invest-copilot/tasks/phase2-backtest-integration/SPEC.md

Task: Wire Backtest Integration

Current State

src/backend/services/backtest_service.py (16,798 bytes) exists with backtesting logic. POST /api/v1/strategies/{id}/backtest endpoint exists per README. However, the backtest engine is not connected to the data pipeline — it runs against whatever data happens to be in the DB, with no guarantee of freshness or completeness.

Goal

Connect the backtest engine to the data pipeline so:

1. Backtests always run against a known-good, pipeline-fresh dataset
2. Backtest results are stored and queryable
3. Users can trigger backtests via the API and see results

Requirements

1. Verify backtest_service.py reads from database correctly
2. Add backtest result storage model (SQLAlchemy)
3. Store backtest results: trades, metrics, equity curve
4. Add GET /api/v1/backtests/{id} endpoint to retrieve results
5. Add GET /api/v1/backtests endpoint to list past backtests
6. Ensure backtest runs after pipeline completes (dependency on pipeline task)

Acceptance Criteria

• Backtest endpoint returns results with trades, metrics, equity curve
• Results persist in database and survive server restart
• Past backtests queryable via list endpoint
• Backtest uses data from the most recent pipeline run
• Frontend can display backtest results on strategy page

Constraints

• Use TimescaleDB hypertables for equity curve time-series data
• Follow existing patterns — check models/ for existing backtest model
• Keep under 200 lines per framework rule
• Read existing migrations before writing schema

Files to Create/Modify

• src/backend/models/ (check for existing backtest model, add if missing)
• src/backend/services/backtest_service.py (add result storage)
• src/backend/routers/strategies.py (add result endpoints)
• src/backend/tasks/pipeline.py (add backtest trigger option)

Next Steps After This Task

Phase 2 complete. Move to Phase 5 (Sector Rotation) or Phase 7 (PWA).