- Added signalQualityVersion field to Trade model
- Tracks which scoring logic version was used for each trade
- v1: Original logic (price position < 5% threshold)
- v2: Added volume compensation for low ADX
- v3: CURRENT - Stricter logic requiring ADX > 18 for extreme positions (< 15%)
This enables future analysis to:
- Compare performance between logic versions
- Filter trades by scoring algorithm
- Data-driven improvements based on clean datasets
All new trades will be marked as v3. Old trades remain null/v1 for comparison.
- Detect position size mismatches (>50% variance) after opening
- Save phantom trades to database with expectedSizeUSD, actualSizeUSD, phantomReason
- Return error from execute endpoint to prevent Position Manager tracking
- Add comprehensive documentation of phantom trade issue and solution
- Enable data collection for pattern analysis and future optimization
Fixes oracle price lag issue during volatile markets where transactions
confirm but positions don't actually open at expected size.
- Add signalQualityScore field to Trade model (0-100)
- Calculate quality score in execute endpoint using same logic as check-risk
- Save score with every trade for correlation analysis
- Create database migration for new field
- Enables future analysis: score vs win rate, P&L, etc.
This allows data-driven decisions on dynamic position sizing
- Fixed Prisma client not being available in Docker container
- Added isTestTrade flag to exclude test trades from analytics
- Created analytics views for net positions (matches Drift UI netting)
- Added API endpoints: /api/analytics/positions and /api/analytics/stats
- Added test trade endpoint: /api/trading/test-db
- Updated Dockerfile to properly copy Prisma client from builder stage
- Database now successfully stores all trades with full details
- Supports position netting calculations to match Drift perpetuals behavior
- Add PostgreSQL database with Prisma ORM
- Trade model: tracks entry/exit, P&L, order signatures, config snapshots
- PriceUpdate model: tracks price movements for drawdown analysis
- SystemEvent model: logs errors and system events
- DailyStats model: aggregated performance metrics
- Implement dual stop loss system (enabled by default)
- Soft stop (TRIGGER_LIMIT) at -1.5% to avoid wicks
- Hard stop (TRIGGER_MARKET) at -2.5% to guarantee exit
- Configurable via USE_DUAL_STOPS, SOFT_STOP_PERCENT, HARD_STOP_PERCENT
- Backward compatible with single stop modes
- Add database service layer (lib/database/trades.ts)
- createTrade(): save new trades with all details
- updateTradeExit(): close trades with P&L calculations
- addPriceUpdate(): track price movements during trade
- getTradeStats(): calculate win rate, profit factor, avg win/loss
- logSystemEvent(): log errors and system events
- Update execute endpoint to use dual stops and save to database
- Calculate dual stop prices when enabled
- Pass dual stop parameters to placeExitOrders
- Save complete trade record to database after execution
- Add test trade button to settings page
- New /api/trading/test endpoint for executing test trades
- Displays detailed results including dual stop prices
- Confirmation dialog before execution
- Shows entry price, position size, stops, and TX signature
- Generate Prisma client in Docker build
- Update DATABASE_URL for container networking
