilldownRow, ...]
+
+
+class EventComparisonPageService:
+    def __init__(
+        self,
+        comparison_service: EventComparisonService | None = None,
+        event_preset_service: EventPresetService | None = None,
+        template_service: StrategyTemplateService | None = None,
+    ) -> None:
+        self.event_preset_service = event_preset_service or EventPresetService()
+        self.template_service = template_service or StrategyTemplateService()
+        if comparison_service is None:
+            provider = bind_fixture_source(
+                SyntheticHistoricalProvider(),
+                build_event_comparison_fixture_source(),
+            )
+            comparison_service = EventComparisonService(
+                provider=provider,
+                event_preset_service=self.event_preset_service,
+                template_service=self.template_service,
+            )
+        self.comparison_service = comparison_service
+
+    def preset_options(self, symbol: str = SUPPORTED_EVENT_COMPARISON_SYMBOL) -> list[dict[str, object]]:
+        return [
+            {
+                "slug": preset.slug,
+                "label": preset.display_name,
+                "description": preset.description,
+                "default_template_slugs": list(preset.scenario_overrides.default_template_slugs),
+            }
+            for preset in self.event_preset_service.list_presets(symbol)
+        ]
+
+    def template_options(self, symbol: str = SUPPORTED_EVENT_COMPARISON_SYMBOL) -> list[dict[str, object]]:
+        return [
+            {
+                "slug": template.slug,
+                "label": template.display_name,
+                "description": template.description,
+            }
+            for template in self.template_service.list_active_templates(symbol)
+        ]
+
+    def default_template_selection(self, preset_slug: str) -> tuple[str, ...]:
+        preset = self.event_preset_service.get_preset(preset_slug)
+        return tuple(preset.scenario_overrides.default_template_slugs)
+
+    def derive_entry_spot(self, *, preset_slug: str, template_slugs: tuple[str, ...]) -> float:
+        if not template_slugs:
+            raise ValueError("Select at least one strategy template.")
+        scenario = self.comparison_service.preview_scenario_from_inputs(
+            preset_slug=preset_slug,
+            template_slugs=template_slugs,
+            underlying_units=1.0,
+            loan_amount=0.0,
+            margin_call_ltv=0.75,
+        )
+        return float(scenario.initial_portfolio.entry_spot)
+
+    def preview_scenario(
+        self,
+        *,
+        preset_slug: str,
+        template_slugs: tuple[str, ...],
+        underlying_units: float,
+        loan_amount: float,
+        margin_call_ltv: float,
+    ) -> BacktestScenario:
+        if not template_slugs:
+            raise ValueError("Select at least one strategy template.")
+        normalized_inputs = normalize_historical_scenario_inputs(
+            underlying_units=underlying_units,
+            loan_amount=loan_amount,
+            margin_call_ltv=margin_call_ltv,
+        )
+        try:
+            scenario = self.comparison_service.preview_scenario_from_inputs(
+                preset_slug=preset_slug,
+                template_slugs=template_slugs,
+                underlying_units=normalized_inputs.underlying_units,
+                loan_amount=normalized_inputs.loan_amount,
+                margin_call_ltv=normalized_inputs.margin_call_ltv,
+            )
+        except ValueError as exc:
+            if str(exc) == "loan_amount must be less than initial collateral value":
+                preset = self.event_preset_service.get_preset(preset_slug)
+                preview = self.comparison_service.provider.load_history(
+                    preset.symbol.strip().upper(),
+                    preset.window_start,
+                    preset.window_end,
+                )
+                if preview:
+                    _validate_initial_collateral(
+                        normalized_inputs.underlying_units,
+                        preview[0].close,
+                        normalized_inputs.loan_amount,
+                    )
+            raise
+        _validate_initial_collateral(
+            normalized_inputs.underlying_units,
+            scenario.initial_portfolio.entry_spot,
+            normalized_inputs.loan_amount,
+        )
+        return scenario
+
+    def run_read_only_comparison(
+        self,
+        *,
+        preset_slug: str,
+        template_slugs: tuple[str, ...],
+        underlying_units: float,
+        loan_amount: float,
+        margin_call_ltv: float,
+    ) -> EventComparisonReport:
+        if not preset_slug:
+            raise ValueError("Preset selection is required")
+        if not template_slugs:
+            raise ValueError("Select at least one strategy template.")
+
+        normalized_inputs = normalize_historical_scenario_inputs(
+            underlying_units=underlying_units,
+            loan_amount=loan_amount,
+            margin_call_ltv=margin_call_ltv,
+        )
+
+        preset = self.event_preset_service.get_preset(preset_slug)
+        normalized_symbol = preset.symbol.strip().upper()
+        if normalized_symbol != SUPPORTED_EVENT_COMPARISON_SYMBOL:
+            raise ValueError("BT-003A event comparison is currently limited to GLD on this page")
+
+        try:
+            preview = self.comparison_service.preview_scenario_from_inputs(
+                preset_slug=preset.slug,
+                template_slugs=template_slugs,
+                underlying_units=normalized_inputs.underlying_units,
+                loan_amount=normalized_inputs.loan_amount,
+                margin_call_ltv=normalized_inputs.margin_call_ltv,
+            )
+        except ValueError as exc:
+            if str(exc) == "loan_amount must be less than initial collateral value":
+                preview_history = self.comparison_service.provider.load_history(
+                    normalized_symbol,
+                    preset.window_start,
+                    preset.window_end,
+                )
+                if preview_history:
+                    _validate_initial_collateral(
+                        normalized_inputs.underlying_units,
+                        preview_history[0].close,
+                        normalized_inputs.loan_amount,
+                    )
+            raise
+        _validate_initial_collateral(
+            normalized_inputs.underlying_units,
+            preview.initial_portfolio.entry_spot,
+            normalized_inputs.loan_amount,
+        )
+        return self.comparison_service.compare_event_from_inputs(
+            preset_slug=preset.slug,
+            template_slugs=template_slugs,
+            underlying_units=normalized_inputs.underlying_units,
+            loan_amount=normalized_inputs.loan_amount,
+            margin_call_ltv=normalized_inputs.margin_call_ltv,
+        )
+
+    @staticmethod
+    def chart_model(report: EventComparisonReport, max_ranked_series: int = 3) -> EventComparisonChartModel:
+        ranked = report.rankings[:max_ranked_series]
+        if not ranked:
+            return EventComparisonChartModel(dates=(), series=())
+        dates = tuple(point.date.isoformat() for point in ranked[0].result.daily_path)
+        series = [
+            EventComparisonChartSeries(
+                name="Unhedged collateral baseline",
+                values=tuple(round(point.underlying_value, 2) for point in ranked[0].result.daily_path),
+            )
+        ]
+        for item in ranked:
+            series.append(
+                EventComparisonChartSeries(
+                    name=item.template_name,
+                    values=tuple(round(point.net_portfolio_value, 2) for point in item.result.daily_path),
+                )
+            )
+        return EventComparisonChartModel(dates=dates, series=tuple(series))
+
+    @staticmethod
+    def drilldown_model(
+        report: EventComparisonReport,
+        *,
+        template_slug: str | None = None,
+    ) -> EventComparisonDrilldownModel:
+        ranking = EventComparisonPageService._select_ranking(report, template_slug=template_slug)
+        daily_path = ranking.result.daily_path
+        worst_ltv_point = max(daily_path, key=lambda point: point.ltv_hedged, default=None)
+        breach_dates = tuple(point.date.isoformat() for point in daily_path if point.margin_call_hedged)
+        return EventComparisonDrilldownModel(
+            rank=ranking.rank,
+            template_slug=ranking.template_slug,
+            template_name=ranking.template_name,
+            survived_margin_call=ranking.survived_margin_call,
+            margin_call_days_hedged=ranking.margin_call_days_hedged,
+            total_option_payoff_realized=ranking.result.summary_metrics.total_option_payoff_realized,
+            hedge_cost=ranking.hedge_cost,
+            final_equity=ranking.final_equity,
+            worst_ltv_hedged=ranking.max_ltv_hedged,
+            worst_ltv_date=worst_ltv_point.date.isoformat() if worst_ltv_point is not None else None,
+            breach_dates=breach_dates,
+            rows=tuple(
+                EventComparisonDrilldownRow(
+                    date=point.date.isoformat(),
+                    spot_close=point.spot_close,
+                    net_portfolio_value=point.net_portfolio_value,
+                    option_market_value=point.option_market_value,
+                    realized_option_cashflow=point.realized_option_cashflow,
+                    ltv_unhedged=point.ltv_unhedged,
+                    ltv_hedged=point.ltv_hedged,
+                    margin_call_hedged=point.margin_call_hedged,
+                    active_position_ids=point.active_position_ids,
+                )
+                for point in daily_path
+            ),
+        )
+
+    @staticmethod
+    def drilldown_options(report: EventComparisonReport) -> dict[str, str]:
+        return {ranking.template_slug: f"#{ranking.rank} — {ranking.template_name}" for ranking in report.rankings}
+
+    @staticmethod
+    def _select_ranking(
+        report: EventComparisonReport,
+        *,
+        template_slug: str | None = None,
+    ) -> EventComparisonRanking:
+        if not report.rankings:
+            raise ValueError("Event comparison report has no ranked results")
+        if template_slug is None:
+            return report.rankings[0]
+        for ranking in report.rankings:
+            if ranking.template_slug == template_slug:
+                return ranking
+        raise ValueError(f"Unknown ranked template: {template_slug}")

app/services/event_presets.py

@@ -0,0 +1,116 @@
+from __future__ import annotations
+
+import json
+from datetime import date
+from pathlib import Path
+
+from app.models.event_preset import EventPreset, EventScenarioOverrides
+
+DEFAULT_EVENT_PRESET_FILE = Path(__file__).resolve().parents[2] / "config" / "event_presets.json"
+
+
+def default_event_presets() -> list[EventPreset]:
+    return [
+        EventPreset(
+            event_preset_id="gld-jan-2024-selloff-v1",
+            slug="gld-jan-2024-selloff",
+            display_name="GLD January 2024 Selloff",
+            symbol="GLD",
+            window_start=date(2024, 1, 2),
+            window_end=date(2024, 1, 8),
+            anchor_date=date(2024, 1, 4),
+            event_type="selloff",
+            tags=("system", "selloff", "macro"),
+            description="Short January 2024 selloff window for deterministic synthetic event comparisons.",
+            scenario_overrides=EventScenarioOverrides(
+                default_template_slugs=(
+                    "protective-put-atm-12m",
+                    "protective-put-95pct-12m",
+                    "protective-put-90pct-12m",
+                    "ladder-50-50-atm-95pct-12m",
+                )
+            ),
+        ),
+        EventPreset(
+            event_preset_id="gld-jan-2024-drawdown-v1",
+            slug="gld-jan-2024-drawdown",
+            display_name="GLD January 2024 Drawdown",
+            symbol="GLD",
+            window_start=date(2024, 1, 2),
+            window_end=date(2024, 1, 8),
+            anchor_date=date(2024, 1, 5),
+            event_type="selloff",
+            tags=("system", "drawdown"),
+            description="January 2024 drawdown preset for deterministic synthetic event comparison runs.",
+            scenario_overrides=EventScenarioOverrides(
+                lookback_days=0,
+                recovery_days=0,
+                default_template_slugs=(
+                    "protective-put-atm-12m",
+                    "ladder-50-50-atm-95pct-12m",
+                    "ladder-33-33-33-atm-95pct-90pct-12m",
+                ),
+            ),
+        ),
+        EventPreset(
+            event_preset_id="gld-jan-2024-stress-window-v1",
+            slug="gld-jan-2024-stress-window",
+            display_name="GLD January 2024 Stress Window",
+            symbol="GLD",
+            window_start=date(2024, 1, 2),
+            window_end=date(2024, 1, 8),
+            anchor_date=None,
+            event_type="stress_test",
+            tags=("system", "stress_test"),
+            description="Stress-window preset with a modest warmup and recovery tail for report scaffolding.",
+            scenario_overrides=EventScenarioOverrides(
+                lookback_days=0,
+                recovery_days=0,
+                default_template_slugs=(
+                    "protective-put-atm-12m",
+                    "protective-put-95pct-12m",
+                ),
+            ),
+        ),
+    ]
+
+
+class FileEventPresetRepository:
+    def __init__(self, path: str | Path = DEFAULT_EVENT_PRESET_FILE) -> None:
+        self.path = Path(path)
+
+    def list_presets(self) -> list[EventPreset]:
+        self._ensure_seeded()
+        payload = json.loads(self.path.read_text())
+        return [EventPreset.from_dict(item) for item in payload.get("presets", [])]
+
+    def get_by_slug(self, slug: str) -> EventPreset | None:
+        return next((preset for preset in self.list_presets() if preset.slug == slug), None)
+
+    def save_all(self, presets: list[EventPreset]) -> None:
+        self.path.parent.mkdir(parents=True, exist_ok=True)
+        payload = {"presets": [preset.to_dict() for preset in presets]}
+        self.path.write_text(json.dumps(payload, indent=2) + "\n")
+
+    def _ensure_seeded(self) -> None:
+        if self.path.exists():
+            return
+        self.save_all(default_event_presets())
+
+
+class EventPresetService:
+    def __init__(self, repository: FileEventPresetRepository | None = None) -> None:
+        self.repository = repository or FileEventPresetRepository()
+
+    def list_presets(self, symbol: str | None = None) -> list[EventPreset]:
+        presets = self.repository.list_presets()
+        if symbol is None:
+            return presets
+        normalized_symbol = symbol.strip().upper()
+        return [preset for preset in presets if preset.symbol.strip().upper() == normalized_symbol]
+
+    def get_preset(self, slug: str) -> EventPreset:
+        preset = self.repository.get_by_slug(slug)
+        if preset is None:
+            raise KeyError(f"Unknown event preset: {slug}")
+        return preset

app/services/ltv_history.py

@@ -0,0 +1,137 @@
+from __future__ import annotations
+
+import csv
+from dataclasses import dataclass
+from datetime import UTC, datetime, timedelta
+from decimal import Decimal
+from io import StringIO
+from typing import Mapping
+
+from app.models.ltv_history import LtvHistoryRepository, LtvSnapshot
+from app.services.boundary_values import boundary_decimal
+
+
+@dataclass(frozen=True)
+class LtvHistoryChartModel:
+    title: str
+    labels: tuple[str, ...]
+    ltv_values: tuple[float, ...]
+    threshold_values: tuple[float, ...]
+
+
+class LtvHistoryService:
+    def __init__(self, repository: LtvHistoryRepository | None = None) -> None:
+        self.repository = repository or LtvHistoryRepository()
+
+    def record_workspace_snapshot(self, workspace_id: str, portfolio: Mapping[str, object]) -> list[LtvSnapshot]:
+        snapshots = self.repository.load(workspace_id)
+        snapshot = self._build_snapshot(portfolio)
+        updated: list[LtvSnapshot] = []
+        replaced = False
+        for existing in snapshots:
+            if existing.snapshot_date == snapshot.snapshot_date:
+                updated.append(snapshot)
+                replaced = True
+            else:
+                updated.append(existing)
+        if not replaced:
+            updated.append(snapshot)
+        updated.sort(key=lambda item: (item.snapshot_date, item.captured_at))
+        self.repository.save(workspace_id, updated)
+        return updated
+
+    @staticmethod
+    def chart_model(
+        snapshots: list[LtvSnapshot],
+        *,
+        days: int,
+        current_margin_threshold: Decimal | float | str | None = None,
+    ) -> LtvHistoryChartModel:
+        if days <= 0:
+            raise ValueError("days must be positive")
+        title = f"{days} Day"
+        if not snapshots:
+            return LtvHistoryChartModel(title=title, labels=(), ltv_values=(), threshold_values=())
+        latest_date = max(datetime.fromisoformat(item.snapshot_date).date() for item in snapshots)
+        cutoff_date = latest_date - timedelta(days=days - 1)
+        filtered = [item for item in snapshots if datetime.fromisoformat(item.snapshot_date).date() >= cutoff_date]
+        threshold = (
+            boundary_decimal(current_margin_threshold, field_name="current_margin_threshold")
+            if current_margin_threshold is not None
+            else filtered[-1].margin_threshold
+        )
+        threshold_value = round(float(threshold * Decimal("100")), 1)
+        return LtvHistoryChartModel(
+            title=title,
+            labels=tuple(item.snapshot_date for item in filtered),
+            ltv_values=tuple(round(float(item.ltv_ratio * Decimal("100")), 1) for item in filtered),
+            threshold_values=tuple(threshold_value for _ in filtered),
+        )
+
+    @staticmethod
+    def export_csv(snapshots: list[LtvSnapshot]) -> str:
+        output = StringIO()
+        writer = csv.DictWriter(
+            output,
+            fieldnames=[
+                "snapshot_date",
+                "captured_at",
+                "ltv_ratio_pct",
+                "margin_threshold_pct",
+                "loan_amount_usd",
+                "collateral_value_usd",
+                "spot_price_usd_per_ozt",
+                "source",
+            ],
+        )
+        writer.writeheader()
+        for snapshot in snapshots:
+            writer.writerow(
+                {
+                    "snapshot_date": snapshot.snapshot_date,
+                    "captured_at": snapshot.captured_at,
+                    "ltv_ratio_pct": f"{float(snapshot.ltv_ratio * Decimal('100')):.1f}",
+                    "margin_threshold_pct": f"{float(snapshot.margin_threshold * Decimal('100')):.1f}",
+                    "loan_amount_usd": _decimal_text(snapshot.loan_amount),
+                    "collateral_value_usd": _decimal_text(snapshot.collateral_value),
+                    "spot_price_usd_per_ozt": _decimal_text(snapshot.spot_price),
+                    "source": snapshot.source,
+                }
+            )
+        return output.getvalue()
+
+    @staticmethod
+    def _build_snapshot(portfolio: Mapping[str, object]) -> LtvSnapshot:
+        captured_at = _normalize_timestamp(str(portfolio.get("quote_updated_at", "")))
+        return LtvSnapshot(
+            snapshot_date=captured_at[:10],
+            captured_at=captured_at,
+            ltv_ratio=boundary_decimal(portfolio.get("ltv_ratio"), field_name="portfolio.ltv_ratio"),
+            margin_threshold=boundary_decimal(
+                portfolio.get("margin_call_ltv"),
+                field_name="portfolio.margin_call_ltv",
+            ),
+            loan_amount=boundary_decimal(portfolio.get("loan_amount"), field_name="portfolio.loan_amount"),
+            collateral_value=boundary_decimal(portfolio.get("gold_value"), field_name="portfolio.gold_value"),
+            spot_price=boundary_decimal(portfolio.get("spot_price"), field_name="portfolio.spot_price"),
+            source=str(portfolio.get("quote_source", "unknown")) or "unknown",
+        )
+
+
+def _normalize_timestamp(value: str) -> str:
+    if value:
+        try:
+            return datetime.fromisoformat(value.replace("Z", "+00:00")).astimezone(UTC).isoformat()
+        except ValueError:
+            pass
+    return datetime.now(UTC).replace(microsecond=0).isoformat()
+
+
+def _decimal_text(value: Decimal) -> str:
+    if value == value.to_integral():
+        return str(value.quantize(Decimal("1")))
+    normalized = value.normalize()
+    exponent = normalized.as_tuple().exponent
+    if isinstance(exponent, int) and exponent < 0:
+        return format(normalized, "f")
+    return str(normalized)

app/services/position_costs.py

@@ -0,0 +1,120 @@
+"""Position cost calculations for premium, spread, and storage costs."""
+
+from __future__ import annotations
+
+from decimal import Decimal
+from typing import Any
+
+from app.models.position import Position
+
+
+def calculate_effective_entry(
+    entry_price: Decimal,
+    purchase_premium: Decimal | None = None,
+) -> Decimal:
+    """Calculate effective entry cost including dealer premium.
+
+    Args:
+        entry_price: Spot price at entry (per unit)
+        purchase_premium: Dealer markup over spot as percentage (e.g., 0.04 for 4%)
+
+    Returns:
+        Effective entry cost per unit
+    """
+    if purchase_premium is None or purchase_premium == 0:
+        return entry_price
+    return entry_price * (Decimal("1") + purchase_premium)
+
+
+def calculate_effective_exit(
+    current_spot: Decimal,
+    bid_ask_spread: Decimal | None = None,
+) -> Decimal:
+    """Calculate effective exit value after bid/ask spread.
+
+    Args:
+        current_spot: Current spot price (per unit)
+        bid_ask_spread: Expected sale discount below spot as percentage (e.g., 0.03 for 3%)
+
+    Returns:
+        Effective exit value per unit
+    """
+    if bid_ask_spread is None or bid_ask_spread == 0:
+        return current_spot
+    return current_spot * (Decimal("1") - bid_ask_spread)
+
+
+def calculate_true_pnl(
+    position: Position,
+    current_spot: Decimal,
+) -> dict[str, Any]:
+    """Calculate true P&L accounting for premium and spread.
+
+    Args:
+        position: Position to calculate P&L for
+        current_spot: Current spot price per unit
+
+    Returns:
+        Dict with paper_pnl, realized_pnl, effective_entry, effective_exit, entry_value, exit_value
+    """
+    # Effective entry cost (includes premium)
+    effective_entry = calculate_effective_entry(position.entry_price, position.purchase_premium)
+
+    # Effective exit value (after spread)
+    effective_exit = calculate_effective_exit(current_spot, position.bid_ask_spread)
+
+    # Paper P&L (without premium/spread)
+    paper_pnl = (current_spot - position.entry_price) * position.quantity
+
+    # True P&L (with premium/spread)
+    true_pnl = (effective_exit - effective_entry) * position.quantity
+
+    # Entry and exit values
+    entry_value = position.entry_price * position.quantity
+    exit_value = current_spot * position.quantity
+
+    return {
+        "paper_pnl": float(paper_pnl),
+        "true_pnl": float(true_pnl),
+        "effective_entry": float(effective_entry),
+        "effective_exit": float(effective_exit),
+        "entry_value": float(entry_value),
+        "exit_value": float(exit_value),
+        "premium_impact": float((position.purchase_premium or 0) * entry_value),
+        "spread_impact": float((position.bid_ask_spread or 0) * exit_value),
+    }
+
+
+def get_default_premium_for_product(
+    underlying: str, product_type: str = "default"
+) -> tuple[Decimal | None, Decimal | None]:
+    """Get default premium/spread for common gold products.
+
+    Args:
+        underlying: Underlying instrument ("GLD", "GC=F", "XAU")
+        product_type: Product type ("default", "coin_1oz", "bar_1kg", "allocated")
+
+    Returns:
+        Tuple of (purchase_premium, bid_ask_spread) or None if not applicable
+    """
+    # GLD/GLDM: ETF is liquid, minimal spread
+    if underlying in ("GLD", "GLDM"):
+        # ETF spread is minimal, premium is 0
+        return Decimal("0"), Decimal("0.001")  # 0% premium, 0.1% spread
+
+    # GC=F: Futures roll costs are handled separately (GCF-001)
+    if underlying == "GC=F":
+        return None, None
+
+    # XAU: Physical gold
+    if underlying == "XAU":
+        defaults = {
+            "default": (Decimal("0.04"), Decimal("0.03")),  # 4% premium, 3% spread
+            "coin_1oz": (Decimal("0.04"), Decimal("0.03")),  # 1oz coins: 4% premium, 3% spread
+            "bar_1kg": (Decimal("0.015"), Decimal("0.015")),  # 1kg bars: 1.5% premium, 1.5% spread
+            "allocated": (Decimal("0.001"), Decimal("0.003")),  # Allocated: 0.1% premium, 0.3% spread
+        }
+        return defaults.get(product_type, defaults["default"])
+
+    # Unknown underlying
+    return None, None

app/services/price_feed.py

@@ -0,0 +1,167 @@
+"""Live price feed service for fetching real-time GLD and other asset prices."""
+
+from __future__ import annotations
+
+import asyncio
+import logging
+import math
+from dataclasses import dataclass
+from datetime import datetime
+
+import yfinance as yf
+
+from app.services.cache import get_cache
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass(frozen=True)
+class PriceData:
+    """Price data for a symbol."""
+
+    symbol: str
+    price: float
+    currency: str
+    timestamp: datetime
+    source: str = "yfinance"
+
+    def __post_init__(self) -> None:
+        normalized_symbol = self.symbol.strip().upper()
+        if not normalized_symbol:
+            raise ValueError("symbol is required")
+        if not math.isfinite(self.price) or self.price <= 0:
+            raise ValueError("price must be a finite positive number")
+        normalized_currency = self.currency.strip().upper()
+        if not normalized_currency:
+            raise ValueError("currency is required")
+        if not isinstance(self.timestamp, datetime):
+            raise TypeError("timestamp must be a datetime")
+        object.__setattr__(self, "symbol", normalized_symbol)
+        object.__setattr__(self, "currency", normalized_currency)
+        object.__setattr__(self, "source", self.source.strip() or "yfinance")
+
+
+class PriceFeed:
+    """Live price feed service using yfinance with Redis caching."""
+
+    CACHE_TTL_SECONDS = 60
+    DEFAULT_SYMBOLS = ["GLD", "TLT", "BTC-USD"]
+
+    def __init__(self):
+        self._cache = get_cache()
+
+    @staticmethod
+    def _required_payload_value(payload: dict[str, object], key: str, *, context: str) -> object:
+        if key not in payload:
+            raise TypeError(f"{context} is missing required field: {key}")
+        return payload[key]
+
+    @classmethod
+    def _normalize_cached_price_payload(cls, payload: object, *, expected_symbol: str) -> PriceData:
+        if not isinstance(payload, dict):
+            raise TypeError("cached price payload must be a plain dict")
+        payload_symbol = str(payload.get("symbol", expected_symbol)).strip().upper()
+        normalized_symbol = expected_symbol.strip().upper()
+        if payload_symbol != normalized_symbol:
+            raise ValueError(f"cached symbol mismatch: {payload_symbol} != {normalized_symbol}")
+        timestamp = cls._required_payload_value(payload, "timestamp", context="cached price payload")
+        if not isinstance(timestamp, str) or not timestamp.strip():
+            raise TypeError("cached timestamp must be a non-empty ISO string")
+        price_val = cls._required_payload_value(payload, "price", context="cached price payload")
+        if not isinstance(price_val, (int, float)):
+            raise TypeError(f"cached price must be numeric, got {type(price_val).__name__}")
+        price = float(price_val)
+        return PriceData(
+            symbol=payload_symbol,
+            price=price,
+            currency=str(payload.get("currency", "USD")),
+            timestamp=datetime.fromisoformat(timestamp),
+            source=str(payload.get("source", "yfinance")),
+        )
+
+    @classmethod
+    def _normalize_provider_price_payload(cls, payload: object, *, expected_symbol: str) -> PriceData:
+        if not isinstance(payload, dict):
+            raise TypeError("provider price payload must be a plain dict")
+        payload_symbol = str(payload.get("symbol", expected_symbol)).strip().upper()
+        normalized_symbol = expected_symbol.strip().upper()
+        if payload_symbol != normalized_symbol:
+            raise ValueError(f"provider symbol mismatch: {payload_symbol} != {normalized_symbol}")
+        timestamp = cls._required_payload_value(payload, "timestamp", context="provider price payload")
+        if not isinstance(timestamp, datetime):
+            raise TypeError("provider timestamp must be a datetime")
+        price_val = cls._required_payload_value(payload, "price", context="provider price payload")
+        if not isinstance(price_val, (int, float)):
+            raise TypeError(f"provider price must be numeric, got {type(price_val).__name__}")
+        price = float(price_val)
+        return PriceData(
+            symbol=payload_symbol,
+            price=price,
+            currency=str(payload.get("currency", "USD")),
+            timestamp=timestamp,
+            source=str(payload.get("source", "yfinance")),
+        )
+
+    @staticmethod
+    def _price_data_to_cache_payload(data: PriceData) -> dict[str, object]:
+        return {
+            "symbol": data.symbol,
+            "price": data.price,
+            "currency": data.currency,
+            "timestamp": data.timestamp.isoformat(),
+            "source": data.source,
+        }
+
+    async def get_price(self, symbol: str) -> PriceData | None:
+        """Get current price for a symbol, with caching."""
+        normalized_symbol = symbol.strip().upper()
+        cache_key = f"price:{normalized_symbol}"
+
+        if self._cache.enabled:
+            cached = await self._cache.get_json(cache_key)
+            if cached is not None:
+                try:
+                    return self._normalize_cached_price_payload(cached, expected_symbol=normalized_symbol)
+                except (TypeError, ValueError) as exc:
+                    logger.warning("Discarding cached price payload for %s: %s", normalized_symbol, exc)
+
+        try:
+            payload = await self._fetch_yfinance(normalized_symbol)
+            if payload is None:
+                return None
+            data = self._normalize_provider_price_payload(payload, expected_symbol=normalized_symbol)
+            if self._cache.enabled:
+                await self._cache.set_json(
+                    cache_key, self._price_data_to_cache_payload(data), ttl=self.CACHE_TTL_SECONDS
+                )
+            return data
+        except Exception as exc:
+            logger.error("Failed to fetch price for %s: %s", normalized_symbol, exc)
+            return None
+
+    async def _fetch_yfinance(self, symbol: str) -> dict[str, object] | None:
+        """Fetch price from yfinance (run in thread pool to avoid blocking)."""
+        loop = asyncio.get_event_loop()
+        return await loop.run_in_executor(None, self._sync_fetch_yfinance, symbol)
+
+    def _sync_fetch_yfinance(self, symbol: str) -> dict[str, object] | None:
+        """Synchronous yfinance fetch."""
+        ticker = yf.Ticker(symbol)
+        hist = ticker.history(period="1d", interval="1m")
+
+        if hist.empty:
+            return None
+        last_price = hist["Close"].iloc[-1]
+        return {
+            "symbol": symbol,
+            "price": float(last_price),
+            "currency": ticker.info.get("currency", "USD"),
+            "timestamp": datetime.utcnow(),
+            "source": "yfinance",
+        }
+
+    async def get_prices(self, symbols: list[str]) -> dict[str, PriceData | None]:
+        """Get prices for multiple symbols concurrently."""
+        tasks = [self.get_price(symbol) for symbol in symbols]
+        results = await asyncio.gather(*tasks)
+        return {symbol: result for symbol, result in zip(symbols, results, strict=True)}

app/services/runtime.py

@@ -0,0 +1,18 @@
+"""Runtime service registry for UI pages and background tasks."""
+
+from __future__ import annotations
+
+from app.services.data_service import DataService
+
+_data_service: DataService | None = None
+
+
+def set_data_service(service: DataService) -> None:
+    global _data_service
+    _data_service = service
+
+
+def get_data_service() -> DataService:
+    if _data_service is None:
+        raise RuntimeError("DataService has not been initialized")
+    return _data_service

app/services/settings_status.py

@@ -0,0 +1,56 @@
+from __future__ import annotations
+
+from dataclasses import dataclass
+from decimal import Decimal
+from typing import Protocol
+
+from app.models.portfolio import PortfolioConfig
+from app.services.boundary_values import boundary_decimal
+
+
+class _SaveStatusConfig(Protocol):
+    entry_basis_mode: str
+    gold_value: float | None
+    entry_price: float | None
+    gold_ounces: float | None
+    current_ltv: float
+    margin_call_price: object
+
+
+@dataclass(frozen=True, slots=True)
+class SaveStatusSnapshot:
+    entry_basis_mode: str
+    gold_value: Decimal
+    entry_price: Decimal
+    gold_ounces: Decimal
+    current_ltv: Decimal
+    margin_call_price: Decimal
+
+
+def _normalize_save_status_snapshot(config: PortfolioConfig | _SaveStatusConfig) -> SaveStatusSnapshot:
+    margin_call_price = config.margin_call_price
+    resolved_margin_call_price = margin_call_price() if callable(margin_call_price) else margin_call_price
+    return SaveStatusSnapshot(
+        entry_basis_mode=config.entry_basis_mode,
+        gold_value=boundary_decimal(config.gold_value, field_name="config.gold_value"),
+        entry_price=boundary_decimal(config.entry_price, field_name="config.entry_price"),
+        gold_ounces=boundary_decimal(config.gold_ounces, field_name="config.gold_ounces"),
+        current_ltv=boundary_decimal(config.current_ltv, field_name="config.current_ltv"),
+        margin_call_price=boundary_decimal(
+            resolved_margin_call_price,
+            field_name="config.margin_call_price",
+        ),
+    )
+
+
+def margin_call_price_value(config: PortfolioConfig | _SaveStatusConfig) -> float:
+    return float(_normalize_save_status_snapshot(config).margin_call_price)
+
+
+def save_status_text(config: PortfolioConfig | _SaveStatusConfig) -> str:
+    snapshot = _normalize_save_status_snapshot(config)
+    return (
+        f"Saved: basis={snapshot.entry_basis_mode}, start=${float(snapshot.gold_value):,.0f}, "
+        f"entry=${float(snapshot.entry_price):,.2f}/oz, weight={float(snapshot.gold_ounces):,.2f} oz, "
+        f"LTV={float(snapshot.current_ltv):.1%}, trigger=${float(snapshot.margin_call_price):,.2f}/oz"
+    )

app/services/storage_costs.py

@@ -0,0 +1,105 @@
+"""Storage cost calculation service for positions with physical storage requirements."""
+
+from __future__ import annotations
+
+from decimal import Decimal
+
+from app.models.position import Position
+
+_DECIMAL_ZERO = Decimal("0")
+_DECIMAL_ONE = Decimal("1")
+_DECIMAL_HUNDRED = Decimal("100")
+_DECIMAL_TWELVE = Decimal("12")
+
+
+def calculate_annual_storage_cost(position: Position, current_value: Decimal) -> Decimal:
+    """Calculate annual storage cost for a single position.
+
+    Args:
+        position: Position with optional storage_cost_basis and storage_cost_period
+        current_value: Current market value of the position (quantity × current_price)
+
+    Returns:
+        Annual storage cost in position's storage_cost_currency (default USD)
+
+    Notes:
+        - If storage_cost_basis is None, returns 0 (no storage cost)
+        - If storage_cost_period is "monthly", annualizes the cost (×12)
+        - If storage_cost_basis is a percentage, applies it to current_value
+        - If storage_cost_basis is a fixed amount, uses it directly
+    """
+    if position.storage_cost_basis is None:
+        return _DECIMAL_ZERO
+
+    basis = position.storage_cost_basis
+    period = position.storage_cost_period or "annual"
+
+    # Determine if basis is a percentage (e.g., 0.12 for 0.12%) or fixed amount
+    # Heuristic: if basis < 1, treat as percentage; otherwise as fixed amount
+    if basis < _DECIMAL_ONE:
+        # Percentage-based cost
+        if period == "monthly":
+            # Monthly percentage, annualize it
+            annual_rate = basis * _DECIMAL_TWELVE
+        else:
+            # Already annual
+            annual_rate = basis
+
+        # Apply percentage to current value
+        return (current_value * annual_rate) / _DECIMAL_HUNDRED
+    else:
+        # Fixed amount
+        if period == "monthly":
+            # Monthly fixed cost, annualize it
+            return basis * _DECIMAL_TWELVE
+        else:
+            # Already annual fixed cost
+            return basis
+
+
+def calculate_total_storage_cost(
+    positions: list[Position],
+    current_values: dict[str, Decimal],
+) -> Decimal:
+    """Calculate total annual storage cost across all positions.
+
+    Args:
+        positions: List of positions with optional storage costs
+        current_values: Mapping of position ID (str) to current market value
+
+    Returns:
+        Total annual storage cost in USD (assumes all positions use USD)
+    """
+    total = _DECIMAL_ZERO
+    for position in positions:
+        current_value = current_values.get(str(position.id), _DECIMAL_ZERO)
+        cost = calculate_annual_storage_cost(position, current_value)
+        total += cost
+    return total
+
+
+def get_default_storage_cost_for_underlying(underlying: str) -> tuple[Decimal | None, str | None]:
+    """Get default storage cost settings for a given underlying instrument.
+
+    Args:
+        underlying: Instrument symbol (e.g., "XAU", "GLD", "GC=F")
+
+    Returns:
+        Tuple of (storage_cost_basis, storage_cost_period) or (None, None) if no default
+
+    Notes:
+        - XAU (physical gold): 0.12% annual for allocated vault storage
+        - GLD: None (expense ratio baked into share price)
+        - GC=F: None (roll costs are the storage analog, handled separately)
+    """
+    if underlying == "XAU":
+        # Physical gold: 0.12% annual storage cost for allocated vault storage
+        return Decimal("0.12"), "annual"
+    elif underlying == "GLD":
+        # GLD: expense ratio is implicit in share price, no separate storage cost
+        return None, None
+    elif underlying == "GC=F":
+        # Futures: roll costs are the storage analog (deferred to GCF-001)
+        return None, None
+    else:
+        return None, None

app/services/strategy_templates.py

@@ -0,0 +1,346 @@
+from __future__ import annotations
+
+import json
+import re
+from pathlib import Path
+from typing import Any
+from uuid import uuid4
+
+from app.models.strategy_template import StrategyTemplate
+from app.strategies.base import BaseStrategy, StrategyConfig
+from app.strategies.laddered_put import LadderedPutStrategy, LadderSpec
+from app.strategies.protective_put import ProtectivePutSpec, ProtectivePutStrategy
+
+CONFIG_TEMPLATE_FILE = Path(__file__).resolve().parents[2] / "config" / "strategy_templates.json"
+DATA_TEMPLATE_FILE = Path("data/strategy_templates.json")
+_SLUGIFY_RE = re.compile(r"[^a-z0-9]+")
+
+
+def default_strategy_templates() -> list[StrategyTemplate]:
+    return [
+        StrategyTemplate.protective_put(
+            template_id="protective-put-atm-12m-v1",
+            slug="protective-put-atm-12m",
+            display_name="Protective Put ATM",
+            description="Full downside protection using a 12-month at-the-money put.",
+            strike_pct=1.0,
+            target_expiry_days=365,
+            tags=("system", "protective_put", "conservative"),
+        ),
+        StrategyTemplate.protective_put(
+            template_id="protective-put-95pct-12m-v1",
+            slug="protective-put-95pct-12m",
+            display_name="Protective Put 95%",
+            description="Lower-cost 12-month protective put using a 95% spot strike.",
+            strike_pct=0.95,
+            target_expiry_days=365,
+            tags=("system", "protective_put", "balanced"),
+        ),
+        StrategyTemplate.protective_put(
+            template_id="protective-put-90pct-12m-v1",
+            slug="protective-put-90pct-12m",
+            display_name="Protective Put 90%",
+            description="Cost-sensitive 12-month protective put using a 90% spot strike.",
+            strike_pct=0.90,
+            target_expiry_days=365,
+            tags=("system", "protective_put", "cost_sensitive"),
+        ),
+        StrategyTemplate.laddered_put(
+            template_id="ladder-50-50-atm-95pct-12m-v1",
+            slug="ladder-50-50-atm-95pct-12m",
+            display_name="Laddered Puts 50/50 ATM + 95%",
+            description="Split hedge evenly across ATM and 95% strike 12-month puts.",
+            strike_pcts=(1.0, 0.95),
+            weights=(0.5, 0.5),
+            target_expiry_days=365,
+            tags=("system", "laddered_put", "balanced"),
+        ),
+        StrategyTemplate.laddered_put(
+            template_id="ladder-33-33-33-atm-95pct-90pct-12m-v1",
+            slug="ladder-33-33-33-atm-95pct-90pct-12m",
+            display_name="Laddered Puts 33/33/33 ATM + 95% + 90%",
+            description="Three-layer 12-month put ladder across ATM, 95%, and 90% strikes.",
+            strike_pcts=(1.0, 0.95, 0.90),
+            weights=(1 / 3, 1 / 3, 1 / 3),
+            target_expiry_days=365,
+            tags=("system", "laddered_put", "cost_sensitive"),
+        ),
+    ]
+
+
+class FileStrategyTemplateRepository:
+    def __init__(
+        self,
+        path: str | Path = DATA_TEMPLATE_FILE,
+        *,
+        seed_path: str | Path | None = CONFIG_TEMPLATE_FILE,
+    ) -> None:
+        self.path = Path(path)
+        self.seed_path = Path(seed_path) if seed_path is not None else None
+
+    def list_templates(self) -> list[StrategyTemplate]:
+        self._ensure_store()
+        defaults = self._seed_templates()
+        payload = json.loads(self.path.read_text())
+        customs = [StrategyTemplate.from_dict(item) for item in payload.get("templates", [])]
+        merged: dict[str, StrategyTemplate] = {template.slug: template for template in defaults}
+        for template in customs:
+            merged[template.slug] = template
+        return list(merged.values())
+
+    def get_by_slug(self, slug: str) -> StrategyTemplate | None:
+        return next((template for template in self.list_templates() if template.slug == slug), None)
+
+    def save_all(self, templates: list[StrategyTemplate]) -> None:
+        self.path.parent.mkdir(parents=True, exist_ok=True)
+        default_slugs = {template.slug for template in self._seed_templates()}
+        payload = {
+            "templates": [
+                template.to_dict()
+                for template in templates
+                if template.slug not in default_slugs or "system" not in template.tags
+            ]
+        }
+        self.path.write_text(json.dumps(payload, indent=2) + "\n")
+
+    def _ensure_store(self) -> None:
+        if self.path.exists():
+            return
+        self.path.parent.mkdir(parents=True, exist_ok=True)
+        self.path.write_text(json.dumps({"templates": []}, indent=2) + "\n")
+
+    def _seed_templates(self) -> list[StrategyTemplate]:
+        if self.seed_path is not None and self.seed_path.exists():
+            payload = json.loads(self.seed_path.read_text())
+            return [StrategyTemplate.from_dict(item) for item in payload.get("templates", [])]
+        return default_strategy_templates()
+
+
+class StrategyTemplateService:
+    def __init__(self, repository: FileStrategyTemplateRepository | None = None) -> None:
+        self.repository = repository or FileStrategyTemplateRepository()
+
+    def list_active_templates(self, underlying_symbol: str = "GLD") -> list[StrategyTemplate]:
+        symbol = underlying_symbol.upper()
+        return [
+            template
+            for template in self.repository.list_templates()
+            if template.status == "active" and template.underlying_symbol.upper() in {symbol, "*"}
+        ]
+
+    def get_template(self, slug: str) -> StrategyTemplate:
+        template = self.repository.get_by_slug(slug)
+        if template is None:
+            raise KeyError(f"Unknown strategy template: {slug}")
+        return template
+
+    def create_custom_template(
+        self,
+        *,
+        display_name: str,
+        template_kind: str,
+        target_expiry_days: int,
+        strike_pcts: tuple[float, ...],
+        weights: tuple[float, ...] | None = None,
+        underlying_symbol: str = "GLD",
+    ) -> StrategyTemplate:
+        name = display_name.strip()
+        if not name:
+            raise ValueError("Template name is required")
+        if target_expiry_days <= 0:
+            raise ValueError("Expiration days must be positive")
+        if not strike_pcts:
+            raise ValueError("At least one strike is required")
+        if any(strike_pct <= 0 for strike_pct in strike_pcts):
+            raise ValueError("Strike percentages must be positive")
+
+        templates = self.repository.list_templates()
+        normalized_name = name.casefold()
+        if any(template.display_name.casefold() == normalized_name for template in templates):
+            raise ValueError("Template name already exists")
+
+        slug = self._slugify(name)
+        if any(template.slug == slug for template in templates):
+            raise ValueError("Template slug already exists; choose a different name")
+
+        template_id = f"custom-{uuid4()}"
+        if template_kind == "protective_put":
+            if len(strike_pcts) != 1:
+                raise ValueError("Protective put builder expects exactly one strike")
+            template = StrategyTemplate.protective_put(
+                template_id=template_id,
+                slug=slug,
+                display_name=name,
+                description=f"Custom {target_expiry_days}-day protective put at {strike_pcts[0] * 100:.0f}% strike.",
+                strike_pct=strike_pcts[0],
+                target_expiry_days=target_expiry_days,
+                underlying_symbol=underlying_symbol,
+                tags=("custom", "protective_put"),
+            )
+        elif template_kind == "laddered_put":
+            if len(strike_pcts) < 2:
+                raise ValueError("Laddered put builder expects at least two strikes")
+            resolved_weights = weights or self._equal_weights(len(strike_pcts))
+            if len(resolved_weights) != len(strike_pcts):
+                raise ValueError("Weights must match the number of strikes")
+            template = StrategyTemplate.laddered_put(
+                template_id=template_id,
+                slug=slug,
+                display_name=name,
+                description=(
+                    f"Custom {target_expiry_days}-day put ladder at "
+                    + ", ".join(f"{strike_pct * 100:.0f}%" for strike_pct in strike_pcts)
+                    + " strikes."
+                ),
+                strike_pcts=strike_pcts,
+                weights=resolved_weights,
+                target_expiry_days=target_expiry_days,
+                underlying_symbol=underlying_symbol,
+                tags=("custom", "laddered_put"),
+            )
+        else:
+            raise ValueError(f"Unsupported strategy type: {template_kind}")
+
+        templates.append(template)
+        self.repository.save_all(templates)
+        return template
+
+    def build_strategy(self, config: StrategyConfig, slug: str) -> BaseStrategy:
+        return self.build_strategy_from_template(config, self.get_template(slug))
+
+    def build_strategy_from_template(self, config: StrategyConfig, template: StrategyTemplate) -> BaseStrategy:
+        months = max(1, round(template.target_expiry_days / 30.4167))
+        if template.template_kind == "protective_put":
+            leg = template.legs[0]
+            return ProtectivePutStrategy(
+                config,
+                ProtectivePutSpec(
+                    label=self._protective_label(leg.strike_rule.value),
+                    strike_pct=leg.strike_rule.value,
+                    months=months,
+                ),
+            )
+        if template.template_kind == "laddered_put":
+            return LadderedPutStrategy(
+                config,
+                LadderSpec(
+                    label=self._ladder_label(template),
+                    weights=tuple(leg.allocation_weight for leg in template.legs),
+                    strike_pcts=tuple(leg.strike_rule.value for leg in template.legs),
+                    months=months,
+                ),
+            )
+        raise ValueError(f"Unsupported template kind: {template.template_kind}")
+
+    def catalog_items(self) -> list[dict[str, Any]]:
+        ui_defaults = {
+            "protective_put_atm": {"estimated_cost": 6.25, "coverage": "High"},
+            "protective_put_otm_95": {"estimated_cost": 4.95, "coverage": "Balanced"},
+            "protective_put_otm_90": {"estimated_cost": 3.7, "coverage": "Cost-efficient"},
+            "laddered_put_50_50_atm_otm95": {
+                "estimated_cost": 4.45,
+                "coverage": "Layered",
+            },
+            "laddered_put_33_33_33_atm_otm95_otm90": {
+                "estimated_cost": 3.85,
+                "coverage": "Layered",
+            },
+        }
+        items: list[dict[str, Any]] = []
+        for template in self.list_active_templates():
+            strategy_name = self.strategy_name(template)
+            downside_put_legs = [
+                {
+                    "allocation_weight": leg.allocation_weight,
+                    "strike_pct": leg.strike_rule.value,
+                }
+                for leg in template.legs
+                if leg.side == "long" and leg.option_type == "put"
+            ]
+            defaults = ui_defaults.get(strategy_name, {}) if "system" in template.tags else {}
+            items.append(
+                {
+                    "name": strategy_name,
+                    "template_slug": template.slug,
+                    "label": template.display_name,
+                    "description": template.description,
+                    "downside_put_legs": downside_put_legs,
+                    "estimated_cost": defaults.get("estimated_cost", self._estimated_cost(template)),
+                    "coverage": defaults.get("coverage", self._coverage_label(template)),
+                }
+            )
+        return items
+
+    def strategy_name(self, template: StrategyTemplate) -> str:
+        strategy = self.build_strategy_from_template(
+            StrategyConfig(portfolio=self._stub_portfolio(), spot_price=1.0, volatility=0.16, risk_free_rate=0.045),
+            template,
+        )
+        return strategy.name
+
+    @staticmethod
+    def _slugify(display_name: str) -> str:
+        slug = _SLUGIFY_RE.sub("-", display_name.strip().lower()).strip("-")
+        if not slug:
+            raise ValueError("Template name must contain letters or numbers")
+        return slug
+
+    @staticmethod
+    def _equal_weights(count: int) -> tuple[float, ...]:
+        if count <= 0:
+            raise ValueError("count must be positive")
+        base = round(1.0 / count, 10)
+        weights = [base for _ in range(count)]
+        weights[-1] = 1.0 - sum(weights[:-1])
+        return tuple(weights)
+
+    @staticmethod
+    def _estimated_cost(template: StrategyTemplate) -> float:
+        weighted_cost = sum(
+            leg.allocation_weight * max(1.1, 6.25 - ((1.0 - leg.strike_rule.value) * 25.5)) for leg in template.legs
+        )
+        expiry_factor = max(0.45, (template.target_expiry_days / 365) ** 0.5)
+        weighted_cost *= expiry_factor
+        if len(template.legs) > 1:
+            weighted_cost *= 0.8
+        return round(weighted_cost, 2)
+
+    @staticmethod
+    def _coverage_label(template: StrategyTemplate) -> str:
+        if len(template.legs) > 1:
+            return "Layered"
+        strike_pct = template.legs[0].strike_rule.value
+        if strike_pct >= 0.99:
+            return "High"
+        if strike_pct >= 0.95:
+            return "Balanced"
+        return "Cost-efficient"
+
+    @staticmethod
+    def _protective_label(strike_pct: float) -> str:
+        if abs(strike_pct - 1.0) < 1e-9:
+            return "ATM"
+        return f"OTM_{int(round(strike_pct * 100))}"
+
+    def _ladder_label(self, template: StrategyTemplate) -> str:
+        weight_labels = "_".join(str(int(round(leg.allocation_weight * 100))) for leg in template.legs)
+        strike_labels = "_".join(self._strike_label(leg.strike_rule.value) for leg in template.legs)
+        return f"{weight_labels}_{strike_labels}"
+
+    @staticmethod
+    def _strike_label(strike_pct: float) -> str:
+        if abs(strike_pct - 1.0) < 1e-9:
+            return "ATM"
+        return f"OTM{int(round(strike_pct * 100))}"
+
+    @staticmethod
+    def _stub_portfolio():
+        from app.models.portfolio import LombardPortfolio
+
+        return LombardPortfolio(
+            gold_ounces=1.0,
+            gold_price_per_ounce=1.0,
+            loan_amount=0.5,
+            initial_ltv=0.5,
+            margin_call_ltv=0.75,
+        )

app/services/turnstile.py

@@ -0,0 +1,92 @@
+from __future__ import annotations
+
+import logging
+import os
+from dataclasses import dataclass
+
+import requests
+
+TURNSTILE_VERIFY_URL = "https://challenges.cloudflare.com/turnstile/v0/siteverify"
+DEFAULT_TURNSTILE_TEST_SITE_KEY = "1x00000000000000000000AA"
+DEFAULT_TURNSTILE_TEST_SECRET_KEY = "1x0000000000000000000000000000000AA"
+ALWAYS_FAIL_TURNSTILE_TEST_SITE_KEY = "2x00000000000000000000AB"
+ALWAYS_FAIL_TURNSTILE_TEST_SECRET_KEY = "2x0000000000000000000000000000000AA"
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass(frozen=True)
+class TurnstileSettings:
+    site_key: str
+    secret_key: str
+    enabled: bool
+    uses_test_keys: bool
+
+
+def _environment() -> str:
+    return os.getenv("APP_ENV", os.getenv("ENVIRONMENT", "development")).lower()
+
+
+def load_turnstile_settings() -> TurnstileSettings:
+    site_key = os.getenv("TURNSTILE_SITE_KEY", "")
+    secret_key = os.getenv("TURNSTILE_SECRET_KEY", "")
+    enabled = os.getenv("TURNSTILE_ENABLED", "true").lower() not in {"0", "false", "no"}
+    env = _environment()
+
+    known_test_pairs = {
+        (DEFAULT_TURNSTILE_TEST_SITE_KEY, DEFAULT_TURNSTILE_TEST_SECRET_KEY),
+        (ALWAYS_FAIL_TURNSTILE_TEST_SITE_KEY, ALWAYS_FAIL_TURNSTILE_TEST_SECRET_KEY),
+    }
+
+    if env == "test":
+        if (site_key, secret_key) not in known_test_pairs:
+            if site_key or secret_key:
+                logger.info("Ignoring configured Turnstile credentials in test environment and using test keys")
+            site_key = DEFAULT_TURNSTILE_TEST_SITE_KEY
+            secret_key = DEFAULT_TURNSTILE_TEST_SECRET_KEY
+    elif not site_key or not secret_key:
+        if env == "development":
+            site_key = site_key or DEFAULT_TURNSTILE_TEST_SITE_KEY
+            secret_key = secret_key or DEFAULT_TURNSTILE_TEST_SECRET_KEY
+        else:
+            raise RuntimeError("Turnstile keys must be configured outside development/test environments")
+
+    uses_test_keys = site_key == DEFAULT_TURNSTILE_TEST_SITE_KEY and secret_key == DEFAULT_TURNSTILE_TEST_SECRET_KEY
+    return TurnstileSettings(
+        site_key=site_key,
+        secret_key=secret_key,
+        enabled=enabled,
+        uses_test_keys=uses_test_keys,
+    )
+
+
+def verify_turnstile_token(token: str, remote_ip: str | None = None) -> bool:
+    settings = load_turnstile_settings()
+    if not settings.enabled:
+        return True
+    if not token.strip():
+        return False
+    if _environment() == "test":
+        if (
+            settings.site_key == ALWAYS_FAIL_TURNSTILE_TEST_SITE_KEY
+            and settings.secret_key == ALWAYS_FAIL_TURNSTILE_TEST_SECRET_KEY
+        ):
+            return False
+        if settings.uses_test_keys:
+            return True
+    try:
+        response = requests.post(
+            TURNSTILE_VERIFY_URL,
+            data={
+                "secret": settings.secret_key,
+                "response": token,
+                "remoteip": remote_ip or "",
+            },
+            timeout=10,
+        )
+        response.raise_for_status()
+        payload = response.json()
+    except (requests.RequestException, ValueError) as exc:
+        logger.warning("Turnstile verification failed: %s", exc)
+        return False
+    return bool(payload.get("success"))

app/strategies/__init__.py

@@ -1,5 +1,4 @@
 from .base import BaseStrategy, StrategyConfig
-from .engine import StrategySelectionEngine
 from .laddered_put import LadderedPutStrategy, LadderSpec
 from .lease import LeaseAnalysisSpec, LeaseStrategy
 from .protective_put import ProtectivePutSpec, ProtectivePutStrategy
@@ -15,3 +14,11 @@ __all__ = [
     "LeaseStrategy",
     "StrategySelectionEngine",
 ]
+
+
+def __getattr__(name: str):
+    if name == "StrategySelectionEngine":
+        from .engine import StrategySelectionEngine
+
+        return StrategySelectionEngine
+    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")

app/strategies/engine.py

@@ -9,10 +9,9 @@ from app.core.pricing.black_scholes import (
     DEFAULT_VOLATILITY,
 )
 from app.models.portfolio import LombardPortfolio
+from app.services.strategy_templates import StrategyTemplateService
 from app.strategies.base import BaseStrategy, StrategyConfig
-from app.strategies.laddered_put import LadderedPutStrategy, LadderSpec
 from app.strategies.lease import LeaseStrategy
-from app.strategies.protective_put import ProtectivePutSpec, ProtectivePutStrategy
 
 RiskProfile = Literal["conservative", "balanced", "cost_sensitive"]
 
@@ -34,6 +33,7 @@ class StrategySelectionEngine:
     spot_price: float = RESEARCH_GLD_SPOT
     volatility: float = RESEARCH_VOLATILITY
     risk_free_rate: float = RESEARCH_RISK_FREE_RATE
+    template_service: StrategyTemplateService | None = None
 
     def _config(self) -> StrategyConfig:
         portfolio = LombardPortfolio(
@@ -52,30 +52,12 @@ class StrategySelectionEngine:
 
     def _strategies(self) -> list[BaseStrategy]:
         config = self._config()
-        return [
+        template_service = self.template_service or StrategyTemplateService()
-            ProtectivePutStrategy(config, ProtectivePutSpec(label="ATM", strike_pct=1.0, months=12)),
+        template_strategies = [
-            ProtectivePutStrategy(config, ProtectivePutSpec(label="OTM_95", strike_pct=0.95, months=12)),
+            template_service.build_strategy_from_template(config, template)
-            ProtectivePutStrategy(config, ProtectivePutSpec(label="OTM_90", strike_pct=0.90, months=12)),
+            for template in template_service.list_active_templates("GLD")
-            LadderedPutStrategy(
-                config,
-                LadderSpec(
-                    label="50_50_ATM_OTM95",
-                    weights=(0.5, 0.5),
-                    strike_pcts=(1.0, 0.95),
-                    months=12,
-                ),
-            ),
-            LadderedPutStrategy(
-                config,
-                LadderSpec(
-                    label="33_33_33_ATM_OTM95_OTM90",
-                    weights=(1 / 3, 1 / 3, 1 / 3),
-                    strike_pcts=(1.0, 0.95, 0.90),
-                    months=12,
-                ),
-            ),
-            LeaseStrategy(config),
         ]
+        return [*template_strategies, LeaseStrategy(config)]
 
     def compare_all_strategies(self) -> list[dict]:
         comparisons: list[dict] = []
@@ -149,6 +131,7 @@ class StrategySelectionEngine:
                 spot_price=self.spot_price,
                 volatility=volatility,
                 risk_free_rate=self.risk_free_rate,
+                template_service=self.template_service,
             )
             recommendation = engine.recommend("balanced")
             results["volatility"].append(
@@ -169,6 +152,7 @@ class StrategySelectionEngine:
                 spot_price=spot_price,
                 volatility=DEFAULT_VOLATILITY,
                 risk_free_rate=DEFAULT_RISK_FREE_RATE,
+                template_service=self.template_service,
             )
             recommendation = engine.recommend("balanced")
             results["spot_price"].append(

app/strategies/laddered_put.py

@@ -3,10 +3,13 @@ from __future__ import annotations
 from dataclasses import dataclass
 
 from app.strategies.base import BaseStrategy, StrategyConfig
+
+# Re-export for test access
 from app.strategies.protective_put import (
     DEFAULT_SCENARIO_CHANGES,
     ProtectivePutSpec,
     ProtectivePutStrategy,
+    gld_ounces_per_share,  # noqa: F401
 )
 
 
@@ -87,7 +90,7 @@ class LadderedPutStrategy(BaseStrategy):
             contract = leg.build_contract()
             weighted_payoff = contract.payoff(threshold_price) * weight
             total_payoff += weighted_payoff
-            floor_value += contract.strike * leg.hedge_units * weight
+            floor_value += contract.strike * contract.notional_units * weight
             leg_protection.append(
                 {
                     "weight": weight,

app/strategies/protective_put.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import math
 from dataclasses import dataclass
 from datetime import date, timedelta
 
@@ -7,6 +8,7 @@ from app.core.pricing.black_scholes import (
     BlackScholesInputs,
     black_scholes_price_and_greeks,
 )
+from app.domain.instruments import gld_ounces_per_share
 from app.models.option import Greeks, OptionContract
 from app.models.strategy import HedgingStrategy
 from app.strategies.base import BaseStrategy, StrategyConfig
@@ -47,7 +49,8 @@ class ProtectivePutStrategy(BaseStrategy):
 
     @property
     def hedge_units(self) -> float:
-        return self.config.portfolio.gold_value / self.config.spot_price
+        """Gold ounces to hedge (canonical portfolio weight)."""
+        return self.config.portfolio.gold_ounces
 
     @property
     def strike(self) -> float:
@@ -57,6 +60,20 @@ class ProtectivePutStrategy(BaseStrategy):
     def term_years(self) -> float:
         return self.spec.months / 12.0
 
+    @property
+    def gld_backing(self) -> float:
+        """GLD ounces per share for contract count calculation."""
+        return float(gld_ounces_per_share())
+
+    @property
+    def contract_count(self) -> int:
+        """Number of GLD option contracts needed.
+
+        GLD options cover 100 shares each. Each share represents ~0.0919 oz
+        (expense-ratio adjusted). Formula: ceil(gold_ounces / (100 * backing)).
+        """
+        return math.ceil(self.hedge_units / (100 * self.gld_backing))
+
     def build_contract(self) -> OptionContract:
         pricing = black_scholes_price_and_greeks(
             BlackScholesInputs(
@@ -73,8 +90,8 @@ class ProtectivePutStrategy(BaseStrategy):
             strike=self.strike,
             expiry=date.today() + timedelta(days=max(1, round(365 * self.term_years))),
             premium=pricing.price,
-            quantity=1.0,
+            quantity=float(self.contract_count),
-            contract_size=self.hedge_units,
+            contract_size=100 * self.gld_backing,
             underlying_price=self.config.spot_price,
             greeks=Greeks(
                 delta=pricing.delta,
@@ -114,7 +131,7 @@ class ProtectivePutStrategy(BaseStrategy):
         payoff_at_threshold = contract.payoff(threshold_price)
         hedged_value_at_threshold = self.config.portfolio.gold_value_at_price(threshold_price) + payoff_at_threshold
         protected_ltv = self.config.portfolio.loan_amount / hedged_value_at_threshold
-        floor_value = contract.strike * self.hedge_units
+        floor_value = contract.strike * contract.notional_units
         return {
             "strategy": self.name,
             "threshold_price": round(threshold_price, 2),

config/event_presets.json

@@ -0,0 +1,70 @@
+{
+  "presets": [
+    {
+      "event_preset_id": "gld-jan-2024-selloff-v1",
+      "slug": "gld-jan-2024-selloff",
+      "display_name": "GLD January 2024 Selloff",
+      "symbol": "GLD",
+      "window_start": "2024-01-02",
+      "window_end": "2024-01-08",
+      "anchor_date": "2024-01-04",
+      "event_type": "selloff",
+      "tags": ["system", "selloff", "macro"],
+      "description": "Short January 2024 selloff window for deterministic synthetic event comparisons.",
+      "scenario_overrides": {
+        "lookback_days": null,
+        "recovery_days": null,
+        "default_template_slugs": [
+          "protective-put-atm-12m",
+          "protective-put-95pct-12m",
+          "protective-put-90pct-12m",
+          "ladder-50-50-atm-95pct-12m"
+        ]
+      },
+      "created_at": "2026-03-24T00:00:00+00:00"
+    },
+    {
+      "event_preset_id": "gld-jan-2024-drawdown-v1",
+      "slug": "gld-jan-2024-drawdown",
+      "display_name": "GLD January 2024 Drawdown",
+      "symbol": "GLD",
+      "window_start": "2024-01-02",
+      "window_end": "2024-01-08",
+      "anchor_date": "2024-01-05",
+      "event_type": "selloff",
+      "tags": ["system", "drawdown"],
+      "description": "January 2024 drawdown preset for deterministic synthetic event comparison runs.",
+      "scenario_overrides": {
+        "lookback_days": 0,
+        "recovery_days": 0,
+        "default_template_slugs": [
+          "protective-put-atm-12m",
+          "ladder-50-50-atm-95pct-12m",
+          "ladder-33-33-33-atm-95pct-90pct-12m"
+        ]
+      },
+      "created_at": "2026-03-24T00:00:00+00:00"
+    },
+    {
+      "event_preset_id": "gld-jan-2024-stress-window-v1",
+      "slug": "gld-jan-2024-stress-window",
+      "display_name": "GLD January 2024 Stress Window",
+      "symbol": "GLD",
+      "window_start": "2024-01-02",
+      "window_end": "2024-01-08",
+      "anchor_date": null,
+      "event_type": "stress_test",
+      "tags": ["system", "stress_test"],
+      "description": "Stress-window preset with a modest warmup and recovery tail for report scaffolding.",
+      "scenario_overrides": {
+        "lookback_days": 0,
+        "recovery_days": 0,
+        "default_template_slugs": [
+          "protective-put-atm-12m",
+          "protective-put-95pct-12m"
+        ]
+      },
+      "created_at": "2026-03-24T00:00:00+00:00"
+    }
+  ]
+}

config/strategy_templates.json

@@ -0,0 +1,253 @@
+{
+  "templates": [
+    {
+      "template_id": "protective-put-atm-12m-v1",
+      "slug": "protective-put-atm-12m",
+      "display_name": "Protective Put ATM",
+      "description": "Full downside protection using a 12-month at-the-money put.",
+      "template_kind": "protective_put",
+      "status": "active",
+      "version": 1,
+      "underlying_symbol": "GLD",
+      "contract_mode": "continuous_units",
+      "legs": [
+        {
+          "leg_id": "protective-put-atm-12m-v1-leg-1",
+          "side": "long",
+          "option_type": "put",
+          "allocation_weight": 1.0,
+          "strike_rule": {
+            "rule_type": "spot_pct",
+            "value": 1.0
+          },
+          "target_expiry_days": 365,
+          "quantity_rule": "target_coverage_pct",
+          "target_coverage_pct": 1.0
+        }
+      ],
+      "roll_policy": {
+        "policy_type": "hold_to_expiry",
+        "days_before_expiry": null,
+        "rebalance_on_new_deposit": false
+      },
+      "entry_policy": {
+        "entry_timing": "scenario_start_close",
+        "stagger_days": null
+      },
+      "tags": [
+        "system",
+        "protective_put",
+        "conservative"
+      ],
+      "created_at": "2026-03-24T00:00:00+00:00",
+      "updated_at": "2026-03-24T00:00:00+00:00"
+    },
+    {
+      "template_id": "protective-put-95pct-12m-v1",
+      "slug": "protective-put-95pct-12m",
+      "display_name": "Protective Put 95%",
+      "description": "Lower-cost 12-month protective put using a 95% spot strike.",
+      "template_kind": "protective_put",
+      "status": "active",
+      "version": 1,
+      "underlying_symbol": "GLD",
+      "contract_mode": "continuous_units",
+      "legs": [
+        {
+          "leg_id": "protective-put-95pct-12m-v1-leg-1",
+          "side": "long",
+          "option_type": "put",
+          "allocation_weight": 1.0,
+          "strike_rule": {
+            "rule_type": "spot_pct",
+            "value": 0.95
+          },
+          "target_expiry_days": 365,
+          "quantity_rule": "target_coverage_pct",
+          "target_coverage_pct": 1.0
+        }
+      ],
+      "roll_policy": {
+        "policy_type": "hold_to_expiry",
+        "days_before_expiry": null,
+        "rebalance_on_new_deposit": false
+      },
+      "entry_policy": {
+        "entry_timing": "scenario_start_close",
+        "stagger_days": null
+      },
+      "tags": [
+        "system",
+        "protective_put",
+        "balanced"
+      ],
+      "created_at": "2026-03-24T00:00:00+00:00",
+      "updated_at": "2026-03-24T00:00:00+00:00"
+    },
+    {
+      "template_id": "protective-put-90pct-12m-v1",
+      "slug": "protective-put-90pct-12m",
+      "display_name": "Protective Put 90%",
+      "description": "Cost-sensitive 12-month protective put using a 90% spot strike.",
+      "template_kind": "protective_put",
+      "status": "active",
+      "version": 1,
+      "underlying_symbol": "GLD",
+      "contract_mode": "continuous_units",
+      "legs": [
+        {
+          "leg_id": "protective-put-90pct-12m-v1-leg-1",
+          "side": "long",
+          "option_type": "put",
+          "allocation_weight": 1.0,
+          "strike_rule": {
+            "rule_type": "spot_pct",
+            "value": 0.9
+          },
+          "target_expiry_days": 365,
+          "quantity_rule": "target_coverage_pct",
+          "target_coverage_pct": 1.0
+        }
+      ],
+      "roll_policy": {
+        "policy_type": "hold_to_expiry",
+        "days_before_expiry": null,
+        "rebalance_on_new_deposit": false
+      },
+      "entry_policy": {
+        "entry_timing": "scenario_start_close",
+        "stagger_days": null
+      },
+      "tags": [
+        "system",
+        "protective_put",
+        "cost_sensitive"
+      ],
+      "created_at": "2026-03-24T00:00:00+00:00",
+      "updated_at": "2026-03-24T00:00:00+00:00"
+    },
+    {
+      "template_id": "ladder-50-50-atm-95pct-12m-v1",
+      "slug": "ladder-50-50-atm-95pct-12m",
+      "display_name": "Laddered Puts 50/50 ATM + 95%",
+      "description": "Split hedge evenly across ATM and 95% strike 12-month puts.",
+      "template_kind": "laddered_put",
+      "status": "active",
+      "version": 1,
+      "underlying_symbol": "GLD",
+      "contract_mode": "continuous_units",
+      "legs": [
+        {
+          "leg_id": "ladder-50-50-atm-95pct-12m-v1-leg-1",
+          "side": "long",
+          "option_type": "put",
+          "allocation_weight": 0.5,
+          "strike_rule": {
+            "rule_type": "spot_pct",
+            "value": 1.0
+          },
+          "target_expiry_days": 365,
+          "quantity_rule": "target_coverage_pct",
+          "target_coverage_pct": 1.0
+        },
+        {
+          "leg_id": "ladder-50-50-atm-95pct-12m-v1-leg-2",
+          "side": "long",
+          "option_type": "put",
+          "allocation_weight": 0.5,
+          "strike_rule": {
+            "rule_type": "spot_pct",
+            "value": 0.95
+          },
+          "target_expiry_days": 365,
+          "quantity_rule": "target_coverage_pct",
+          "target_coverage_pct": 1.0
+        }
+      ],
+      "roll_policy": {
+        "policy_type": "hold_to_expiry",
+        "days_before_expiry": null,
+        "rebalance_on_new_deposit": false
+      },
+      "entry_policy": {
+        "entry_timing": "scenario_start_close",
+        "stagger_days": null
+      },
+      "tags": [
+        "system",
+        "laddered_put",
+        "balanced"
+      ],
+      "created_at": "2026-03-24T00:00:00+00:00",
+      "updated_at": "2026-03-24T00:00:00+00:00"
+    },
+    {
+      "template_id": "ladder-33-33-33-atm-95pct-90pct-12m-v1",
+      "slug": "ladder-33-33-33-atm-95pct-90pct-12m",
+      "display_name": "Laddered Puts 33/33/33 ATM + 95% + 90%",
+      "description": "Three-layer 12-month put ladder across ATM, 95%, and 90% strikes.",
+      "template_kind": "laddered_put",
+      "status": "active",
+      "version": 1,
+      "underlying_symbol": "GLD",
+      "contract_mode": "continuous_units",
+      "legs": [
+        {
+          "leg_id": "ladder-33-33-33-atm-95pct-90pct-12m-v1-leg-1",
+          "side": "long",
+          "option_type": "put",
+          "allocation_weight": 0.3333333333333333,
+          "strike_rule": {
+            "rule_type": "spot_pct",
+            "value": 1.0
+          },
+          "target_expiry_days": 365,
+          "quantity_rule": "target_coverage_pct",
+          "target_coverage_pct": 1.0
+        },
+        {
+          "leg_id": "ladder-33-33-33-atm-95pct-90pct-12m-v1-leg-2",
+          "side": "long",
+          "option_type": "put",
+          "allocation_weight": 0.3333333333333333,
+          "strike_rule": {
+            "rule_type": "spot_pct",
+            "value": 0.95
+          },
+          "target_expiry_days": 365,
+          "quantity_rule": "target_coverage_pct",
+          "target_coverage_pct": 1.0
+        },
+        {
+          "leg_id": "ladder-33-33-33-atm-95pct-90pct-12m-v1-leg-3",
+          "side": "long",
+          "option_type": "put",
+          "allocation_weight": 0.3333333333333333,
+          "strike_rule": {
+            "rule_type": "spot_pct",
+            "value": 0.9
+          },
+          "target_expiry_days": 365,
+          "quantity_rule": "target_coverage_pct",
+          "target_coverage_pct": 1.0
+        }
+      ],
+      "roll_policy": {
+        "policy_type": "hold_to_expiry",
+        "days_before_expiry": null,
+        "rebalance_on_new_deposit": false
+      },
+      "entry_policy": {
+        "entry_timing": "scenario_start_close",
+        "stagger_days": null
+      },
+      "tags": [
+        "system",
+        "laddered_put",
+        "cost_sensitive"
+      ],
+      "created_at": "2026-03-24T00:00:00+00:00",
+      "updated_at": "2026-03-24T00:00:00+00:00"
+    }
+  ]
+}

docker-compose.deploy.yml

@@ -15,11 +15,31 @@ services:
       NICEGUI_MOUNT_PATH: ${NICEGUI_MOUNT_PATH:-/}
       NICEGUI_STORAGE_SECRET: ${NICEGUI_STORAGE_SECRET}
       CORS_ORIGINS: ${CORS_ORIGINS:-*}
+      TURNSTILE_SITE_KEY: ${TURNSTILE_SITE_KEY:-}
+      TURNSTILE_SECRET_KEY: ${TURNSTILE_SECRET_KEY:-}
     ports:
       - "${APP_BIND_ADDRESS:-127.0.0.1}:${APP_PORT:-8000}:8000"
+    networks:
+      - default
+      - proxy-net
+    volumes:
+      - vault-dash-data:/app/data
     healthcheck:
-      test: ["CMD", "curl", "-fsS", "http://127.0.0.1:8000/health"]
+      test:
+        [
+          "CMD",
+          "python",
+          "-c",
+          "import sys, urllib.request; urllib.request.urlopen('http://127.0.0.1:8000/health', timeout=3); sys.exit(0)",
+        ]
       interval: 30s
       timeout: 5s
       retries: 5
       start_period: 20s
+
+networks:
+  proxy-net:
+    external: true
+
+volumes:
+  vault-dash-data:

docker-compose.yml

@@ -5,7 +5,7 @@ services:
       dockerfile: Dockerfile
     image: vault-dash:dev
     ports:
-      - "8000:8000"
+      - "8100:8000"
     environment:
       APP_ENV: development
       APP_HOST: 0.0.0.0
@@ -20,6 +20,7 @@ services:
     volumes:
       - ./app:/app/app
       - ./config:/app/config
+      - vault-dash-data:/app/data
     depends_on:
       redis:
         condition: service_healthy
@@ -46,4 +47,5 @@ services:
     restart: unless-stopped
 
 volumes:
+  vault-dash-data:
   redis-data:

docs/BT-002_HISTORICAL_OPTIONS_SNAPSHOT_PROVIDER.md

@@ -0,0 +1,66 @@
+# BT-002 Historical Options Snapshot Provider
+
+## What shipped
+
+BT-002 adds a point-in-time historical options snapshot provider for backtests.
+
+The new provider lives in `app/services/backtesting/historical_provider.py` and plugs into the same `BacktestService` / engine flow as the existing synthetic provider.
+
+## Provider contract
+
+The snapshot provider exposes the same backtest-facing behaviors as the synthetic provider:
+
+- load underlying daily closes for the scenario window
+- validate `ProviderRef`
+- open positions at scenario start using only the entry-day snapshot
+- mark open positions later using the exact same contract identity
+
+This lets backtests swap:
+
+- synthetic pricing: `synthetic_v1 / synthetic_bs_mid`
+- observed snapshot pricing: `daily_snapshots_v1 / snapshot_mid`
+
+## Contract-selection rules
+
+The provider uses explicit, deterministic, point-in-time rules:
+
+1. filter to the entry-day option chain only
+2. keep contracts with expiry at or beyond the target expiry date
+3. choose the nearest eligible expiry
+4. within that expiry, choose the nearest strike to the target strike
+5. on equal-distance strike ties:
+   - puts prefer the higher strike
+   - calls prefer the lower strike
+
+These rules avoid lookahead bias because later snapshots are not consulted for entry selection.
+
+## Daily mark-to-market rules
+
+After entry, the provider marks positions using the exact same `contract_key`.
+
+It does **not** silently substitute a different strike or expiry when the original contract is missing.
+
+Current fallback policy:
+
+1. use the exact same contract from the same-day snapshot
+2. if missing before expiry, carry forward the previous mark for that same contract and emit a warning
+3. if the valuation date is at or after expiry, settle to intrinsic value and close the position
+
+## Data-quality tradeoffs
+
+The current BT-002 slice intentionally keeps the data model simple:
+
+- snapshots are assumed to provide a precomputed daily `mid`
+- the provider does not currently derive mids from bid/ask pairs
+- missing exact-contract marks are explicit warnings, not silent substitutions
+- the engine currently still supports `continuous_units` sizing for snapshot-backed runs
+
+## Known limitations / follow-up
+
+This slice does **not** yet include:
+
+- file-backed or external ingestion of real historical snapshot datasets
+- listed-contract rounding / contract-size-aware position sizing
+- persistent run-status objects beyond template-level warnings
+
+Those follow-ups should remain explicit roadmap work rather than being implied by BT-002.

docs/CORE-001A_DECIMAL_UNITS_ARCHITECTURE.md

@@ -0,0 +1,543 @@
+# CORE-001A Decimal Unit Value Object Architecture
+
+## Scope
+
+This document defines the first implementation slice for:
+
+- **CORE-001** — Explicit Unit/Value Classes for Domain Quantities
+- **CORE-001A** — Decimal Unit Value Object Foundation
+
+The goal is to introduce a small, strict, reusable domain layer that prevents silent unit confusion across portfolio, hedge, and backtesting code.
+
+This slice is intentionally limited to:
+
+- enums / typed constants for currency and weight units
+- immutable Decimal-based value objects
+- explicit conversion methods
+- explicitly allowed arithmetic operators
+- fail-closed defaults for invalid or ambiguous arithmetic
+
+This slice should **not** yet migrate every page or calculation path. That belongs to:
+
+- **CORE-001B** — overview and hedge migration
+- **CORE-001C** — backtests and event-comparison migration
+- **CORE-001D** — persistence / API / integration cleanup
+
+---
+
+## Design goals
+
+1. **Eliminate unit ambiguity by construction.** Values must carry unit metadata.
+2. **Use Decimal for bookkeeping accuracy.** No binary floating point in core domain value objects.
+3. **Fail closed by default.** Arithmetic only works when explicitly defined and unit-safe.
+4. **Keep the first slice small.** Add primitives first, then migrate consumers incrementally.
+5. **Make edge conversions explicit.** Float-heavy libraries remain at the boundaries only.
+
+---
+
+## Core design decisions
+
+### 1. Canonical numeric type: `Decimal`
+
+All domain value objects introduced in this slice should use Python `Decimal` as the canonical numeric representation.
+
+Implementation guidance:
+
+- never construct `Decimal` directly from `float`
+- construct from:
+  - `str`
+  - `int`
+  - existing `Decimal`
+- introduce a small helper such as `to_decimal(value: Decimal | int | str) -> Decimal`
+- if a float enters from an external provider, convert it at the edge using a deliberate helper, e.g. `decimal_from_float(value: float) -> Decimal`
+
+### 2. Immutable value objects
+
+Use frozen dataclasses for predictable behavior and easy testing.
+
+Recommended style:
+
+- `@dataclass(frozen=True, slots=True)`
+- validation in `__post_init__`
+- methods return new values rather than mutating in place
+
+### 3. Unit metadata is mandatory
+
+A raw numeric value without unit/currency metadata must not be considered a domain quantity.
+
+Examples:
+
+- `Money(amount=Decimal("1000"), currency=BaseCurrency.USD)`
+- `GoldQuantity(amount=Decimal("220"), unit=WeightUnit.OUNCE_TROY)`
+- `PricePerWeight(amount=Decimal("4400"), currency=BaseCurrency.USD, per_unit=WeightUnit.OUNCE_TROY)`
+
+### 4. Unsupported operators should fail
+
+Do not make these classes behave like plain numbers.
+
+Examples of operations that should fail unless explicitly defined:
+
+- `Money + GoldQuantity`
+- `GoldQuantity + PricePerWeight`
+- `Money * Money`
+- `PricePerWeight + Money`
+- adding values with different currencies without explicit conversion support
+
+### 5. Explicit conversions only
+
+Unit changes must be requested directly.
+
+Examples:
+
+- `gold.to_unit(WeightUnit.GRAM)`
+- `price.to_unit(WeightUnit.KILOGRAM)`
+- `money.assert_currency(BaseCurrency.USD)`
+
+---
+
+## Proposed module layout
+
+Recommended first location:
+
+- `app/domain/units.py`
+
+Optional supporting files if it grows:
+
+- `app/domain/__init__.py`
+- `app/domain/decimal_utils.py`
+- `app/domain/exceptions.py`
+
+Reasoning:
+
+- this is core domain logic, not page logic
+- it should be usable from models, services, calculations, and backtesting
+- avoid burying it inside `app/models/` if the types are broader than persistence models
+
+---
+
+## Proposed enums
+
+## `BaseCurrency`
+
+```python
+from enum import StrEnum
+
+class BaseCurrency(StrEnum):
+    USD = "USD"
+    EUR = "EUR"
+    CHF = "CHF"
+```
+
+Notes:
+
+- omit `Invalid`; prefer validation failure over sentinel invalid values
+- add currencies only when needed
+
+## `WeightUnit`
+
+```python
+from enum import StrEnum
+
+class WeightUnit(StrEnum):
+    GRAM = "g"
+    KILOGRAM = "kg"
+    OUNCE_TROY = "ozt"
+```
+
+Notes:
+
+- use **troy ounce**, not generic `oz`, because gold math should be explicit
+- naming should be domain-precise to avoid ounce ambiguity
+
+---
+
+## Proposed conversion constants
+
+Use Decimal constants, not floats.
+
+```python
+GRAMS_PER_KILOGRAM = Decimal("1000")
+GRAMS_PER_TROY_OUNCE = Decimal("31.1034768")
+```
+
+Recommended helper:
+
+```python
+def weight_unit_factor(unit: WeightUnit) -> Decimal:
+    ...
+```
+
+Interpretation:
+
+- factor returns grams per given unit
+- conversions can normalize through grams
+
+Example:
+
+```python
+def convert_weight(amount: Decimal, from_unit: WeightUnit, to_unit: WeightUnit) -> Decimal:
+    grams = amount * weight_unit_factor(from_unit)
+    return grams / weight_unit_factor(to_unit)
+```
+
+---
+
+## Proposed value objects
+
+## `Money`
+
+```python
+@dataclass(frozen=True, slots=True)
+class Money:
+    amount: Decimal
+    currency: BaseCurrency
+```
+
+### Allowed operations
+
+- `Money + Money -> Money` if same currency
+- `Money - Money -> Money` if same currency
+- `Money * Decimal -> Money`
+- `Money / Decimal -> Money`
+- unary negation
+- equality on same currency and amount
+
+### Must fail
+
+- addition/subtraction across different currencies
+- multiplication by `Money`
+- addition to non-money quantities
+- division by `Money` unless a future ratio type is added explicitly
+
+### Recommended methods
+
+- `zero(currency: BaseCurrency) -> Money`
+- `assert_currency(currency: BaseCurrency) -> Money`
+- `quantize_cents() -> Money` (optional, for display/persistence edges only)
+
+## `Weight`
+
+Use a neutral weight-bearing quantity rather than a `Gold` type for the foundation layer.
+
+```python
+@dataclass(frozen=True, slots=True)
+class Weight:
+    amount: Decimal
+    unit: WeightUnit
+```
+
+### Allowed operations
+
+- `Weight + Weight -> Weight` after explicit normalization or same-unit conversion inside method
+- `Weight - Weight -> Weight`
+- `Weight * Decimal -> Weight`
+- `Weight / Decimal -> Weight`
+- `to_unit(unit: WeightUnit) -> Weight`
+
+### Must fail
+
+- implicit multiplication with `Weight`
+- addition to `Money`
+- comparison without normalization if not explicitly handled
+
+## `PricePerWeight`
+
+```python
+@dataclass(frozen=True, slots=True)
+class PricePerWeight:
+    amount: Decimal
+    currency: BaseCurrency
+    per_unit: WeightUnit
+```
+
+Interpretation:
+
+- `4400 USD / ozt`
+- `141.46 USD / g`
+
+### Allowed operations
+
+- `PricePerWeight.to_unit(unit: WeightUnit) -> PricePerWeight`
+- `Weight * PricePerWeight -> Money`
+- `PricePerWeight * Weight -> Money`
+- `PricePerWeight * Decimal -> PricePerWeight` (optional; acceptable if useful)
+
+### Must fail
+
+- adding prices of different currencies without explicit conversion
+- adding `PricePerWeight` to `Money`
+- multiplying `PricePerWeight * PricePerWeight`
+
+## `AssetQuantity`
+
+Backtesting currently uses neutral `underlying_units`, while live pages also use physical-gold semantics. For the foundation layer, keep this explicit.
+
+Two viable approaches:
+
+### Option A: only introduce `Weight` in CORE-001A
+
+Pros:
+
+- simpler first slice
+- cleanly solves current gold/spot confusion first
+
+Cons:
+
+- historical `underlying_units` remain primitive a bit longer
+
+### Option B: also introduce a neutral counted-asset quantity
+
+```python
+@dataclass(frozen=True, slots=True)
+class AssetQuantity:
+    amount: Decimal
+    symbol: str
+```
+
+Recommendation:
+
+- **Option A for CORE-001A**
+- defer `AssetQuantity` to CORE-001C where historical scenario boundaries are migrated
+
+---
+
+## Explicit operator design
+
+The main rule is:
+
+> only define operators that are unquestionably unit-safe and domain-obvious.
+
+Recommended first operator set:
+
+```python
+Weight * PricePerWeight -> Money
+PricePerWeight * Weight -> Money
+Money + Money -> Money
+Money - Money -> Money
+Weight + Weight -> Weight
+Weight - Weight -> Weight
+```
+
+Example pseudocode:
+
+```python
+def __mul__(self, other: object) -> Money:
+    if isinstance(other, PricePerWeight):
+        adjusted_price = other.to_unit(self.unit)
+        return Money(
+            amount=self.amount * adjusted_price.amount,
+            currency=adjusted_price.currency,
+        )
+    return NotImplemented
+```
+
+Important note:
+
+- returning `NotImplemented` is correct for unsupported operator pairs
+- if the reverse operation is also unsupported, Python will raise a `TypeError`
+- that is the desired fail-closed behavior
+
+---
+
+## Validation rules
+
+Recommended invariants:
+
+### Money
+
+- currency required
+- amount finite Decimal
+
+### Weight
+
+- unit required
+- amount finite Decimal
+- negative values allowed only if the domain needs them; otherwise reject at construction
+
+Recommendation:
+
+- allow negative values in the primitive type
+- enforce business positivity at higher-level models where appropriate
+
+### PricePerWeight
+
+- currency required
+- per-unit required
+- amount must be non-negative for current use cases
+
+---
+
+## Serialization guidance
+
+For CORE-001A, serialization can remain explicit and boring.
+
+Recommended shape:
+
+```python
+{
+  "amount": "4400.00",
+  "currency": "USD",
+  "per_unit": "ozt"
+}
+```
+
+Guidelines:
+
+- serialize `Decimal` as string, not float
+- keep enum serialization stable and human-readable
+- avoid hidden coercion in JSON helpers
+
+Persistence migration itself belongs primarily to **CORE-001D**, but the foundational classes should be serialization-friendly.
+
+---
+
+## Interop boundaries
+
+Several existing libraries/services are float-heavy:
+
+- yfinance payloads
+- chart libraries
+- some existing calculations in `app/core/`
+- option pricing inputs/outputs
+
+CORE-001A should establish a clear policy:
+
+### Inside the core domain
+
+- use Decimal-bearing unit-safe types
+
+### At external edges
+
+- accept floats only in adapters
+- immediately convert to Decimal-bearing domain types
+- convert back to floats only when required by third-party/chart APIs
+
+Recommended helper names:
+
+- `decimal_from_provider_float(...)`
+- `money_from_float_usd(...)`
+- `price_per_ounce_usd_from_float(...)`
+- `to_chart_float(...)`
+
+The helper names should make the boundary obvious.
+
+---
+
+## Suggested implementation order
+
+### Step 1: add foundational helpers
+
+- `to_decimal(...)`
+- `decimal_from_float(...)`
+- weight conversion constants and helpers
+
+### Step 2: add enums
+
+- `BaseCurrency`
+- `WeightUnit`
+
+### Step 3: add frozen value objects
+
+- `Money`
+- `Weight`
+- `PricePerWeight`
+
+### Step 4: add unit tests first
+
+Test at least:
+
+- `Weight(Decimal("1"), OUNCE_TROY).to_unit(GRAM)`
+- `PricePerWeight(USD/ozt).to_unit(GRAM)`
+- `Weight * PricePerWeight -> Money`
+- `Money + Money` same currency succeeds
+- `Money + Money` different currency fails
+- invalid operator combinations raise `TypeError`
+- decimal construction helpers reject unsafe ambiguous input patterns if desired
+
+### Step 5: add one thin usage seam
+
+Before full migration, wire one small non-invasive helper or calculation path to prove ergonomics.
+
+Recommendation:
+
+- introduce a helper used by the overview quote fallback path or a standalone calculation test first
+- keep page-wide migration for CORE-001B
+
+---
+
+## Proposed first test file
+
+- `tests/test_units.py`
+
+Recommended test groups:
+
+1. Decimal normalization helpers
+2. Weight conversions
+3. Price-per-weight conversions
+4. Unit-safe multiplication
+5. Currency mismatch failures
+6. Unsupported operator failures
+7. Serialization shape helpers if implemented in this slice
+
+---
+
+## Migration notes for later slices
+
+## CORE-001B
+
+Migrate:
+
+- overview spot resolution / fallback
+- margin-call math
+- hedge starting-position math
+- hedge scenario contribution math where unit-bearing values are mixed
+
+## CORE-001C
+
+Migrate:
+
+- workspace `gold_value -> historical underlying_units` conversion
+- backtest scenario portfolio construction
+- event comparison scenario materialization
+- explicit distinction between:
+  - physical gold weight
+  - USD notional collateral value
+  - historical underlying units
+
+## CORE-001D
+
+Clean up:
+
+- persistence schemas
+- API serialization
+- cache payloads
+- third-party provider adapters
+
+---
+
+## Non-goals for CORE-001A
+
+Do not attempt all of this in the first slice:
+
+- full currency FX conversion
+- replacing every float in the app
+- redesigning all existing Pydantic models at once
+- full options contract quantity modeling
+- chart formatting overhaul
+- database migration complexity
+
+---
+
+## Recommendation
+
+Implement `CORE-001A` as a small, strict, test-first domain package introducing:
+
+- `BaseCurrency`
+- `WeightUnit`
+- `Money`
+- `Weight`
+- `PricePerWeight`
+
+all backed by `Decimal`, immutable, with explicit conversions and only a tiny allowed operator surface.
+
+That creates the foundation needed to safely migrate the visible calculation paths in `CORE-001B` and the historical scenario paths in `CORE-001C` without repeating the unit-confusion bugs already discovered in overview and backtesting.

docs/CORE-001D_BOUNDARY_CLEANUP_PLAN.md

@@ -0,0 +1,139 @@
+# CORE-001D Boundary and Persistence Cleanup Plan
+
+## Goal
+Make Decimal/unit-safe domain types reliable at external boundaries without forcing a risky full-model rewrite.
+
+This slice follows:
+- `CORE-001A` Decimal/unit foundations
+- `CORE-001B` overview + hedge migration
+- `CORE-001C` backtests + event comparison migration
+
+## Why this exists
+The visible math paths now use unit-safe domain helpers, but several persistence and adapter seams still store or pass raw floats. That is acceptable at the edge for now, but the boundaries should be explicit, tested, and stable.
+
+## Main hotspots found in the current codebase
+
+### 1. Portfolio persistence still serializes raw floats
+Files:
+- `app/models/portfolio.py`
+- workspace-backed `portfolio_config.json` payloads
+
+Current state:
+- `PortfolioConfig` stores float fields
+- `PortfolioRepository.save/load` round-trips plain JSON numbers
+
+Risk:
+- persistence format is implicit
+- Decimal-safe internal math can be silently rounded or reinterpreted at reload boundaries
+
+### 2. Legacy portfolio/domain types still expose float-heavy APIs
+Files:
+- `app/models/portfolio.py`
+- `app/services/settings_status.py`
+- `app/services/alerts.py`
+
+Current state:
+- `LombardPortfolio` remains float-based for compatibility
+- several services convert Decimal-backed results back to float for formatting/threshold checks
+
+Risk:
+- domain-safe calculations exist, but callers can still drift into ambiguous float semantics
+
+### 3. Backtesting UI/service seams still take float inputs
+Files:
+- `app/services/backtesting/ui_service.py`
+- `app/services/backtesting/comparison.py`
+- `app/services/event_comparison_ui.py`
+- `app/domain/backtesting_math.py`
+
+Current state:
+- typed materialization exists, but service entrypoints still accept `float`
+- conversions back to float happen for model compatibility
+
+Risk:
+- callers can bypass intent and reintroduce unit ambiguity at service boundaries
+
+### 4. Provider/cache adapters use generic JSON and float payloads
+Files:
+- `app/services/cache.py`
+- `app/services/price_feed.py`
+- `app/services/data_service.py`
+- `app/services/backtesting/historical_provider.py`
+
+Current state:
+- cache serialization supports datetime only via custom default
+- provider payloads are mostly raw floats, dicts, and lists
+
+Risk:
+- external payloads are fine to keep float-heavy, but conversion into domain-safe structures should happen at named boundaries and be test-covered
+
+## Recommended implementation order
+
+### Step 1: make persistence format explicit
+Target:
+- `PortfolioConfig` JSON shape
+- workspace portfolio JSON shape
+
+Deliverables:
+- explicit serialization helpers for persisted money/price/weight-like fields
+- tests proving stable round-trip behavior
+- docs for JSON number vs string decisions
+
+Preferred near-term approach:
+- keep external JSON ergonomic
+- document exact persisted field meanings and units
+- ensure reload path normalizes through a single constructor/adapter
+
+### Step 2: add named boundary adapters
+Target:
+- portfolio persistence load/save
+- price feed quote ingestion
+- historical close ingestion
+- options-chain normalization
+
+Deliverables:
+- helper functions with explicit names such as `*_from_provider_payload(...)` or `*_to_persistence_dict(...)`
+- tests proving conversion behavior and fail-closed validation
+
+### Step 3: reduce raw-float service entrypoints where practical
+Target:
+- backtesting UI/comparison service inputs
+- settings/alerts status helpers
+
+Deliverables:
+- services accept typed or normalized values earlier
+- float conversion, where still required, happens at the last compatibility seam
+
+## Non-goals
+- replacing every float in every Pydantic/dataclass immediately
+- redesigning third-party payload models wholesale
+- changing public UI formatting behavior just for type purity
+
+## First candidate sub-slices
+
+### CORE-001D1 — Portfolio persistence serialization seam
+- make `PortfolioConfig` persistence round-trip explicit
+- add serialization tests for workspace-scoped config files
+
+### CORE-001D2 — Provider and cache adapter boundaries
+- document/test cache + provider conversion seams
+- ensure raw external floats are normalized before domain math
+
+### CORE-001D3 — Service entrypoint tightening
+- narrow float-heavy internal service APIs where easy and low-risk
+
+## Success criteria
+- persistence schema for bookkeeping-sensitive fields is explicit and tested
+- Decimal/unit-safe values cross boundaries through named adapters
+- remaining float-heavy hotspots are either removed or intentionally documented as edge-only
+- no regression in existing browser-visible flows
+
+## Pre-launch rollout policy
+For the current pre-launch stage, the storage schema may make a clean breaking transition.
+
+That means:
+- newly persisted numeric domain values should use explicit structured unit-aware storage
+- old flat storage payloads do not need compatibility or migration yet
+- invalid or old-format payloads should fail loudly instead of being silently normalized
+
+A real migration path should be introduced later, once persistence is considered live for users.

docs/DATABENTO_INTEGRATION_PLAN.md

@@ -0,0 +1,780 @@
+# Databento Historical Data Integration Plan
+
+## Overview
+
+Integrate Databento historical API for backtesting and scenario comparison pages, replacing yfinance for historical data on these pages. The integration will support configurable start prices/values independent of portfolio settings, with intelligent caching to avoid redundant downloads.
+
+## Architecture
+
+### Current State
+- **Backtest page** (`app/pages/backtests.py`): Uses `YFinanceHistoricalPriceSource` via `BacktestPageService`
+- **Event comparison** (`app/pages/event_comparison.py`): Uses seeded event presets with yfinance data
+- **Historical provider** (`app/services/backtesting/historical_provider.py`): Protocol-based architecture with `YFinanceHistoricalPriceSource` and `SyntheticHistoricalProvider`
+
+### Target State
+- Add `DatabentoHistoricalPriceSource` implementing `HistoricalPriceSource` protocol
+- Add `DatabentoHistoricalOptionSource` implementing `OptionSnapshotSource` protocol (future)
+- Smart caching layer: only re-download when parameters change
+- Pre-seeded scenario data via batch downloads
+
+## Databento Data Sources
+
+### Underlyings and Datasets
+
+| Instrument | Dataset | Symbol Format | Notes |
+|------------|---------|----------------|-------|
+| GLD ETF | `XNAS.BASIC` or `EQUS.PLUS` | `GLD` | US equities consolidated |
+| GC=F Futures | `GLBX.MDP3` | `GC` + continuous or `GC=F` raw | Gold futures |
+| Gold Options | `OPRA.PILLAR` | `GLD` underlying | Options on GLD ETF |
+
+### Schemas
+
+| Schema | Use Case | Fields |
+|--------|----------|--------|
+| `ohlcv-1d` | Daily backtesting | open, high, low, close, volume |
+| `ohlcv-1h` | Intraday scenarios | Hourly bars |
+| `trades` | Tick-level analysis | Full trade data |
+| `definition` | Instrument metadata | Expiries, strike prices, tick sizes |
+
+## Implementation Plan
+
+### Phase 1: Historical Price Source (DATA-DB-001)
+
+**File:** `app/services/backtesting/databento_source.py`
+
+```python
+from __future__ import annotations
+
+from dataclasses import dataclass
+from datetime import date, timedelta
+from pathlib import Path
+from typing import Any
+import hashlib
+import json
+
+from app.services.backtesting.historical_provider import DailyClosePoint, HistoricalPriceSource
+
+try:
+    import databento as db
+    DATABENTO_AVAILABLE = True
+except ImportError:
+    DATABENTO_AVAILABLE = False
+
+
+@dataclass(frozen=True)
+class DatabentoCacheKey:
+    """Cache key for Databento data requests."""
+    dataset: str
+    symbol: str
+    schema: str
+    start_date: date
+    end_date: date
+    
+    def cache_path(self, cache_dir: Path) -> Path:
+        key_str = f"{self.dataset}_{self.symbol}_{self.schema}_{self.start_date}_{self.end_date}"
+        key_hash = hashlib.sha256(key_str.encode()).hexdigest()[:16]
+        return cache_dir / f"dbn_{key_hash}.parquet"
+    
+    def metadata_path(self, cache_dir: Path) -> Path:
+        key_str = f"{self.dataset}_{self.symbol}_{self.schema}_{self.start_date}_{self.end_date}"
+        key_hash = hashlib.sha256(key_str.encode()).hexdigest()[:16]
+        return cache_dir / f"dbn_{key_hash}_meta.json"
+
+
+@dataclass
+class DatabentoSourceConfig:
+    """Configuration for Databento data source."""
+    api_key: str | None = None  # Falls back to DATABENTO_API_KEY env var
+    cache_dir: Path = Path(".cache/databento")
+    dataset: str = "XNAS.BASIC"
+    schema: str = "ohlcv-1d"
+    stype_in: str = "raw_symbol"
+    
+    # Re-download threshold
+    max_cache_age_days: int = 30
+
+
+class DatabentoHistoricalPriceSource(HistoricalPriceSource):
+    """Databento-based historical price source for backtesting."""
+    
+    def __init__(self, config: DatabentoSourceConfig | None = None) -> None:
+        if not DATABENTO_AVAILABLE:
+            raise RuntimeError("databento package required: pip install databento")
+        
+        self.config = config or DatabentoSourceConfig()
+        self.config.cache_dir.mkdir(parents=True, exist_ok=True)
+        self._client: db.Historical | None = None
+    
+    @property
+    def client(self) -> db.Historical:
+        if self._client is None:
+            self._client = db.Historical(key=self.config.api_key)
+        return self._client
+    
+    def _load_from_cache(self, key: DatabentoCacheKey) -> list[DailyClosePoint] | None:
+        """Load cached data if available and fresh."""
+        cache_file = key.cache_path(self.config.cache_dir)
+        meta_file = key.metadata_path(self.config.cache_dir)
+        
+        if not cache_file.exists() or not meta_file.exists():
+            return None
+        
+        try:
+            with open(meta_file) as f:
+                meta = json.load(f)
+            
+            # Check cache age
+            download_date = date.fromisoformat(meta["download_date"])
+            age_days = (date.today() - download_date).days
+            if age_days > self.config.max_cache_age_days:
+                return None
+            
+            # Check parameters match
+            if meta["dataset"] != key.dataset or meta["symbol"] != key.symbol:
+                return None
+            
+            # Load parquet and convert
+            import pandas as pd
+            df = pd.read_parquet(cache_file)
+            return self._df_to_daily_points(df)
+        except Exception:
+            return None
+    
+    def _save_to_cache(self, key: DatabentoCacheKey, df: pd.DataFrame) -> None:
+        """Save data to cache."""
+        cache_file = key.cache_path(self.config.cache_dir)
+        meta_file = key.metadata_path(self.config.cache_dir)
+        
+        df.to_parquet(cache_file, index=False)
+        
+        meta = {
+            "download_date": date.today().isoformat(),
+            "dataset": key.dataset,
+            "symbol": key.symbol,
+            "schema": key.schema,
+            "start_date": key.start_date.isoformat(),
+            "end_date": key.end_date.isoformat(),
+            "rows": len(df),
+        }
+        with open(meta_file, "w") as f:
+            json.dump(meta, f, indent=2)
+    
+    def _fetch_from_databento(self, key: DatabentoCacheKey) -> pd.DataFrame:
+        """Fetch data from Databento API."""
+        data = self.client.timeseries.get_range(
+            dataset=key.dataset,
+            symbols=key.symbol,
+            schema=key.schema,
+            start=key.start_date.isoformat(),
+            end=(key.end_date + timedelta(days=1)).isoformat(),  # Exclusive end
+            stype_in=self.config.stype_in,
+        )
+        df = data.to_df()
+        return df
+    
+    def _df_to_daily_points(self, df: pd.DataFrame) -> list[DailyClosePoint]:
+        """Convert DataFrame to DailyClosePoint list."""
+        points = []
+        for idx, row in df.iterrows():
+            # Databento ohlcv schema has ts_event as timestamp
+            ts = row.get("ts_event", row.get("ts_recv", idx))
+            if hasattr(ts, "date"):
+                row_date = ts.date()
+            else:
+                row_date = date.fromisoformat(str(ts)[:10])
+            
+            close = float(row["close"]) / 1e9  # Databento prices are int64 x 1e-9
+            
+            points.append(DailyClosePoint(date=row_date, close=close))
+        
+        return sorted(points, key=lambda p: p.date)
+    
+    def load_daily_closes(self, symbol: str, start_date: date, end_date: date) -> list[DailyClosePoint]:
+        """Load daily closing prices from Databento (with caching)."""
+        # Map symbols to datasets
+        dataset = self._resolve_dataset(symbol)
+        databento_symbol = self._resolve_symbol(symbol)
+        
+        key = DatabentoCacheKey(
+            dataset=dataset,
+            symbol=databento_symbol,
+            schema=self.config.schema,
+            start_date=start_date,
+            end_date=end_date,
+        )
+        
+        # Try cache first
+        cached = self._load_from_cache(key)
+        if cached is not None:
+            return cached
+        
+        # Fetch from Databento
+        import pandas as pd
+        df = self._fetch_from_databento(key)
+        
+        # Cache results
+        self._save_to_cache(key, df)
+        
+        return self._df_to_daily_points(df)
+    
+    def _resolve_dataset(self, symbol: str) -> str:
+        """Resolve symbol to Databento dataset."""
+        symbol_upper = symbol.upper()
+        if symbol_upper in ("GLD", "GLDM", "IAU"):
+            return "XNAS.BASIC"  # ETFs on Nasdaq
+        elif symbol_upper in ("GC=F", "GC", "GOLD"):
+            return "GLBX.MDP3"  # CME gold futures
+        elif symbol_upper == "XAU":
+            return "XNAS.BASIC"  # Treat as GLD proxy
+        else:
+            return self.config.dataset  # Use configured default
+    
+    def _resolve_symbol(self, symbol: str) -> str:
+        """Resolve vault-dash symbol to Databento symbol."""
+        symbol_upper = symbol.upper()
+        if symbol_upper == "XAU":
+            return "GLD"  # Proxy XAU via GLD prices
+        elif symbol_upper == "GC=F":
+            return "GC"  # Use parent symbol for continuous contracts
+        return symbol_upper
+    
+    def get_cost_estimate(self, symbol: str, start_date: date, end_date: date) -> float:
+        """Estimate cost in USD for a data request."""
+        dataset = self._resolve_dataset(symbol)
+        databento_symbol = self._resolve_symbol(symbol)
+        
+        try:
+            cost = self.client.metadata.get_cost(
+                dataset=dataset,
+                symbols=databento_symbol,
+                schema=self.config.schema,
+                start=start_date.isoformat(),
+                end=(end_date + timedelta(days=1)).isoformat(),
+            )
+            return cost
+        except Exception:
+            return 0.0  # Return 0 if cost estimation fails
+
+
+class DatabentoBacktestProvider:
+    """Databento-backed historical provider for synthetic backtesting."""
+    
+    provider_id = "databento_v1"
+    pricing_mode = "synthetic_bs_mid"
+    
+    def __init__(
+        self,
+        price_source: DatabentoHistoricalPriceSource,
+        implied_volatility: float = 0.16,
+        risk_free_rate: float = 0.045,
+    ) -> None:
+        self.price_source = price_source
+        self.implied_volatility = implied_volatility
+        self.risk_free_rate = risk_free_rate
+    
+    def load_history(self, symbol: str, start_date: date, end_date: date) -> list[DailyClosePoint]:
+        return self.price_source.load_daily_closes(symbol, start_date, end_date)
+    
+    # ... rest delegates to SyntheticHistoricalProvider logic
+```
+
+### Phase 2: Backtest Settings Model (DATA-DB-002)
+
+**File:** `app/models/backtest_settings.py`
+
+```python
+from dataclasses import dataclass, field
+from datetime import date
+from uuid import UUID
+
+from app.models.backtest import ProviderRef
+
+
+@dataclass(frozen=True)
+class BacktestSettings:
+    """User-configurable backtest settings (independent of portfolio)."""
+    
+    # Scenario identification
+    settings_id: UUID
+    name: str
+    
+    # Data source configuration
+    data_source: str = "databento"  # "databento", "yfinance", "synthetic"
+    dataset: str = "XNAS.BASIC"
+    schema: str = "ohlcv-1d"
+    
+    # Date range
+    start_date: date = date(2024, 1, 1)
+    end_date: date = date(2024, 12, 31)
+    
+    # Independent scenario configuration (not derived from portfolio)
+    underlying_symbol: str = "GLD"
+    start_price: float = 0.0  # 0 = auto-derive from first close
+    underlying_units: float = 1000.0  # Independent of portfolio
+    loan_amount: float = 0.0  # Debt position for LTV analysis
+    margin_call_ltv: float = 0.75
+    
+    # Templates to test
+    template_slugs: tuple[str, ...] = field(default_factory=lambda: ("protective-put-atm-12m",))
+    
+    # Provider reference
+    provider_ref: ProviderRef = field(default_factory=lambda: ProviderRef(
+        provider_id="databento_v1",
+        pricing_mode="synthetic_bs_mid",
+    ))
+    
+    # Cache metadata
+    cache_key: str = ""  # Populated when data is fetched
+    data_cost_usd: float = 0.0  # Cost of last data fetch
+```
+
+### Phase 3: Cache Management (DATA-DB-003)
+
+**File:** `app/services/backtesting/databento_cache.py`
+
+```python
+from __future__ import annotations
+
+from dataclasses import dataclass
+from datetime import date, timedelta
+from pathlib import Path
+import hashlib
+import json
+
+from app.services.backtesting.databento_source import DatabentoCacheKey
+
+
+@dataclass
+class CacheEntry:
+    """Metadata for a cached Databento dataset."""
+    cache_key: DatabentoCacheKey
+    file_path: Path
+    download_date: date
+    size_bytes: int
+    cost_usd: float
+
+
+class DatabentoCacheManager:
+    """Manages Databento data cache lifecycle."""
+    
+    def __init__(self, cache_dir: Path = Path(".cache/databento")) -> None:
+        self.cache_dir = cache_dir
+        self.cache_dir.mkdir(parents=True, exist_ok=True)
+    
+    def list_entries(self) -> list[CacheEntry]:
+        """List all cached entries."""
+        entries = []
+        for meta_file in self.cache_dir.glob("*_meta.json"):
+            with open(meta_file) as f:
+                meta = json.load(f)
+            
+            cache_file = meta_file.with_name(meta_file.stem.replace("_meta", "") + ".parquet")
+            if cache_file.exists():
+                entries.append(CacheEntry(
+                    cache_key=DatabentoCacheKey(
+                        dataset=meta["dataset"],
+                        symbol=meta["symbol"],
+                        schema=meta["schema"],
+                        start_date=date.fromisoformat(meta["start_date"]),
+                        end_date=date.fromisoformat(meta["end_date"]),
+                    ),
+                    file_path=cache_file,
+                    download_date=date.fromisoformat(meta["download_date"]),
+                    size_bytes=cache_file.stat().st_size,
+                    cost_usd=0.0,  # Would need to track separately
+                ))
+        return entries
+    
+    def invalidate_expired(self, max_age_days: int = 30) -> list[Path]:
+        """Remove cache entries older than max_age_days."""
+        removed = []
+        cutoff = date.today() - timedelta(days=max_age_days)
+        
+        for entry in self.list_entries():
+            if entry.download_date < cutoff:
+                entry.file_path.unlink(missing_ok=True)
+                meta_file = entry.file_path.with_name(entry.file_path.stem + "_meta.json")
+                meta_file.unlink(missing_ok=True)
+                removed.append(entry.file_path)
+        
+        return removed
+    
+    def clear_all(self) -> int:
+        """Clear all cached data."""
+        count = 0
+        for file in self.cache_dir.glob("*"):
+            if file.is_file():
+                file.unlink()
+                count += 1
+        return count
+    
+    def get_cache_size(self) -> int:
+        """Get total cache size in bytes."""
+        return sum(f.stat().st_size for f in self.cache_dir.glob("*") if f.is_file())
+    
+    def should_redownload(self, key: DatabentoCacheKey, params_changed: bool) -> bool:
+        """Determine if data should be re-downloaded."""
+        cache_file = key.cache_path(self.cache_dir)
+        meta_file = key.metadata_path(self.cache_dir)
+        
+        if params_changed:
+            return True
+        
+        if not cache_file.exists() or not meta_file.exists():
+            return True
+        
+        try:
+            with open(meta_file) as f:
+                meta = json.load(f)
+            download_date = date.fromisoformat(meta["download_date"])
+            age_days = (date.today() - download_date).days
+            return age_days > 30
+        except Exception:
+            return True
+```
+
+### Phase 4: Backtest Page UI Updates (DATA-DB-004)
+
+**Key changes to `app/pages/backtests.py`:**
+
+1. Add Databento configuration section
+2. Add independent start price/units inputs
+3. Show estimated data cost before fetching
+4. Cache status indicator
+
+```python
+# In backtests.py
+
+with ui.card().classes("w-full ..."):
+    ui.label("Data Source").classes("text-lg font-semibold")
+    
+    data_source = ui.select(
+        {"databento": "Databento (historical market data)", "yfinance": "Yahoo Finance (free, limited)"},
+        value="databento",
+        label="Data source",
+    ).classes("w-full")
+    
+    # Databento-specific settings
+    with ui.column().classes("w-full gap-2").bind_visibility_from(data_source, "value", lambda v: v == "databento"):
+        ui.label("Dataset configuration").classes("text-sm text-slate-500")
+        
+        dataset_select = ui.select(
+            {"XNAS.BASIC": "Nasdaq Basic (GLD)", "GLBX.MDP3": "CME Globex (GC=F)"},
+            value="XNAS.BASIC",
+            label="Dataset",
+        ).classes("w-full")
+        
+        schema_select = ui.select(
+            {"ohlcv-1d": "Daily bars", "ohlcv-1h": "Hourly bars"},
+            value="ohlcv-1d",
+            label="Resolution",
+        ).classes("w-full")
+        
+        # Cost estimate
+        cost_label = ui.label("Estimated cost: $0.00").classes("text-sm text-slate-500")
+        
+        # Cache status
+        cache_status = ui.label("").classes("text-xs text-slate-400")
+    
+    # Independent scenario settings
+    with ui.card().classes("w-full ..."):
+        ui.label("Scenario Configuration").classes("text-lg font-semibold")
+        ui.label("Configure start values independent of portfolio settings").classes("text-sm text-slate-500")
+        
+        start_price_input = ui.number(
+            "Start price",
+            value=0.0,
+            min=0.0,
+            step=0.01,
+        ).classes("w-full")
+        ui.label("Set to 0 to auto-derive from first historical close").classes("text-xs text-slate-400 -mt-2")
+        
+        underlying_units_input = ui.number(
+            "Underlying units",
+            value=1000.0,
+            min=0.0001,
+            step=0.0001,
+        ).classes("w-full")
+        
+        loan_amount_input = ui.number(
+            "Loan amount ($)",
+            value=0.0,
+            min=0.0,
+            step=1000,
+        ).classes("w-full")
+```
+
+### Phase 5: Scenario Pre-Seeding (DATA-DB-005)
+
+**File:** `app/services/backtesting/scenario_bulk_download.py`
+
+```python
+from __future__ import annotations
+
+from dataclasses import dataclass
+from datetime import date
+from pathlib import Path
+import json
+
+try:
+    import databento as db
+    DATABENTO_AVAILABLE = True
+except ImportError:
+    DATABENTO_AVAILABLE = False
+
+
+@dataclass
+class ScenarioPreset:
+    """Pre-configured scenario ready for backtesting."""
+    preset_id: str
+    display_name: str
+    symbol: str
+    dataset: str
+    window_start: date
+    window_end: date
+    default_start_price: float  # First close in window
+    default_templates: tuple[str, ...]
+    event_type: str
+    tags: tuple[str, ...]
+    description: str
+
+
+def download_historical_presets(
+    client: db.Historical,
+    presets: list[ScenarioPreset],
+    output_dir: Path,
+) -> dict[str, Path]:
+    """Bulk download historical data for all presets.
+    
+    Returns mapping of preset_id to cached file path.
+    """
+    results = {}
+    
+    for preset in presets:
+        cache_key = DatabentoCacheKey(
+            dataset=preset.dataset,
+            symbol=preset.symbol,
+            schema="ohlcv-1d",
+            start_date=preset.window_start,
+            end_date=preset.window_end,
+        )
+        
+        cache_file = cache_key.cache_path(output_dir)
+        
+        # Download if not cached
+        if not cache_file.exists():
+            data = client.timeseries.get_range(
+                dataset=preset.dataset,
+                symbols=preset.symbol,
+                schema="ohlcv-1d",
+                start=preset.window_start.isoformat(),
+                end=preset.window_end.isoformat(),
+            )
+            data.to_parquet(cache_file)
+        
+        results[preset.preset_id] = cache_file
+    
+    return results
+
+
+def create_default_presets() -> list[ScenarioPreset]:
+    """Create default scenario presets for gold hedging research."""
+    return [
+        ScenarioPreset(
+            preset_id="gld-2020-covid-crash",
+            display_name="GLD March 2020 COVID Crash",
+            symbol="GLD",
+            dataset="XNAS.BASIC",
+            window_start=date(2020, 2, 15),
+            window_end=date(2020, 4, 15),
+            default_start_price=143.0,  # Approx GLD close on 2020-02-15
+            default_templates=("protective-put-atm-12m", "protective-put-95pct-12m"),
+            event_type="crash",
+            tags=("covid", "crash", "high-vol"),
+            description="March 2020 COVID market crash - extreme volatility event",
+        ),
+        ScenarioPreset(
+            preset_id="gld-2022-rate-hike-cycle",
+            display_name="GLD 2022 Rate Hike Cycle",
+            symbol="GLD",
+            dataset="XNAS.BASIC",
+            window_start=date(2022, 1, 1),
+            window_end=date(2022, 12, 31),
+            default_start_price=168.0,
+            default_templates=("protective-put-atm-12m", "ladder-50-50-atm-95pct-12m"),
+            event_type="rate_cycle",
+            tags=("rates", "fed", "extended"),
+            description="Full year 2022 - aggressive Fed rate hikes",
+        ),
+        ScenarioPreset(
+            preset_id="gcf-2024-rally",
+            display_name="GC=F 2024 Gold Rally",
+            symbol="GC",
+            dataset="GLBX.MDP3",
+            window_start=date(2024, 1, 1),
+            window_end=date(2024, 12, 31),
+            default_start_price=2060.0,
+            default_templates=("protective-put-atm-12m",),
+            event_type="rally",
+            tags=("gold", "futures", "rally"),
+            description="Gold futures rally in 2024",
+        ),
+    ]
+```
+
+### Phase 6: Settings Persistence (DATA-DB-006)
+
+**File:** `app/models/backtest_settings_repository.py`
+
+```python
+from dataclasses import asdict
+from datetime import date
+from pathlib import Path
+from uuid import UUID, uuid4
+import json
+
+from app.models.backtest_settings import BacktestSettings
+
+
+class BacktestSettingsRepository:
+    """Persistence for backtest settings."""
+    
+    def __init__(self, base_path: Path | None = None) -> None:
+        self.base_path = base_path or Path(".workspaces")
+    
+    def _settings_path(self, workspace_id: str) -> Path:
+        return self.base_path / workspace_id / "backtest_settings.json"
+    
+    def load(self, workspace_id: str) -> BacktestSettings:
+        """Load backtest settings, creating defaults if not found."""
+        path = self._settings_path(workspace_id)
+        
+        if path.exists():
+            with open(path) as f:
+                data = json.load(f)
+            return BacktestSettings(
+                settings_id=UUID(data["settings_id"]),
+                name=data.get("name", "Default Backtest"),
+                data_source=data.get("data_source", "databento"),
+                dataset=data.get("dataset", "XNAS.BASIC"),
+                schema=data.get("schema", "ohlcv-1d"),
+                start_date=date.fromisoformat(data["start_date"]),
+                end_date=date.fromisoformat(data["end_date"]),
+                underlying_symbol=data.get("underlying_symbol", "GLD"),
+                start_price=data.get("start_price", 0.0),
+                underlying_units=data.get("underlying_units", 1000.0),
+                loan_amount=data.get("loan_amount", 0.0),
+                margin_call_ltv=data.get("margin_call_ltv", 0.75),
+                template_slugs=tuple(data.get("template_slugs", ("protective-put-atm-12m",))),
+                cache_key=data.get("cache_key", ""),
+                data_cost_usd=data.get("data_cost_usd", 0.0),
+            )
+        
+        # Return defaults
+        return BacktestSettings(
+            settings_id=uuid4(),
+            name="Default Backtest",
+        )
+    
+    def save(self, workspace_id: str, settings: BacktestSettings) -> None:
+        """Persist backtest settings."""
+        path = self._settings_path(workspace_id)
+        path.parent.mkdir(parents=True, exist_ok=True)
+        
+        data = asdict(settings)
+        data["settings_id"] = str(data["settings_id"])
+        data["start_date"] = data["start_date"].isoformat()
+        data["end_date"] = data["end_date"].isoformat()
+        data["template_slugs"] = list(data["template_slugs"])
+        data["provider_ref"] = {
+            "provider_id": settings.provider_ref.provider_id,
+            "pricing_mode": settings.provider_ref.pricing_mode,
+        }
+        
+        with open(path, "w") as f:
+            json.dump(data, f, indent=2)
+```
+
+## Roadmap Items
+
+### DATA-DB-001: Databento Historical Price Source
+**Dependencies:** None  
+**Estimated effort:** 2-3 days  
+**Deliverables:**
+- `app/services/backtesting/databento_source.py`
+- `tests/test_databento_source.py` (mocked API)
+- Environment variable `DATABENTO_API_KEY` support
+
+### DATA-DB-002: Backtest Settings Model
+**Dependencies:** None  
+**Estimated effort:** 1 day  
+**Deliverables:**
+- `app/models/backtest_settings.py`
+- Repository for persistence
+
+### DATA-DB-003: Cache Management
+**Dependencies:** DATA-DB-001  
+**Estimated effort:** 1 day  
+**Deliverables:**
+- `app/services/backtesting/databento_cache.py`
+- Cache cleanup CLI command
+
+### DATA-DB-004: Backtest Page UI Updates
+**Dependencies:** DATA-DB-001, DATA-DB-002  
+**Estimated effort:** 2 days  
+**Deliverables:**
+- Updated `app/pages/backtests.py`
+- Updated `app/pages/event_comparison.py`
+- Cost estimation display
+
+### DATA-DB-005: Scenario Pre-Seeding
+**Dependencies:** DATA-DB-001  
+**Estimated effort:** 1-2 days  
+**Deliverables:**
+- `app/services/backtesting/scenario_bulk_download.py`
+- Pre-configured presets for gold hedging research
+- Bulk download script
+
+### DATA-DB-006: Options Data Source (Future)
+**Dependencies:** DATA-DB-001  
+**Estimated effort:** 3-5 days  
+**Deliverables:**
+- `DatabentoOptionSnapshotSource` implementing `OptionSnapshotSource`
+- OPRA.PILLAR integration for historical options chains
+
+## Configuration
+
+Add to `.env`:
+```
+DATABENTO_API_KEY=db-xxxxxxxxxxxxxxxxxxxxxxxx
+```
+
+Add to `requirements.txt`:
+```
+databento>=0.30.0
+```
+
+Add to `pyproject.toml`:
+```toml
+[project.optional-dependencies]
+databento = ["databento>=0.30.0"]
+```
+
+## Testing Strategy
+
+1. **Unit tests** with mocked Databento responses (`tests/test_databento_source.py`)
+2. **Integration tests** with recorded VCR cassettes (`tests/cassettes/*.yaml`)
+3. **E2E tests** using cached data (`tests/test_backtest_databento_playwright.py`)
+
+## Cost Management
+
+- Use `metadata.get_cost()` before fetching to show estimated cost
+- Default to cached data when available
+- Batch download for large historical ranges (>1 year)
+- Consider Databento flat rate plans for heavy usage
+
+## Security Considerations
+
+- API key stored in environment variable, never in code
+- Cache files contain only market data (no PII)
+- Rate limiting respected (100 requests/second per IP)

docs/DEVOPS_DEPLOY_PROMPT.md

@@ -78,11 +78,19 @@ env:
 4. **Configure Docker on the VPS**:
    - Ensure Docker and Docker Compose are installed
    - The deploy script will pull the container image from the registry
+   - Ensure the shared external Docker network `proxy-net` exists so Caddy can reverse proxy the deployment by container name
 
-5. **Verify network connectivity**:
+5. **Publish public route through Caddy**:
+   - Add `lombard.uncloud.tech` to `/opt/caddy/Caddyfile`
+   - Reverse proxy to `vault-dash:8000` on `proxy-net`
+   - Reload Caddy and verify `https://lombard.uncloud.tech/health`
+   - Remove the retired `vd1.uncloud.vpn` route if it still exists
+
+6. **Verify network connectivity**:
    - Forgejo runner must be able to reach the VPS via SSH
    - VPS must be able to pull images from the registry
 
+
 ## Instructions for the DevOps Agent
 
 When setting up the deployment:

docs/EXEC-001A_BT-001_MVP_ARCHITECTURE.md

@@ -0,0 +1,969 @@
+# EXEC-001A / BT-001 MVP Architecture
+
+## Scope
+
+This document defines the MVP design for four related roadmap items:
+
+- **EXEC-001A** — Named Strategy Templates
+- **BT-001** — Synthetic Historical Backtesting
+- **BT-002** — Historical Daily Options Snapshot Provider
+- **BT-003** — Selloff Event Comparison Report
+
+The goal is to give implementation agents a concrete architecture without requiring a database or a full UI rewrite. The MVP should fit the current codebase shape:
+
+- domain models in `app/models/`
+- IO and orchestration in `app/services/`
+- strategy math in `app/strategies/` or a new `app/backtesting/` package
+- lightweight docs under `docs/`
+
+## Design goals
+
+1. **Keep current live quote/options flows working.** Do not overload `app/services/data_service.py` with historical backtest state.
+2. **Make templates reusable and named.** A strategy definition should be saved once and referenced by many backtests.
+3. **Support synthetic-first backtests.** BT-001 must work before BT-002 exists.
+4. **Prevent lookahead bias by design.** Providers and the run engine must expose only data available at each `as_of_date`.
+5. **Preserve a migration path to real daily options snapshots.** Synthetic pricing and snapshot-based pricing must share the same provider contract.
+6. **Stay file-backed for MVP persistence.** Repositories may use JSON files under `data/` first, behind interfaces.
+
+## Terminology decision
+
+The current code uses `LombardPortfolio.gold_ounces`, but the strategy engine effectively treats that field as generic underlying units. For historical backtesting, implementation agents should **not** extend that ambiguity.
+
+### Recommendation
+
+- Keep `LombardPortfolio` unchanged for existing live pages.
+- Introduce backtesting-specific portfolio state using the neutral term **`underlying_units`**.
+- Treat `symbol` + `underlying_units` as the canonical tradable exposure.
+
+This avoids mixing physical ounces, GLD shares, and synthetic units in the backtest engine.
+
+---
+
+## MVP architecture summary
+
+### Main decision
+
+Create a new isolated subsystem:
+
+- `app/models/strategy_template.py`
+- `app/models/backtest.py`
+- `app/models/event_preset.py`
+- `app/services/historical/`
+- `app/services/backtesting/`
+- optional thin adapters in `app/strategies/` for reusing existing payoff logic
+
+### Why isolate it
+
+The current `DataService` is a live/synthetic read service with cache-oriented payload shaping. Historical backtesting needs:
+
+- versioned saved definitions
+- run lifecycle state
+- daily path simulation
+- historical provider abstraction
+- reproducible result storage
+
+Those concerns should not be mixed into the current request-time quote service.
+
+---
+
+## Domain model proposals
+
+## 1. Strategy templates (EXEC-001A)
+
+A strategy template is a **named, versioned, reusable hedge definition**. It is not a run result and it is not a specific dated option contract.
+
+### `StrategyTemplate`
+
+Recommended fields:
+
+| Field | Type | Notes |
+|---|---|---|
+| `template_id` | `str` | Stable UUID/string key |
+| `slug` | `str` | Human-readable unique name, e.g. `protective-put-atm-12m` |
+| `display_name` | `str` | UI/report label |
+| `description` | `str` | Short rationale |
+| `template_kind` | enum | `protective_put`, `laddered_put`, `collar` (future-safe) |
+| `status` | enum | `draft`, `active`, `archived` |
+| `version` | `int` | Increment on material rule changes |
+| `underlying_symbol` | `str` | MVP may allow one symbol per template |
+| `contract_mode` | enum | `continuous_units` for synthetic MVP, `listed_contracts` for BT-002+ |
+| `legs` | `list[TemplateLeg]` | One or more parametric legs |
+| `roll_policy` | `RollPolicy` | How/when to replace expiring hedges |
+| `entry_policy` | `EntryPolicy` | When the initial hedge is entered |
+| `tags` | `list[str]` | e.g. `conservative`, `income-safe` |
+| `created_at` | `datetime` | Audit |
+| `updated_at` | `datetime` | Audit |
+
+### `TemplateLeg`
+
+Recommended fields:
+
+| Field | Type | Notes |
+|---|---|---|
+| `leg_id` | `str` | Stable within template version |
+| `side` | enum | `long` or `short`; MVP uses `long` only for puts |
+| `option_type` | enum | `put` or `call` |
+| `allocation_weight` | `float` | Must sum to `1.0` across active hedge legs in MVP |
+| `strike_rule` | `StrikeRule` | MVP: `spot_pct` only |
+| `target_expiry_days` | `int` | e.g. `365`, `180`, `90` |
+| `quantity_rule` | enum | MVP: `target_coverage_pct` |
+| `target_coverage_pct` | `float` | Usually `1.0` for full hedge, but supports partial hedges later |
+
+### `StrikeRule`
+
+MVP shape:
+
+| Field | Type | Notes |
+|---|---|---|
+| `rule_type` | enum | `spot_pct` |
+| `value` | `float` | e.g. `1.00`, `0.95`, `0.90` |
+
+Future-safe, but not in MVP:
+
+- `delta_target`
+- `fixed_strike`
+- `moneyness_bucket`
+
+### `RollPolicy`
+
+Recommended MVP fields:
+
+| Field | Type | Notes |
+|---|---|---|
+| `policy_type` | enum | `hold_to_expiry`, `roll_n_days_before_expiry` |
+| `days_before_expiry` | `int` | Required for rolling mode |
+| `rebalance_on_new_deposit` | `bool` | Default `false` in MVP |
+
+### `EntryPolicy`
+
+Recommended MVP fields:
+
+| Field | Type | Notes |
+|---|---|---|
+| `entry_timing` | enum | `scenario_start_close` |
+| `stagger_days` | `int \| None` | Not used in MVP, keep nullable |
+
+### MVP template invariants
+
+Implementation agents should enforce:
+
+- `slug` unique among active templates
+- template versions immutable once referenced by a completed run
+- weights sum to `1.0` for `protective_put`/`laddered_put` templates
+- all legs use the same `target_expiry_days` in MVP unless explicitly marked as a ladder with shared roll policy
+- `underlying_symbol` on the template must either match the scenario symbol or be `*`/generic if generic templates are later supported
+
+### Template examples
+
+- `protective-put-atm-12m`
+- `protective-put-95pct-12m`
+- `ladder-50-50-atm-95pct-12m`
+- `ladder-33-33-33-atm-95pct-90pct-12m`
+
+These map cleanly onto the existing strategy set in `app/strategies/engine.py`.
+
+---
+
+## 2. Backtest scenarios
+
+A backtest scenario is the **saved experiment definition**. It says what portfolio, time window, templates, provider, and execution rules are used.
+
+### `BacktestScenario`
+
+Recommended fields:
+
+| Field | Type | Notes |
+|---|---|---|
+| `scenario_id` | `str` | Stable UUID/string key |
+| `slug` | `str` | Human-readable name |
+| `display_name` | `str` | Report label |
+| `description` | `str` | Optional scenario intent |
+| `symbol` | `str` | Underlying being hedged |
+| `start_date` | `date` | Inclusive |
+| `end_date` | `date` | Inclusive |
+| `initial_portfolio` | `BacktestPortfolioState` | Portfolio at day 0 |
+| `template_refs` | `list[TemplateRef]` | One or more template versions to compare |
+| `provider_ref` | `ProviderRef` | Which historical provider to use |
+| `execution_model` | `ExecutionModel` | Daily close-to-close for MVP |
+| `valuation_frequency` | enum | `daily` in MVP |
+| `benchmark_mode` | enum | `unhedged_only` in MVP |
+| `event_preset_id` | `str \| None` | Optional link for BT-003 |
+| `notes` | `list[str]` | Optional warnings/assumptions |
+| `created_at` | `datetime` | Audit |
+
+### `BacktestPortfolioState`
+
+Recommended fields:
+
+| Field | Type | Notes |
+|---|---|---|
+| `currency` | `str` | `USD` in MVP |
+| `underlying_units` | `float` | Canonical exposure size |
+| `entry_spot` | `float` | Starting spot reference |
+| `loan_amount` | `float` | Outstanding loan |
+| `margin_call_ltv` | `float` | Stress threshold |
+| `cash_balance` | `float` | Usually `0.0` in MVP |
+| `financing_rate` | `float` | Optional, default `0.0` in MVP |
+
+### `TemplateRef`
+
+Use a small immutable reference object:
+
+| Field | Type | Notes |
+|---|---|---|
+| `template_id` | `str` | Stable template key |
+| `version` | `int` | Required for reproducibility |
+| `display_name_override` | `str \| None` | Optional report label |
+
+### `ProviderRef`
+
+Recommended fields:
+
+| Field | Type | Notes |
+|---|---|---|
+| `provider_id` | `str` | e.g. `synthetic_v1`, `daily_snapshots_v1` |
+| `config_key` | `str` | Named config/profile used by the run |
+| `pricing_mode` | enum | `synthetic_bs_mid` or `snapshot_mid` |
+
+### `ExecutionModel`
+
+MVP decision:
+
+- **Daily close-to-close engine**
+- Positions are evaluated once per trading day
+- If a template rule triggers on date `T`, entry/roll is executed using provider data **as of date `T` close**
+- Mark-to-market for date `T` uses the same `T` snapshot
+
+This is a simplification, but it is deterministic and compatible with BT-002 daily snapshots.
+
+### Scenario invariants
+
+- `start_date <= end_date`
+- at least one `template_ref`
+- all referenced template versions must exist before run submission
+- `initial_portfolio.loan_amount < initial_portfolio.underlying_units * entry_spot`
+- scenario must declare the provider explicitly; no hidden global default inside the engine
+
+---
+
+## 3. Backtest runs and results
+
+A run is the **execution record** of one scenario against one or more templates under one provider.
+
+### `BacktestRun`
+
+Recommended fields:
+
+| Field | Type | Notes |
+|---|---|---|
+| `run_id` | `str` | Stable UUID |
+| `scenario_id` | `str` | Source scenario |
+| `status` | enum | `queued`, `running`, `completed`, `failed`, `cancelled` |
+| `provider_snapshot` | `ProviderSnapshot` | Frozen provider config used at run time |
+| `submitted_at` | `datetime` | Audit |
+| `started_at` | `datetime \| None` | Audit |
+| `completed_at` | `datetime \| None` | Audit |
+| `engine_version` | `str` | Git SHA or app version |
+| `rules_version` | `str` | Semantic rules hash for reproducibility |
+| `warnings` | `list[str]` | Missing data fallback, skipped dates, etc. |
+| `error` | `str \| None` | Failure detail |
+
+### `ProviderSnapshot`
+
+Freeze the provider state used by a run:
+
+| Field | Type | Notes |
+|---|---|---|
+| `provider_id` | `str` | Resolved provider implementation |
+| `config` | `dict[str, Any]` | Frozen provider config used for the run |
+| `source_version` | `str \| None` | Optional data snapshot/build hash |
+
+### `BacktestRunResult`
+
+Top-level recommended fields:
+
+| Field | Type | Notes |
+|---|---|---|
+| `run_id` | `str` | Foreign key |
+| `scenario_snapshot` | `BacktestScenario` or frozen subset | Freeze used inputs |
+| `template_results` | `list[TemplateBacktestResult]` | One per template |
+| `comparison_summary` | `RunComparisonSummary` | Ranked table |
+| `generated_at` | `datetime` | Audit |
+
+### `TemplateBacktestResult`
+
+Recommended fields:
+
+| Field | Type | Notes |
+|---|---|---|
+| `template_id` | `str` | Identity |
+| `template_version` | `int` | Reproducibility |
+| `template_name` | `str` | Display |
+| `summary_metrics` | `BacktestSummaryMetrics` | Compact ranking metrics |
+| `daily_path` | `list[BacktestDailyPoint]` | Daily timeseries |
+| `position_log` | `list[BacktestPositionRecord]` | Open/roll/expire events |
+| `trade_log` | `list[BacktestTradeRecord]` | Cashflow events |
+| `validation_notes` | `list[str]` | e.g. synthetic IV fallback used |
+
+### `BacktestSummaryMetrics`
+
+Recommended MVP metrics:
+
+| Field | Type | Notes |
+|---|---|---|
+| `start_value` | `float` | Initial collateral value |
+| `end_value_unhedged` | `float` | Baseline terminal collateral |
+| `end_value_hedged_net` | `float` | After hedge P&L and premiums |
+| `total_hedge_cost` | `float` | Sum of paid premiums |
+| `total_option_payoff_realized` | `float` | Expiry/close realized payoff |
+| `max_ltv_unhedged` | `float` | Path max |
+| `max_ltv_hedged` | `float` | Path max |
+| `margin_call_days_unhedged` | `int` | Count |
+| `margin_call_days_hedged` | `int` | Count |
+| `worst_drawdown_unhedged` | `float` | Optional but useful |
+| `worst_drawdown_hedged` | `float` | Optional but useful |
+| `days_protected_below_threshold` | `int` | Optional convenience metric |
+| `roll_count` | `int` | Operational complexity |
+
+### `BacktestDailyPoint`
+
+Recommended daily path fields:
+
+| Field | Type | Notes |
+|---|---|---|
+| `date` | `date` | Trading date |
+| `spot_close` | `float` | Underlying close |
+| `underlying_value` | `float` | `underlying_units * spot_close` |
+| `option_market_value` | `float` | Mark-to-market of open hedge |
+| `premium_cashflow` | `float` | Negative on entry/roll |
+| `realized_option_cashflow` | `float` | Expiry/sale value |
+| `net_portfolio_value` | `float` | Underlying + option MTM + cash |
+| `loan_amount` | `float` | Constant in MVP |
+| `ltv_unhedged` | `float` | Baseline |
+| `ltv_hedged` | `float` | Hedge-aware |
+| `margin_call_unhedged` | `bool` | Baseline |
+| `margin_call_hedged` | `bool` | Hedge-aware |
+| `active_position_ids` | `list[str]` | Traceability |
+
+### `BacktestTradeRecord`
+
+Recommended fields:
+
+| Field | Type | Notes |
+|---|---|---|
+| `trade_id` | `str` | Stable key |
+| `date` | `date` | Execution date |
+| `action` | enum | `buy_open`, `sell_close`, `expire`, `roll` |
+| `leg_id` | `str` | Template leg link |
+| `instrument_key` | `HistoricalInstrumentKey` | Strike/expiry/type |
+| `quantity` | `float` | Continuous or discrete |
+| `price` | `float` | Fill price |
+| `cashflow` | `float` | Signed |
+| `reason` | enum | `initial_entry`, `scheduled_roll`, `expiry`, `scenario_end` |
+
+### Run/result invariants
+
+- runs are append-only after completion
+- results must freeze template versions and scenario inputs used at execution time
+- failed runs may omit `template_results` but must preserve `warnings`/`error`
+- ranking should never rely on a metric that can be absent without a fallback rule
+
+---
+
+## 4. Event presets (BT-003)
+
+An event preset is a **named reusable market window** used to compare strategy behavior across selloffs.
+
+### `EventPreset`
+
+Recommended fields:
+
+| Field | Type | Notes |
+|---|---|---|
+| `event_preset_id` | `str` | Stable key |
+| `slug` | `str` | e.g. `covid-crash-2020` |
+| `display_name` | `str` | Report label |
+| `symbol` | `str` | Underlying symbol |
+| `window_start` | `date` | Inclusive |
+| `window_end` | `date` | Inclusive |
+| `anchor_date` | `date \| None` | Optional focal date |
+| `event_type` | enum | `selloff`, `recovery`, `stress_test` |
+| `tags` | `list[str]` | e.g. `macro`, `liquidity`, `vol-spike` |
+| `description` | `str` | Why this event exists |
+| `scenario_overrides` | `EventScenarioOverrides` | Optional defaults |
+| `created_at` | `datetime` | Audit |
+
+### `EventScenarioOverrides`
+
+MVP fields:
+
+| Field | Type | Notes |
+|---|---|---|
+| `lookback_days` | `int \| None` | Optional pre-window warmup |
+| `recovery_days` | `int \| None` | Optional post-event tail |
+| `default_template_slugs` | `list[str]` | Suggested comparison set |
+| `normalize_start_value` | `bool` | Default `true` for event comparison charts |
+
+### BT-003 usage pattern
+
+- a report selects one or more `EventPreset`s
+- each preset materializes a `BacktestScenario`
+- the same template set is run across all events
+- report compares normalized daily paths and summary metrics
+
+### MVP event decision
+
+Use **manual date windows only**. Do not attempt automatic peak/trough detection in the first slice.
+
+---
+
+## Historical provider abstraction
+
+## Core interface
+
+Create a provider contract that exposes only **point-in-time historical data**.
+
+### `HistoricalMarketDataProvider`
+
+Recommended methods:
+
+```python
+class HistoricalMarketDataProvider(Protocol):
+    provider_id: str
+
+    def get_trading_days(self, symbol: str, start_date: date, end_date: date) -> list[date]: ...
+
+    def get_underlying_bars(
+        self, symbol: str, start_date: date, end_date: date
+    ) -> list[UnderlyingBar]: ...
+
+    def get_option_snapshot(
+        self, query: OptionSnapshotQuery
+    ) -> OptionSnapshot: ...
+
+    def price_open_position(
+        self, position: HistoricalOptionPosition, as_of_date: date
+    ) -> HistoricalOptionMark: ...
+```
+
+### Why this interface
+
+It cleanly supports both provider types:
+
+- **BT-001 synthetic provider** — generate option values from deterministic assumptions
+- **BT-002 snapshot provider** — read real daily option quotes/surfaces from stored snapshots
+
+It also makes lookahead control explicit: every method is asked for data **as of** a specific date.
+
+## Supporting provider models
+
+### `UnderlyingBar`
+
+| Field | Type | Notes |
+|---|---|---|
+| `date` | `date` | Trading day |
+| `open` | `float` | Optional for future use |
+| `high` | `float` | Optional |
+| `low` | `float` | Optional |
+| `close` | `float` | Required |
+| `volume` | `float \| None` | Optional |
+| `source` | `str` | Provider/source tag |
+
+### `OptionSnapshotQuery`
+
+| Field | Type | Notes |
+|---|---|---|
+| `symbol` | `str` | Underlying |
+| `as_of_date` | `date` | Point-in-time date |
+| `option_type` | enum | `put`/`call` |
+| `target_expiry_days` | `int` | Desired tenor |
+| `strike_rule` | `StrikeRule` | Resolved against current spot |
+| `pricing_side` | enum | `mid` in MVP |
+
+### `OptionSnapshot`
+
+| Field | Type | Notes |
+|---|---|---|
+| `as_of_date` | `date` | Snapshot date |
+| `symbol` | `str` | Underlying |
+| `underlying_close` | `float` | Spot used for selection/pricing |
+| `selected_contract` | `HistoricalOptionQuote` | Resolved contract |
+| `selection_notes` | `list[str]` | e.g. nearest expiry/nearest strike |
+| `source` | `str` | Provider ID |
+
+### `HistoricalOptionQuote`
+
+| Field | Type | Notes |
+|---|---|---|
+| `instrument_key` | `HistoricalInstrumentKey` | Canonical contract identity |
+| `bid` | `float` | Optional for snapshot provider |
+| `ask` | `float` | Optional |
+| `mid` | `float` | Required for MVP valuation |
+| `implied_volatility` | `float \| None` | Required for BT-002, synthetic-derived for BT-001 |
+| `delta` | `float \| None` | Optional now, useful later |
+| `open_interest` | `int \| None` | Optional now |
+| `volume` | `int \| None` | Optional now |
+| `source` | `str` | Provider/source tag |
+
+### `HistoricalInstrumentKey`
+
+| Field | Type | Notes |
+|---|---|---|
+| `symbol` | `str` | Underlying |
+| `option_type` | enum | `put`/`call` |
+| `expiry` | `date` | Contract expiry |
+| `strike` | `float` | Contract strike |
+
+---
+
+## Provider implementations
+
+## A. `SyntheticHistoricalProvider` (BT-001 first)
+
+Purpose:
+
+- generate deterministic historical backtests without requiring stored historical options chains
+- use historical underlying closes plus a synthetic volatility/rates regime
+- resolve template legs into synthetic option quotes on each rebalance date
+- reprice open positions daily using the same model family
+
+### Recommended behavior
+
+Inputs:
+
+- underlying close series (from yfinance file cache, CSV fixture, or another deterministic source)
+- configured implied volatility regime, e.g. fixed `0.16` or dated step regime
+- configured risk-free rate regime
+- optional stress spread for transaction cost realism
+
+Entry and valuation:
+
+- on a rebalance date, compute strike from `spot_pct * spot_close`
+- set expiry by nearest trading day to `as_of_date + target_expiry_days`
+- price using Black-Scholes with the current day's spot, configured IV, remaining time, and option type
+- on later dates, reprice the same contract using current spot and remaining time only
+
+### MVP synthetic assumptions
+
+- constant or schedule-based implied volatility; no future realized volatility leakage
+- no stochastic volatility process in first slice
+- no early exercise modeling
+- no assignment modeling
+- `mid` price only
+- deterministic rounding/selection rules
+
+### Why synthetic-first is acceptable
+
+It validates:
+
+- template persistence
+- run lifecycle
+- path valuation
+- daily result rendering
+- anti-lookahead contract boundaries
+
+before adding BT-002 data ingestion complexity.
+
+## B. `DailyOptionsSnapshotProvider` (BT-002)
+
+Purpose:
+
+- load historical option quotes for each trading day
+- resolve actual listed contracts closest to template rules
+- mark open positions to historical daily mids thereafter
+
+### Recommended behavior
+
+- selection on entry day uses nearest eligible expiry and nearest eligible strike from that day's chain only
+- mark-to-market later uses the exact same contract key if a quote exists on later dates
+- if the contract is missing on a later date, provider returns a missing-data result and the engine applies a documented fallback policy
+
+### MVP fallback policy for missing marks
+
+Implementation agents should choose one explicit fallback and test it. Recommended order:
+
+1. exact contract from same-day snapshot
+2. if unavailable, previous available mark from same contract with warning
+3. if unavailable and contract is expired, intrinsic value at expiry or zero afterward
+4. otherwise fail the run or mark the template result incomplete
+
+Do **not** silently substitute a different strike/expiry for an already-open position.
+
+---
+
+## Backtest engine flow
+
+Create a dedicated engine under `app/backtesting/engine.py`. Keep orchestration and repository wiring in `app/services/backtesting/`.
+
+### High-level loop
+
+For each template in the scenario:
+
+1. load trading days from provider
+2. create baseline unhedged path
+3. resolve initial hedge on `start_date`
+4. for each trading day:
+   - read underlying close for day `T`
+   - mark open option positions as of `T`
+   - compute unhedged and hedged portfolio value
+   - compute LTV and margin-call flags
+   - check roll/expiry rules using only `T` data
+   - if a roll is due, close/expire old position and open replacement using `T` snapshot
+5. liquidate remaining position at scenario end if still open
+6. calculate summary metrics
+7. rank templates inside `comparison_summary`
+
+### Position model recommendation
+
+Use a separate open-position model rather than reusing `OptionContract` directly.
+
+Recommended `HistoricalOptionPosition` fields:
+
+- `position_id`
+- `instrument_key`
+- `opened_at`
+- `expiry`
+- `quantity`
+- `entry_price`
+- `current_mark`
+- `template_leg_id`
+- `source_snapshot_date`
+
+Reason: backtests need lifecycle state and audit fields that the current `OptionContract` model does not carry.
+
+### Ranking recommendation
+
+For MVP comparison views, rank templates by:
+
+1. fewer `margin_call_days_hedged`
+2. lower `max_ltv_hedged`
+3. lower `total_hedge_cost`
+4. higher `end_value_hedged_net`
+
+This is easier to explain than a single opaque score.
+
+---
+
+## Data realism constraints
+
+Implementation agents should treat the following as mandatory MVP rules.
+
+## 1. Point-in-time only
+
+On day `T`, the engine may use only:
+
+- underlying bar for `T`
+- option snapshot for `T`
+- provider configuration known before the run starts
+- open positions created earlier or on `T`
+
+It may **not** use:
+
+- future closes
+- future implied vols
+- terminal event windows beyond `T` for trading decisions
+- any provider helper that precomputes the whole path and leaks future state into contract selection
+
+## 2. Stable contract identity after entry
+
+Once a contract is opened, daily valuation must use that exact contract identity:
+
+- same symbol
+- same expiry
+- same strike
+- same option type
+
+No rolling relabeling of a live position to a “nearest” contract.
+
+## 3. Explicit selection rules
+
+Template rules must resolve to contracts with deterministic tiebreakers:
+
+- nearest expiry at or beyond target DTE
+- nearest strike to rule target
+- if tied, prefer more conservative strike for puts (higher strike) and earliest expiry
+
+Tiebreakers must be documented and unit-tested.
+
+## 4. Execution timing must be fixed
+
+MVP should use **same-day close execution** consistently.
+
+Do not mix:
+
+- signal at close / fill next open
+- signal at close / fill same close
+- signal intraday / mark at close
+
+If this changes later, it must be a scenario-level parameter.
+
+## 5. Continuous-vs-listed quantity must be explicit
+
+MVP synthetic runs may use `continuous_units`.
+The shipped BT-002 provider slice also remains `continuous_units`-only.
+`listed_contracts` with contract-size rounding is deferred to follow-up slice `BT-002A`.
+
+Do not hide rounding rules inside providers.
+They belong in the position sizing logic and must be recorded in the result.
+
+## 6. Costs must be recorded as cashflows
+
+Premiums and close/expiry proceeds must be stored as dated cashflows.
+Do not collapse the entire hedge economics into end-of-period payoff only.
+
+## 7. Missing data cannot be silent
+
+Any missing snapshot/mark fallback must add:
+
+- a run or template warning
+- a template validation note
+- and, in a fuller follow-up slice, a deterministic result status if the template becomes incomplete
+
+---
+
+## Anti-lookahead rules
+
+These should be copied into tests and implementation notes verbatim.
+
+1. **Contract selection rule**: select options using only the entry-day snapshot.
+2. **Daily MTM rule**: mark open positions using only same-day data for the same contract.
+3. **Expiry rule**: once `as_of_date >= expiry`, option value becomes intrinsic-at-expiry or zero after expiry according to the provider contract; it is not repriced with negative time-to-expiry.
+4. **Event preset rule**: event presets may define scenario dates, but the strategy engine may not inspect future event endpoints when deciding to roll or exit.
+5. **Synthetic vol rule**: synthetic providers may use fixed or date-indexed IV schedules, but never realized future path statistics from dates after `as_of_date`.
+6. **Metric rule**: comparison metrics may summarize the whole run only after the run completes; they may not feed back into trading decisions during the run.
+
+---
+
+## Phased implementation plan with TDD slices
+
+Each slice should leave behind tests and a minimal implementation path.
+
+## Slice 0 — Red tests for model invariants
+
+Target:
+
+- create tests for `StrategyTemplate`, `BacktestScenario`, `BacktestRun`, `EventPreset`
+- validate weights, dates, versioned references, and uniqueness assumptions
+
+Suggested tests:
+
+- invalid ladder weights rejected
+- scenario with end before start rejected
+- template ref requires explicit version
+- loan amount cannot exceed initial collateral value
+
+## Slice 1 — Named template repository (EXEC-001A core)
+
+Target:
+
+- file-backed `StrategyTemplateRepository`
+- save/load/list active templates
+- version bump on immutable update
+
+Suggested tests:
+
+- saving template round-trips cleanly
+- updating active template creates version 2, not in-place mutation
+- archived template stays loadable for historical runs
+
+## Slice 2 — Synthetic provider contract (BT-001 foundation)
+
+Target:
+
+- `HistoricalMarketDataProvider` protocol
+- `SyntheticHistoricalProvider`
+- deterministic underlying fixture input + synthetic option pricing
+
+Suggested tests:
+
+- provider returns stable trading day list
+- spot-pct strike resolution uses same-day spot only
+- repricing uses decreasing time to expiry
+- no future bar access required for day-`T` pricing
+
+## Slice 3 — Single-template backtest engine
+
+Target:
+
+- run one protective-put template across a short scenario
+- output daily path + summary metrics
+
+Suggested tests:
+
+- hedge premium paid on entry day
+- option MTM increases when spot falls materially below strike
+- hedged max LTV is <= unhedged max LTV in a monotonic selloff fixture
+- completed run freezes scenario and template version snapshots
+
+## Slice 4 — Multi-template comparison runs
+
+Target:
+
+- compare ATM, 95% put, 50/50 ladder on same scenario
+- produce ranked `comparison_summary`
+
+Suggested tests:
+
+- all template results share same scenario snapshot
+- ranking uses documented metric order
+- equal primary metric falls back to next metric deterministically
+
+## Slice 5 — Roll logic and expiry behavior
+
+Target:
+
+- support `roll_n_days_before_expiry`
+- support expiry settlement and position replacement
+
+Suggested tests:
+
+- roll occurs exactly on configured trading-day offset
+- expired contracts stop carrying time value
+- no contract identity mutation between entry and close
+
+## Slice 6 — Event presets and BT-003 scenario materialization
+
+Target:
+
+- repository for `EventPreset`
+- materialize preset -> scenario
+- run comparison over multiple named events
+
+Suggested tests:
+
+- preset dates map cleanly into scenario dates
+- scenario overrides are applied explicitly
+- normalized event series start from common baseline
+
+## Slice 7 — Daily snapshot provider (BT-002)
+
+Target:
+
+- add `DailyOptionsSnapshotProvider` behind same contract
+- reuse existing engine with provider swap only
+
+Suggested tests:
+
+- entry picks nearest valid listed contract from snapshot
+- later MTM uses same contract key
+- missing mark generates warning and applies documented fallback
+- synthetic and snapshot providers both satisfy same provider test suite
+
+## Slice 8 — Thin API/UI integration after engine is proven
+
+Not part of this doc’s implementation scope, but the natural next step is:
+
+- `/api/templates`
+- `/api/backtests`
+- `/api/backtests/{run_id}`
+- later a NiceGUI page for listing templates and runs
+
+Per project rules, do not claim this feature is live until the UI consumes real run data.
+
+---
+
+## Recommended file/module layout
+
+Recommended minimal layout for this codebase:
+
+```text
+app/
+  backtesting/
+    __init__.py
+    engine.py                 # run loop, ranking, metric aggregation
+    position_sizer.py         # continuous vs listed quantity rules
+    result_metrics.py         # path -> summary metrics
+    scenario_materializer.py  # event preset -> scenario
+    selection.py              # strike/expiry resolution helpers
+  models/
+    strategy_template.py      # StrategyTemplate, TemplateLeg, RollPolicy, EntryPolicy
+    backtest.py               # BacktestScenario, BacktestRun, results, daily points
+    event_preset.py           # EventPreset, overrides
+    historical_data.py        # UnderlyingBar, OptionSnapshot, InstrumentKey, marks
+  services/
+    backtesting/
+      __init__.py
+      orchestrator.py         # submit/load/list runs
+      repositories.py         # file-backed run repository helpers
+    historical/
+      __init__.py
+      base.py                 # HistoricalMarketDataProvider protocol
+      synthetic.py            # BT-001 provider
+      snapshots.py            # BT-002 provider
+    templates/
+      __init__.py
+      repository.py           # save/load/list/version templates
+    events/
+      __init__.py
+      repository.py           # save/load/list presets
+```
+
+### Persistence recommendation for MVP
+
+Use file-backed repositories first:
+
+```text
+data/
+  strategy_templates.json
+  event_presets.json
+  backtests/
+    <run_id>.json
+```
+
+Reason:
+
+- aligns with current `PortfolioRepository` style
+- keeps the MVP small
+- allows deterministic fixtures in tests
+- can later move behind the same repository interfaces
+
+---
+
+## Code reuse guidance
+
+Implementation agents should reuse existing code selectively.
+
+### Safe to reuse
+
+- pricing helpers in `app/core/pricing/`
+- payoff logic concepts from `app/models/option.py`
+- existing strategy presets from `app/strategies/engine.py` as seed templates
+
+### Do not reuse directly without adaptation
+
+- `StrategySelectionEngine` as the backtest engine
+- `DataService` as a historical run orchestrator
+- `LombardPortfolio.gold_ounces` as the canonical backtest exposure field
+
+Reason: these current types are optimized for present-time research payloads, not dated position lifecycle state.
+
+---
+
+## Open implementation decisions to settle before coding
+
+1. **Underlying source for synthetic BT-001**: use yfinance historical closes directly, local fixture CSVs, or both?
+2. **Quantity mode in first runnable slice**: support only `continuous_units` first, or implement listed contract rounding immediately?
+3. **Scenario end behavior**: liquidate remaining option at final close, or leave terminal MTM only?
+4. **Missing snapshot policy**: hard-fail vs warn-and-carry-forward?
+5. **Provider metadata freezing**: store config only, or config + source data hash?
+
+Recommended answers for MVP:
+
+- yfinance historical closes with deterministic test fixtures for unit tests
+- `continuous_units` first
+- liquidate at final close for clearer realized P&L
+- warn-and-carry-forward only for same-contract marks, otherwise fail
+- freeze provider config plus app/git version
+
+---
+
+## Implementation-ready recommendations
+
+1. **Build BT-001 around a new provider interface, not around `DataService`.**
+2. **Treat templates as immutable versioned definitions.** Runs must reference template versions, not mutable slugs only.
+3. **Use a daily close-to-close engine for MVP and document it everywhere.**
+4. **Record every hedge premium and payoff as dated cashflows.**
+5. **Keep synthetic provider and daily snapshot provider behind the same contract.**
+6. **Introduce `underlying_units` in backtesting models to avoid `gold_ounces` ambiguity.**
+7. **Make missing data warnings explicit and persistent in run results.**
+

docs/GLD_BASIS_RESEARCH.md

@@ -0,0 +1,170 @@
+# GLD ETF vs Gold Futures Basis: Implementation Guide
+
+## Executive Summary
+
+GLD (SPDR Gold Shares ETF) does **not** track gold at a simple 10:1 ratio. Two mechanical factors affect the conversion between GLD and physical gold/futures.
+
+## Key Findings for Dashboard Implementation
+
+### 1. Expense Ratio Decay (Permanent, Predictable)
+
+| Metric | Launch (2004) | Current (2026) |
+|--------|----------------|-----------------|
+| Gold per share | 0.1000 oz | ~0.0919 oz |
+| Effective ratio | 10:1 | **10.9:1** |
+| Cumulative decay | — | 8.1% |
+
+**Formula:**
+```
+ounces_per_share = 0.10 * e^(-0.004 * years_since_2004)
+```
+
+**Dashboard Implementation:**
+```python
+# Current GLD backing (as of 2026)
+GLD_OUNCES_PER_SHARE = 0.0919
+
+def gld_price_to_gold_spot(gld_price: float) -> float:
+    """Convert GLD price to implied gold spot price."""
+    return gld_price / GLD_OUNCES_PER_SHARE
+
+def gold_spot_to_gld_price(gold_spot: float) -> float:
+    """Convert gold spot price to GLD equivalent."""
+    return gold_spot * GLD_OUNCES_PER_SHARE
+
+# Example: At $4,600/oz gold
+# GLD ≈ $4,600 × 0.0919 ≈ $423 (NOT $460)
+```
+
+### 2. Futures-Spot Basis (Variable, Market-Dependent)
+
+| Market State | Futures vs. Spot | GLD vs. GC=F÷10 |
+|--------------|------------------|-----------------|
+| **Contango** (normal) | Futures > Spot by $10-15/oz | GLD appears at "discount" |
+| **Backwardation** (stress) | Spot > Futures | GLD appears at "premium" |
+
+**During stress events:**
+- March 2020 COVID: COMEX futures $50-70 above London spot
+- GLD holders benefited (physical-backed)
+- Futures traders suffered negative roll yield
+
+### 3. After-Hours Pricing Gap
+
+| Instrument | Trading Hours |
+|------------|---------------|
+| GLD | US market hours (9:30 AM - 4 PM ET) |
+| GC=F (futures) | 23 hours/day, 6 days/week |
+
+**Implication:** GLD opens with gaps after weekend/overnight gold moves. Dashboard should show "last regular session close" vs. "current futures indication."
+
+## Dashboard Recommendations
+
+### Data Display
+
+```python
+class GoldPriceDisplay:
+    """Recommended price display for vault-dash."""
+    
+    def __init__(self, gld_price: float, gold_futures_price: float):
+        self.gld_price = gld_price
+        self.gold_futures_price = gold_futures_price
+        self.ounces_per_share = 0.0919  # Current GLD backing
+        
+    @property
+    def implied_spot_from_gld(self) -> float:
+        """Gold spot implied from GLD price."""
+        return self.gld_price / self.ounces_per_share
+    
+    @property
+    def gld_fair_value(self) -> float:
+        """What GLD 'should' trade at based on futures."""
+        # Adjust for contango (~$10/oz typically)
+        spot_estimate = self.gold_futures_price - 10
+        return spot_estimate * self.ounces_per_share
+    
+    @property
+    def basis_bps(self) -> float:
+        """Basis between GLD and fair value in basis points."""
+        diff_bps = (self.gld_price / self.gld_fair_value - 1) * 10000
+        return diff_bps
+```
+
+### Warning Thresholds
+
+```python
+# Raise warnings when basis exceeds normal bounds
+BASIS_WARNING_THRESHOLD = 50  # 50 bps = 0.5%
+
+if abs(basis_bps) > BASIS_WARNING_THRESHOLD:
+    # GLD trading at unusual premium/discount
+    # Possible causes: after-hours gap, physical stress, AP arb failure
+    show_warning(f"GLD basis elevated: {basis_bps:.0f} bps")
+```
+
+### Options Pricing
+
+For Lombard hedge calculations:
+
+```python
+def calculate_hedge_strikes(
+    portfolio_gold_ounces: float,
+    margin_call_price: float,
+    current_gold_spot: float
+) -> dict:
+    """
+    Calculate appropriate GLD option strikes for hedge.
+    
+    IMPORTANT: Use GLD price directly, not converted from futures.
+    """
+    # Convert gold price thresholds to GLD strikes
+    gld_current = current_gold_spot * GLD_OUNCES_PER_SHARE
+    gld_margin_call = margin_call_price * GLD_OUNCES_PER_SHARE
+    
+    # Recommended strikes
+    atm_strike = round(gld_current)  # e.g., $423
+    otm_10_strike = round(gld_current * 0.90)  # 10% OTM: ~$381
+    otm_5_strike = round(gld_current * 0.95)  # 5% OTM: ~$402
+    
+    return {
+        "current_gld": gld_current,
+        "margin_call_gld": gld_margin_call,
+        "atm_strike": atm_strike,
+        "otm_5pct_strike": otm_5_strike,
+        "otm_10pct_strike": otm_10_strike,
+        "contracts_needed": math.ceil(portfolio_gold_ounces / (100 * GLD_OUNCES_PER_SHARE))
+    }
+```
+
+## Data Sources
+
+| Data Point | Source | Notes |
+|------------|--------|-------|
+| GLD NAV/ounce | spdrgoldshares.com | Daily updated |
+| GLD price | Market data API | Real-time |
+| GC=F price | CME/futures API | Extended hours |
+| Contango estimate | Futures curve | Calculate from term structure |
+
+## Key Takeaways for Vault-Dash
+
+1. **Never use a fixed 10:1 ratio** — always use current GLD backing (~0.092 oz/share)
+
+2. **Display both measures:**
+   - GLD implied spot = GLD ÷ 0.0919
+   - GC=F adjusted = GC=F ÷ 10 (naive) for comparison
+
+3. **Show basis indicator:**
+   - Green: basis within ±25 bps (normal)
+   - Yellow: basis ±25-50 bps (elevated)
+   - Red: basis > 50 bps (unusual — possible stress)
+
+4. **For hedging:**
+   - Use GLD's actual price for strike selection
+   - Contract count = gold ounces ÷ (100 × 0.0919)
+   - Don't convert from GC=F to GLD — use GLD directly
+
+## References
+
+- SEC GLD Registration Statement (2004)
+- SPDR Gold Shares: GLDM methodology updates
+- CME Gold Futures specifications
+- Research paper: "Optimal Hedging Strategies for Gold-Backed Lombard Loans"

docs/ROADMAP.md

@@ -1,249 +0,0 @@
-# Vault Dashboard Roadmap
-
-## Overview
-A prioritized roadmap for the Vault Dashboard Lombard loan hedging platform.
-
-## Legend
-- **Priority**: P0 (Critical), P1 (High), P2 (Medium), P3 (Low)
-- **Dependencies**: Features tagged with `[depends: ID]` require the named feature to be completed first
-- **Effort**: S (Small), M (Medium), L (Large)
-
----
-
-## Phase 1: Data Foundation (Foundation Layer)
-
-### DATA-001: Live Price Feed Integration [P0, M] **[foundation]**
-**As a** portfolio manager, **I want** real-time gold price updates **so that** my LTV calculations reflect current market conditions.
-
-**Acceptance Criteria:**
-- Integrate yfinance/live data for GLD spot price
-- Update prices every 30 seconds via WebSocket
-- Display last update timestamp
-- Fallback to cached data if feed fails
-
-**Technical Notes:**
-- Create `app/services/price_feed.py` with async price fetching
-- Extend existing WebSocket manager in `app/services/websocket.py`
-- Store prices in Redis with 60s TTL
-
-**Dependencies:** None
-
----
-
-### DATA-002: Options Chain Data [P0, L] **[depends: DATA-001]**
-**As a** trader, **I want** live options chain data for GLD **so that** I can evaluate protective put strikes and premiums.
-
-**Acceptance Criteria:**
-- Fetch options chains from yfinance or IBKR API
-- Display strikes, expiration dates, bid/ask, implied volatility
-- Cache chain data for 5 minutes
-- Support filtering by expiration (30/60/90 days)
-
-**Technical Notes:**
-- Create `app/services/options_chain.py`
-- Add `/api/options/chain` endpoint
-- Update Options Chain page (`app/pages/options.py`)
-
-**Dependencies:** DATA-001
-
----
-
-### DATA-003: Greeks Calculation [P1, M] **[depends: DATA-002]**
-**As a** risk manager, **I want** real-time Greeks calculations **so that** I understand my hedge sensitivity.
-
-**Acceptance Criteria:**
-- Calculate Delta, Gamma, Theta, Vega for selected options
-- Display Greeks in options chain view
-- Show portfolio-level Greeks if positions held
-- Use Black-Scholes model with live IV
-
-**Technical Notes:**
-- Create `app/services/pricing.py` with B-S model
-- Add QuantLib integration (optional dependency)
-- Cache calculations for performance
-
-**Dependencies:** DATA-002
-
----
-
-## Phase 2: Portfolio & Risk (Core Features)
-
-### PORT-001: Portfolio State Management [P0, M] **[depends: DATA-001]**
-**As a** user, **I want** to configure my actual portfolio (gold value, loan amount) **so that** LTV calculations match my real position.
-
-**Acceptance Criteria:**
-- Settings page with editable portfolio parameters
-- Store config in Redis/database
-- Validate LTV < 100%
-- Show current vs recommended collateral
-
-**Technical Notes:**
-- Extend `app/pages/settings.py`
-- Create `app/models/portfolio.py` with Pydantic models
-- Add persistence layer (Redis JSON or SQLite)
-
-**Dependencies:** DATA-001
-
----
-
-### PORT-002: Alert Notifications [P1, M] **[depends: PORT-001]**
-**As a** risk manager, **I want** alerts when LTV approaches margin call thresholds **so that** I can take action before liquidation.
-
-**Acceptance Criteria:**
-- Configurable alert thresholds (default: 70%, 75%)
-- Browser push notifications
-- Email notifications (optional)
-- Alert history log
-
-**Technical Notes:**
-- Create `app/services/alerts.py`
-- Integrate browser notifications API
-- Add `/api/alerts/configure` endpoint
-- Background task to check thresholds
-
-**Dependencies:** PORT-001
-
----
-
-### PORT-003: Historical LTV Chart [P2, M] **[depends: PORT-001]**
-**As a** user, **I want** to see my LTV history over time **so that** I can identify trends and stress periods.
-
-**Acceptance Criteria:**
-- Store LTV snapshots every hour
-- Display 7/30/90 day charts
-- Show margin call threshold line
-- Export data as CSV
-
-**Technical Notes:**
-- Create `app/services/history.py`
-- Use TimescaleDB or Redis TimeSeries (optional)
-- Integrate with existing chart components
-
-**Dependencies:** PORT-001
-
----
-
-## Phase 3: Strategy Execution (Advanced Features)
-
-### EXEC-001: Strategy Builder [P1, L] **[depends: DATA-003]**
-**As a** trader, **I want** to build and compare hedging strategies **so that** I can choose optimal protection.
-
-**Acceptance Criteria:**
-- Select strategy type (protective put, collar, laddered)
-- Choose strikes and expirations
-- See P&L payoff diagrams
-- Compare cost vs protection level
-
-**Technical Notes:**
-- Extend `app/pages/hedge.py`
-- Create `app/services/strategy_builder.py`
-- Add payoff chart visualization
-- Store strategy templates
-
-**Dependencies:** DATA-003
-
----
-
-### EXEC-002: IBKR Order Integration [P2, L] **[depends: EXEC-001]**
-**As a** authorized user, **I want** to execute hedge trades directly from the dashboard **so that** I can act quickly on recommendations.
-
-**Acceptance Criteria:**
-- IBKR API connection (paper trading first)
-- Preview order with estimated fill
-- One-click execution
-- Order tracking and status updates
-
-**Technical Notes:**
-- Create `app/services/broker.py` with IBKR API
-- Add paper/live mode toggle
-- Store credentials securely
-- Order audit log
-
-**Dependencies:** EXEC-001
-
----
-
-### EXEC-003: Position Monitoring [P2, M] **[depends: EXEC-002]**
-**As a** portfolio manager, **I want** to see my open hedge positions **so that** I know my current protection status.
-
-**Acceptance Criteria:**
-- Display open options positions
-- Show expiration countdown
-- Calculate net Greeks exposure
-- Alert on approaching expiration
-
-**Technical Notes:**
-- Create positions table/view
-- Sync with IBKR positions
-- Update portfolio Greeks calculation
-
-**Dependencies:** EXEC-002
-
----
-
-## Phase 4: Reporting & Analytics (Polish)
-
-### RPT-001: Strategy Report Generation [P3, M] **[depends: EXEC-001]**
-**As a** compliance officer, **I want** PDF reports of hedging decisions **so that** I can document risk management.
-
-**Acceptance Criteria:**
-- Generate PDF with strategy rationale
-- Include P&L scenarios
-- Date range selection
-- Export to email/share
-
-**Technical Notes:**
-- Use reportlab or weasyprint
-- Create `app/services/reporting.py`
-- Add download endpoint
-
-**Dependencies:** EXEC-001
-
----
-
-### RPT-002: What-If Analysis [P3, L] **[depends: DATA-003]**
-**As a** risk manager, **I want** to simulate gold price drops **so that** I can stress test my protection.
-
-**Acceptance Criteria:**
-- Slider to adjust gold price scenarios (-10%, -20%, etc.)
-- Show portfolio P&L impact
-- Display hedge payoff under scenarios
-- Compare protected vs unprotected
-
-**Technical Notes:**
-- Extend strategy builder with scenario mode
-- Add sensitivity analysis
-- Interactive chart updates
-
-**Dependencies:** DATA-003
-
----
-
-## Dependency Graph
-
-```
-DATA-001 (Price Feed)
-├── DATA-002 (Options Chain)
-│   ├── DATA-003 (Greeks)
-│   │   ├── EXEC-001 (Strategy Builder)
-│   │   │   ├── EXEC-002 (IBKR Orders)
-│   │   │   │   └── EXEC-003 (Position Monitoring)
-│   │   │   └── RPT-001 (Reports)
-│   │   └── RPT-002 (What-If)
-│   └── PORT-001 (Portfolio Config)
-│       ├── PORT-002 (Alerts)
-│       └── PORT-003 (History)
-```
-
----
-
-## Implementation Priority Queue
-
-1. **DATA-001** - Unblock all other features
-2. **PORT-001** - Enable user-specific calculations
-3. **DATA-002** - Core options data
-4. **DATA-003** - Risk metrics
-5. **PORT-002** - Risk management safety
-6. **EXEC-001** - Core user workflow
-7. **EXEC-002** - Execution capability
-8. Remaining features

docs/roadmap/ROADMAP.yaml

@@ -0,0 +1,117 @@
+version: 1
+updated_at: 2026-04-07
+structure:
+  backlog_dir: docs/roadmap/backlog
+  in_progress_dir: docs/roadmap/in-progress
+  done_dir: docs/roadmap/done
+  blocked_dir: docs/roadmap/blocked
+  cancelled_dir: docs/roadmap/cancelled
+notes:
+  - The roadmap source of truth is this index plus the per-task YAML files in the status folders.
+  - One task lives in one YAML file and changes state by moving between status folders.
+  - Priority ordering is maintained here so agents can parse one short file first.
+  - Pre-alpha policy: we may cut or replace old features without backward compatibility until alpha is declared.
+  - Alpha migration policy: once alpha is declared, compatibility only needs to move forward; backward migrations are not required.
+priority_queue:
+  - DATA-DB-007
+  - DATA-002A
+  - DATA-001A
+  - DATA-DB-005
+  - OPS-001
+  - BT-003
+  - BT-002A
+  - GCF-001
+  - DATA-DB-006
+  - EXEC-002
+recently_completed:
+  - UX-002
+  - BT-004
+  - BT-005
+  - CORE-003
+  - CONV-001
+  - DATA-DB-004
+  - PORTFOLIO-003
+  - PORTFOLIO-002
+  - DISPLAY-002
+  - PRICING-002
+  - BT-001C
+  - BT-002
+  - PORT-003
+  - BT-003B
+  - CORE-001D
+  - CORE-001D3C
+  - CORE-001D2D
+  - CORE-001D2C
+  - CORE-001D3B
+  - CORE-001D3A
+  - UX-001
+  - CORE-002
+  - CORE-002C
+  - CORE-001D2B
+  - CORE-001D2A
+  - CORE-002B
+states:
+  backlog:
+    - DATA-DB-007
+    - DATA-DB-005
+    - DATA-DB-006
+    - DATA-002A
+    - DATA-001A
+    - OPS-001
+    - BT-003
+    - BT-002A
+    - GCF-001
+    - EXEC-002
+  in_progress: []
+  done:
+    - BT-004
+    - BT-005
+    - CORE-003
+    - CONV-001
+    - DATA-DB-003
+    - DATA-DB-004
+    - DATA-DB-002
+    - DATA-DB-001
+    - PORTFOLIO-003
+    - PORTFOLIO-002
+    - DISPLAY-002
+    - PRICING-003
+    - PRICING-002
+    - PRICING-001
+    - DATA-001
+    - DATA-002
+    - DATA-003
+    - PORT-001
+    - PORT-001A
+    - PORT-002
+    - PORT-003
+    - PORT-004
+    - SEC-001
+    - SEC-001A
+    - EXEC-001A
+    - EXEC-001
+    - BT-001
+    - BT-001A
+    - BT-001C
+    - BT-002
+    - BT-003A
+    - BT-003B
+    - CORE-001A
+    - CORE-001B
+    - CORE-001C
+    - CORE-001D
+    - CORE-001D2A
+    - CORE-001D2B
+    - CORE-001D2C
+    - CORE-001D2D
+    - CORE-001D3A
+    - CORE-001D3B
+    - CORE-001D3C
+    - CORE-002
+    - CORE-002A
+    - CORE-002B
+    - CORE-002C
+    - UX-001
+    - UX-002
+  blocked: []
+  cancelled: []

docs/roadmap/backlog/BT-002A-snapshot-ingestion-and-listed-sizing.yaml

@@ -0,0 +1,16 @@
+id: BT-002A
+title: Snapshot Ingestion and Listed Contract Sizing
+status: backlog
+priority: P3
+effort: M
+depends_on:
+  - BT-002
+tags:
+  - backtesting
+  - data
+summary: Extend BT-002 from provider support to file-backed/external snapshot ingestion and listed-contract sizing semantics.
+acceptance_criteria:
+  - Historical snapshot data can be loaded from a documented file-backed or external source, not only injected in-memory fixtures.
+  - Snapshot-backed runs can size positions in listed contract units with explicit contract-size rounding rules.
+  - Snapshot data-quality warnings and incomplete-run behavior are persisted/reportable, not only template-local warnings.
+  - Provider configuration and snapshot-source assumptions are documented for reproducible runs.

docs/roadmap/backlog/BT-003-selloff-event-report.yaml

@@ -0,0 +1,13 @@
+id: BT-003
+title: Selloff Event Comparison Report
+status: backlog
+priority: P2
+effort: M
+depends_on:
+  - BT-001
+tags: [backtesting, events]
+summary: Rank named strategies across historical selloff events.
+acceptance_criteria:
+  - Event presets define named windows.
+  - Reports rank strategies by survival, max LTV, cost, and final equity.
+  - UI can show unhedged vs hedged path comparisons.

docs/roadmap/backlog/CORE-002B-hedge-quote-unit-rollout.yaml

@@ -0,0 +1,23 @@
+id: CORE-002B
+title: Hedge and Strategy Runtime Quote Unit Rollout
+status: backlog
+priority: P0
+effort: M
+depends_on:
+  - CORE-002A
+  - CORE-001B
+tags:
+  - core
+  - units
+  - hedge
+  - pricing
+summary: Apply explicit instrument-aware quote-unit conversions to the next visible ounce-based hedge/runtime paths so they no longer assume ounce-native spot prices.
+acceptance_criteria:
+  - Hedge/runtime displays that consume live or configured GLD spots use explicit share->ozt conversions where needed.
+  - Visible strategy/hedge labels distinguish converted collateral spot from raw share quotes when relevant.
+  - Unsupported or missing quote-unit metadata fails closed rather than silently applying raw share prices as ounce prices.
+  - Tests cover the changed hedge/runtime math and browser-visible route behavior.
+technical_notes:
+  - Likely file targets include `app/pages/hedge.py`, `app/pages/common.py`, and any service/helpers feeding hedge summary/runtime spot values.
+  - Reuse the new instrument metadata seam rather than introducing new ad hoc scale factors.
+  - Keep backtesting/event share-based paths compatible while tightening visible ounce-based paths.

docs/roadmap/backlog/CORE-003-mypy-type-safety.yaml

@@ -0,0 +1,112 @@
+name: CORE-003 Mypy Type Safety
+description: |
+  Fix all mypy type errors to enable strict type checking in CI.
+  
+  Currently 42 errors in 15 files. The CI uses `|| true` to allow warnings,
+  but we should fix these properly with strong types and conversion functions.
+  
+status: backlog
+priority: medium
+created_at: 2026-03-29
+dependencies: []
+  
+acceptance_criteria:
+  - mypy passes with 0 errors on app/core app/models app/strategies app/services
+  - CI type-check job passes without `|| true`
+  - All type narrowing uses proper patterns (properties, cast(), or isinstance checks)
+  - No duplicate method definitions
+  
+scope:
+  in_scope:
+    - Fix type errors in app/domain/units.py
+    - Fix type errors in app/domain/portfolio_math.py  
+    - Fix type errors in app/models/portfolio.py
+    - Fix type errors in app/domain/backtesting_math.py
+    - Fix type errors in app/domain/instruments.py
+    - Fix type errors in app/services/*.py
+    - Fix type errors in app/pages/*.py
+    - Remove `|| true` from type-check job in CI
+    
+  out_of_scope:
+    - Adding new type annotations to previously untyped code
+    - Refactoring business logic
+    
+files_with_errors:
+  - file: app/domain/units.py
+    errors: 6
+    pattern: "WeightUnit | str" not narrowed after __post_init__
+    fix: Use _unit_typed property for type-narrowed access
+    
+  - file: app/models/portfolio.py  
+    errors: 1
+    pattern: "Duplicate _serialize_value definition"
+    fix: Remove duplicate method definition
+    
+  - file: app/domain/backtesting_math.py
+    errors: 1  
+    pattern: "assert_currency" argument type
+    fix: Use Money.assert_currency properly or add type narrowing
+    
+  - file: app/domain/instruments.py
+    errors: 1
+    pattern: "to_unit" argument type
+    fix: Use _unit_typed property or explicit coercion
+    
+  - file: app/domain/portfolio_math.py
+    errors: 11
+    pattern: "float(object), Weight | Money union, dict type mismatch"
+    fix: Add proper type guards and conversion functions
+    
+  - file: app/services/backtesting/ui_service.py
+    errors: 2
+    pattern: "Provider type mismatch, YFinance vs Databento source"
+    fix: Use proper union types for provider interface
+    
+  - file: app/services/event_comparison_ui.py
+    errors: 1
+    pattern: "FixtureBoundSyntheticHistoricalProvider type"
+    fix: Update type annotations for provider hierarchy
+    
+  - file: app/services/cache.py
+    errors: 1
+    pattern: "str | None to Redis URL"
+    fix: Add None check or use assertion
+    
+  - file: app/services/price_feed.py
+    errors: 2
+    pattern: "float(object)"
+    fix: Add explicit type coercion
+    
+  - file: app/pages/settings.py
+    errors: 1
+    pattern: "Return value on ui.button scope"
+    fix: Proper return type annotation
+
+implementation_notes: |
+  The root cause is that frozen dataclass fields with `Field: UnionType`
+  are not narrowed by `__post_init__` coercion. Mypy sees the declared
+  type, not the runtime type.
+  
+  Solutions:
+  1. Add `@property def _field_typed(self) -> NarrowType:` for internal use
+  2. Use `cast(NarrowType, self.field)` at call sites
+  3. Use `isinstance` checks before operations requiring narrow type
+  
+  Pattern example from units.py fix:
+  ```python
+  @property
+  def _unit_typed(self) -> WeightUnit:
+      """Type-narrowed unit accessor for internal use."""
+      return self.unit  # type: ignore[return-value]
+  
+  def to_unit(self, unit: WeightUnit) -> Weight:
+      return Weight(amount=convert_weight(self.amount, self._unit_typed, unit), unit=unit)
+  ```
+
+estimated_effort: 4-6 hours
+
+tags:
+  - type-safety
+  - mypy
+  - technical-debt
+  - ci-quality

docs/roadmap/backlog/DATA-001A-live-overview-price-wiring.yaml

@@ -0,0 +1,15 @@
+id: DATA-001A
+title: Live Overview Price Wiring
+status: backlog
+priority: P0
+effort: S
+depends_on:
+  - DATA-001
+  - PORT-001
+tags: [overview, pricing]
+summary: Use the live price service directly on the overview page.
+acceptance_criteria:
+  - Overview uses live quote data instead of a hardcoded spot.
+  - Source and last-updated metadata are displayed.
+  - Margin-call and LTV values use configured portfolio inputs.
+  - Browser test verifies visible live data metadata.

docs/roadmap/backlog/DATA-002A-lazy-options-loading.yaml

@@ -0,0 +1,15 @@
+id: DATA-002A
+title: Lazy Options Loading
+status: backlog
+priority: P0
+effort: S
+depends_on:
+  - DATA-002
+tags: [options, performance]
+summary: Render the options page fast by loading only the minimum data initially.
+acceptance_criteria:
+  - Initial page load fetches expirations plus one default expiry chain.
+  - Changing expiry fetches only that expiry on demand.
+  - Browser test verifies /options becomes visible quickly with no visible runtime error.
+technical_notes:
+  - Keep initial render fast and move additional data loading behind user selection.

docs/roadmap/backlog/DATA-DB-005-scenario-pre-seeding.yaml

@@ -0,0 +1,48 @@
+id: DATA-DB-005
+title: Scenario Pre-Seeding from Bulk Downloads
+status: backlog
+priority: medium
+dependencies:
+  - DATA-DB-001
+estimated_effort: 1-2 days
+created: 2026-03-28
+updated: 2026-03-28
+
+description: |
+  Create pre-configured scenario presets for gold hedging research and implement
+  bulk download capability to pre-seed event comparison pages. This allows quick
+  testing against historical events without per-event data fetching.
+
+acceptance_criteria:
+  - Default presets include COVID crash, rate hike cycle, gold rally events
+  - Bulk download script fetches all preset data
+  - Presets stored in config file (JSON/YAML)
+  - Event comparison page shows preset data availability
+  - One-click "Download All Presets" button
+  - Progress indicator during bulk download
+
+implementation_notes: |
+  Default presets:
+  - GLD March 2020 COVID Crash (extreme volatility)
+  - GLD 2022 Rate Hike Cycle (full year)
+  - GC=F 2024 Gold Rally (futures data)
+  
+  Bulk download flow:
+  1. Create batch job for each preset
+  2. Show progress per preset
+  3. Store in cache directory
+  4. Update preset availability status
+  
+  Preset format:
+  - preset_id: unique identifier
+  - display_name: human-readable name
+  - symbol: GLD, GC, etc.
+  - dataset: Databento dataset
+  - window_start/end: date range
+  - default_start_price: first close
+  - default_templates: hedging strategies
+  - event_type: crash, rally, rate_cycle
+  - tags: for filtering
+
+dependencies_detail:
+  - DATA-DB-001: Needs cache infrastructure

docs/roadmap/backlog/DATA-DB-006-databento-options-source.yaml

@@ -0,0 +1,46 @@
+id: DATA-DB-006
+title: Databento Options Data Source
+status: backlog
+priority: low
+dependencies:
+  - DATA-DB-001
+estimated_effort: 3-5 days
+created: 2026-03-28
+updated: 2026-03-28
+
+description: |
+  Implement historical options data source using Databento's OPRA.PILLAR dataset.
+  This enables historical options chain lookups for accurate backtesting with
+  real options prices, replacing synthetic Black-Scholes pricing.
+
+acceptance_criteria:
+  - DatabentoOptionSnapshotSource implements OptionSnapshotSource protocol
+  - OPRA.PILLAR dataset used for GLD/SPY options
+  - Option chain lookup by snapshot_date and symbol
+  - Strike and expiry filtering supported
+  - Cached per-date for efficiency
+  - Fallback to synthetic pricing when data unavailable
+
+implementation_notes: |
+  OPRA.PILLAR provides consolidated options data from all US options exchanges.
+  
+  Key challenges:
+  1. OPRA data volume is large - need efficient caching
+  2. Option symbology differs from regular symbols
+  3. Need strike/expiry resolution in symbology
+  
+  Implementation approach:
+  - Use 'definition' schema to get instrument metadata
+  - Use 'trades' or 'ohlcv-1d' for price history
+  - Cache per (symbol, expiration, strike, option_type, date)
+  - Use continuous contracts for futures options (GC=F)
+  
+  Symbology:
+  - GLD options: Use underlying symbol "GLD" with OPRA
+  - GC options: Use parent symbology "GC" for continuous contracts
+  
+  This is a future enhancement - not required for initial backtesting
+  which uses synthetic Black-Scholes pricing.
+
+dependencies_detail:
+  - DATA-DB-001: Needs base cache infrastructure

docs/roadmap/backlog/DATA-DB-007-gc-databento-contract-mapping.yaml

@@ -0,0 +1,20 @@
+id: DATA-DB-007
+title: Databento GC Contract Mapping for Backtests
+status: backlog
+priority: P1
+effort: M
+depends_on:
+  - DATA-DB-001
+tags:
+  - databento
+  - futures
+  - backtests
+summary: Add real Databento futures contract mapping for GC backtests so the page can support gold futures without fail-closed restrictions.
+acceptance_criteria:
+  - Backtest-page Databento runs support GC without requiring users to know raw contract symbols.
+  - Contract selection or front-month rollover rules are explicit and test-covered.
+  - The selected contract path yields non-empty historical price data for supported windows.
+  - Browser validation confirms the GC path works from `/{workspace_id}/backtests` with no visible runtime error.
+technical_notes:
+  - Current hardening work intentionally fail-closes GC on the backtest page because the raw `GC` symbol does not resolve reliably in Databento historical requests.
+  - Follow-up work should decide between explicit contract selection, continuous mapping, or deterministic rollover logic before re-enabling GC in the Databento path.

docs/roadmap/backlog/EXEC-002-ibkr-order-integration.yaml

@@ -0,0 +1,13 @@
+id: EXEC-002
+title: IBKR Order Integration
+status: backlog
+priority: P2
+effort: L
+depends_on:
+  - EXEC-001
+tags: [broker, execution]
+summary: Execute hedge trades directly from the dashboard.
+acceptance_criteria:
+  - Support IBKR paper trading first.
+  - Preview order, execute, and track status.
+  - Securely store credentials and maintain audit history.

docs/roadmap/backlog/GCF-001-gcf-options-data.yaml

@@ -0,0 +1,25 @@
+id: GCF-001
+title: GC=F Options Data Source
+status: backlog
+priority: P2
+size: L
+depends_on:
+  - DATA-004
+tags: [data-source, options, futures]
+summary: Wire GC=F futures options data for users who choose GC=F as primary underlying.
+acceptance_criteria:
+  - GC=F underlying fetches live options chain from CME or equivalent source
+  - Options chain includes: strikes, expirations, bid/ask, IV, delta
+  - Options displayed in futures contract units (100 oz per contract)
+  - Strike selection in GC=F mode uses futures prices directly
+  - Fallback to estimated options if live data unavailable
+notes:
+  - GC=F is COMEX Gold Futures, contract size = 100 troy oz
+  - Options on futures have different quoting than equity options
+  - May need paid data feed (CME, ICE, broker API)
+  - Alternative: estimate from GLD options + basis
+implementation_hints:
+  - Add `get_gcf_options_chain()` to `DataService`
+  - Contract size: 100 oz per futures option
+  - Explore yfinance GC=F options (limited) vs paid sources
+  - Cache aggressively to minimize API calls

docs/roadmap/backlog/OPS-001-public-caddy-route.yaml

@@ -0,0 +1,15 @@
+id: OPS-001
+title: Public Caddy Route for Lombard Dashboard
+status: backlog
+priority: P1
+effort: S
+depends_on: []
+tags: [ops, deploy, routing]
+summary: Move the production route to public HTTPS at lombard.uncloud.tech.
+acceptance_criteria:
+  - Caddy proxies lombard.uncloud.tech to the deployment container.
+  - HTTPS works with a valid certificate.
+  - Health check succeeds through Caddy.
+  - Deployment docs note that vd1.uncloud.vpn was retired in favor of the public route.
+technical_notes:
+  - Keep public-exposure controls aligned with SEC-001 Turnstile bootstrap protection.

docs/roadmap/done/BT-001-synthetic-backtesting.yaml

@@ -0,0 +1,9 @@
+id: BT-001
+title: Synthetic Historical Backtesting
+status: done
+priority: P1
+effort: L
+depends_on:
+  - EXEC-001A
+  - PORT-001
+summary: Synthetic historical backtesting engine ships with deterministic and optional provider-backed paths.

docs/roadmap/done/BT-001A-backtest-ui.yaml

@@ -0,0 +1,10 @@
+id: BT-001A
+title: Backtest Scenario Runner UI
+status: done
+priority: P1
+effort: M
+depends_on:
+  - BT-001
+  - EXEC-001A
+  - PORT-001
+summary: Thin read-only /backtests UI over the synthetic backtest engine.

docs/roadmap/done/BT-001C-shared-historical-fixture-provider.yaml

@@ -0,0 +1,18 @@
+id: BT-001C
+title: Shared Historical Fixture/Test Provider Cleanup
+status: done
+priority: P2
+effort: S
+depends_on:
+  - BT-001A
+  - BT-003A
+tags:
+  - backtesting
+  - test-infra
+summary: Deterministic historical fixture logic for browser-tested backtest UIs is now centralized behind a shared fixture source used by both `/backtests` and `/event-comparison`.
+completed_notes:
+  - Added `app/services/backtesting/fixture_source.py` with shared seeded GLD fixture history and explicit exact-vs-bounded window policies.
+  - Updated `app/services/backtesting/ui_service.py` so the `/backtests` page uses the shared fixture source in exact-window mode and still fails closed outside the seeded BT-001A range.
+  - Updated `app/services/event_comparison_ui.py` so the `/event-comparison` page uses the same shared fixture source in bounded-window mode for preset subranges inside the seeded BT-003A fixture window.
+  - Added focused regression coverage in `tests/test_backtesting_fixture_source.py` proving the shared source enforces exact and bounded policies explicitly and that both page services use the centralized fixture source.
+  - During this implementation loop, local Docker validation stayed green on the affected historical routes: `/health` returned OK and `tests/test_e2e_playwright.py` passed against the Docker-served app.

docs/roadmap/done/BT-002-historical-options-snapshots.yaml

@@ -0,0 +1,20 @@
+id: BT-002
+title: Historical Daily Options Snapshot Provider
+status: done
+priority: P2
+effort: L
+depends_on:
+  - BT-001
+tags:
+  - backtesting
+  - data
+summary: Backtests can now use a point-in-time historical options snapshot provider with exact-contract mark-to-market instead of synthetic-only option pricing.
+completed_notes:
+  - Added shared historical position/mark provider hooks in `app/services/backtesting/historical_provider.py` so `BacktestService` can swap provider implementations while preserving the backtest engine flow.
+  - Snapshot-backed runs still fail closed on `listed_contracts`; BT-002 ships observed snapshot pricing for `continuous_units` only, with listed-contract sizing explicitly deferred to `BT-002A`.
+  - Added `DailyOptionsSnapshotProvider` with deterministic entry-day contract selection, exact-contract mark-to-market, and explicit carry-forward warnings when later marks are missing.
+  - Updated `app/backtesting/engine.py` and `app/services/backtesting/service.py` so snapshot-backed runs and synthetic runs share the same scenario execution path.
+  - Added focused regression coverage in `tests/test_backtesting_snapshots.py` for entry-day-only selection, observed snapshot marks, and no-substitution missing-mark fallback behavior.
+  - Added provider/data-quality documentation in `docs/BT-002_HISTORICAL_OPTIONS_SNAPSHOT_PROVIDER.md`, including current limitations around precomputed mids, continuous-units sizing, and follow-up ingestion work.
+  - Docker-served browser validation still passed on the affected historical routes after the engine/provider seam changes: `/health` returned OK and `tests/test_e2e_playwright.py` passed against the local Docker app.
+  - While closing that browser loop, `/{workspace_id}/event-comparison` preset changes were corrected to preserve user-edited underlying units and only reset preset-driven template selection, matching the UI copy and stale-state behavior.

docs/roadmap/done/BT-003A-event-comparison-ui.yaml

@@ -0,0 +1,9 @@
+id: BT-003A
+title: Event Comparison UI Read Path
+status: done
+priority: P1
+effort: M
+depends_on:
+  - BT-003
+  - BT-001A
+summary: Thin read-only /event-comparison UI over EventComparisonService.