- Removed v10 TradingView indicator (moneyline_v10_momentum_dots.pinescript)
- Removed v10 penalty system from signal-quality.ts (-30/-25 point penalties)
- Removed backtest result files (sweep_*.csv)
- Updated copilot-instructions.md to remove v10 references
- Simplified direction-specific quality thresholds (LONG 90+, SHORT 80+)
Rationale:
- 1,944 parameter combinations tested in backtest
- All top results IDENTICAL (568 trades, $498 P&L, 61.09% WR)
- Momentum parameters had ZERO impact on trade selection
- Profit factor 1.027 too low (barely profitable after fees)
- Max drawdown -$1,270 vs +$498 profit = terrible risk-reward
- v10 penalties were blocking good trades (bug: applied to wrong positions)
Keeping v9 as production system - simpler, proven, effective.
User Request: Distinguish between SL and Trailing SL in analytics overview
Changes:
1. Position Manager:
- Updated ExitResult interface to include 'TRAILING_SL' exit reason
- Modified trailing stop exit (line 1457) to use 'TRAILING_SL' instead of 'SL'
- Enhanced external closure detection (line 937) to identify trailing stops
- Updated handleManualClosure to detect trailing SL at price target
2. Database:
- Updated UpdateTradeExitParams interface to accept 'TRAILING_SL'
3. Frontend Analytics:
- Updated last trade display to show 'Trailing SL' with special formatting
- Purple background/border for TRAILING_SL vs blue for regular SL
- Runner emoji (🏃) prefix for trailing stops
Impact:
- Users can now see when trades exit via trailing stop vs regular SL
- Better understanding of runner system performance
- Trailing stops visually distinct in analytics dashboard
Files Modified:
- lib/trading/position-manager.ts (4 locations)
- lib/database/trades.ts (UpdateTradeExitParams interface)
- app/analytics/page.tsx (exit reason display)
- .github/copilot-instructions.md (Common Pitfalls #61, #62)
Implemented comprehensive price tracking for multi-timeframe signal analysis.
**Components Added:**
- lib/analysis/blocked-signal-tracker.ts - Background job tracking prices
- app/api/analytics/signal-tracking/route.ts - Status/metrics endpoint
**Features:**
- Automatic price tracking at 1min, 5min, 15min, 30min intervals
- TP1/TP2/SL hit detection using ATR-based targets
- Max favorable/adverse excursion tracking (MFE/MAE)
- Analysis completion after 30 minutes
- Background job runs every 5 minutes
- Entry price captured from signal time
**Database Changes:**
- Added entryPrice field to BlockedSignal (for price tracking baseline)
- Added maxFavorablePrice, maxAdversePrice fields
- Added maxFavorableExcursion, maxAdverseExcursion fields
**Integration:**
- Auto-starts on container startup
- Tracks all DATA_COLLECTION_ONLY signals
- Uses same TP/SL calculation as live trades (ATR-based)
- Calculates profit % based on direction (long vs short)
**API Endpoints:**
- GET /api/analytics/signal-tracking - View tracking status and metrics
- POST /api/analytics/signal-tracking - Manually trigger update (auth required)
**Purpose:**
Enables data-driven multi-timeframe comparison. After 50+ signals per
timeframe, can analyze which timeframe (5min vs 15min vs 1H vs 4H vs Daily)
has best win rate, profit potential, and signal quality.
**What It Tracks:**
- Price at 1min, 5min, 15min, 30min after signal
- Would TP1/TP2/SL have been hit?
- Maximum profit/loss during 30min window
- Complete analysis of signal profitability
**How It Works:**
1. Signal comes in (15min, 1H, 4H, Daily) → saved to BlockedSignal
2. Background job runs every 5min
3. Queries current price from Pyth
4. Calculates profit % from entry
5. Checks if TP/SL thresholds crossed
6. Updates MFE/MAE if new highs/lows
7. After 30min, marks analysisComplete=true
**Future Analysis:**
After 50+ signals per timeframe:
- Compare TP1 hit rates across timeframes
- Identify which timeframe has highest win rate
- Determine optimal signal frequency vs quality trade-off
- Switch production to best-performing timeframe
User requested: "i want all the bells and whistles. lets make the
powerhouse more powerfull. i cant see any reason why we shouldnt"
PROBLEM (User identified):
- Analytics showed 3 open trades when Drift UI showed only 1 position
- Database had 3 separate trade records all marked as 'open'
- Root cause: Drift has 1 POSITION + 3 ORDERS (TP/SL exit orders)
- Validator was incorrectly treating each as separate position
SOLUTION:
- Group database trades by symbol before validation
- If multiple DB trades exist for one Drift position, keep only MOST RECENT
- Close older duplicate trades with exitReason='DUPLICATE_CLEANUP'
- Properly handles: 1 Drift position → 1 DB trade (correct state)
RESULT:
- Database: 1 open trade (matches Drift reality)
- Analytics: Shows accurate position count
- Runs automatically every 10 minutes + manual trigger available
- Set signalSource='manual' for Telegram trades, 'tradingview' for TradingView
- Updated analytics queries to exclude manual trades from indicator analysis
- getTradingStats() filters manual trades (TradingView performance only)
- Version comparison endpoint filters manual trades
- Created comprehensive filtering guide: docs/MANUAL_TRADE_FILTERING.md
- Ensures clean data for indicator optimization without contamination
Improved flip-flop penalty logic to distinguish between:
- Chop (bad): <2% price move from opposite signal → -25 penalty
- Reversal (good): ≥2% price move from opposite signal → allowed
Changes:
- lib/database/trades.ts: getRecentSignals() now returns oppositeDirectionPrice
- lib/trading/signal-quality.ts: Added currentPrice parameter, price movement check
- app/api/trading/check-risk/route.ts: Added currentPrice to RiskCheckRequest interface
- app/api/trading/execute/route.ts: Pass openResult.fillPrice as currentPrice
- app/api/analytics/reentry-check/route.ts: Pass currentPrice from metrics
Example scenarios:
- ETH $170 SHORT → $153 LONG (10% move) = reversal allowed ✅
- ETH $154.50 SHORT → $154.30 LONG (0.13% move) = chop blocked ⚠️
Deployed: 09:18 CET Nov 14, 2025
Container: trading-bot-v4
PHASE 1 IMPLEMENTATION:
Signal quality scoring now checks database for recent trading patterns
and applies penalties to prevent overtrading and flip-flop losses.
NEW PENALTIES:
1. Overtrading: 3+ signals in 30min → -20 points
- Detects consolidation zones where system generates excessive signals
- Counts both executed trades AND blocked signals
2. Flip-flop: Opposite direction in last 15min → -25 points
- Prevents rapid long→short→long whipsaws
- Example: SHORT at 10:00, LONG at 10:12 = blocked
3. Alternating pattern: Last 3 trades flip directions → -30 points
- Detects choppy market conditions
- Pattern like long→short→long = system getting chopped
DATABASE INTEGRATION:
- New function: getRecentSignals() in lib/database/trades.ts
- Queries last 30min of trades + blocked signals
- Checks last 3 executed trades for alternating pattern
- Zero performance impact (fast indexed queries)
ARCHITECTURE:
- scoreSignalQuality() now async (requires database access)
- All callers updated: check-risk, execute, reentry-check
- skipFrequencyCheck flag available for special cases
- Frequency penalties included in qualityResult breakdown
EXPECTED IMPACT:
- Eliminate overnight flip-flop losses (like SOL $141-145 chop)
- Reduce overtrading during sideways consolidation
- Better capital preservation in non-trending markets
- Should improve win rate by 5-10% by avoiding worst setups
TESTING:
- Deploy and monitor next 5 signals in choppy markets
- Check logs for frequency penalty messages
- Analyze if blocked signals would have been losers
Files changed:
- lib/database/trades.ts: Added getRecentSignals()
- lib/trading/signal-quality.ts: Made async, added frequency checks
- app/api/trading/check-risk/route.ts: await + symbol parameter
- app/api/trading/execute/route.ts: await + symbol parameter
- app/api/analytics/reentry-check/route.ts: await + skipFrequencyCheck
- Add BlockedSignal table with 25 fields for comprehensive signal analysis
- Track all blocked signals with metrics (ATR, ADX, RSI, volume, price position)
- Store quality scores, block reasons, and detailed breakdowns
- Include future fields for automated price analysis (priceAfter1/5/15/30Min)
- Restore signalQualityVersion field to Trade table
Database changes:
- New table: BlockedSignal with indexes on symbol, createdAt, score, blockReason
- Fixed schema drift from manual changes
API changes:
- Modified check-risk endpoint to save blocked signals automatically
- Fixed hasContextMetrics variable scope (moved to line 209)
- Save blocks for: quality score too low, cooldown period, hourly limit
- Use config.minSignalQualityScore instead of hardcoded 60
Database helpers:
- Added createBlockedSignal() function with try/catch safety
- Added getRecentBlockedSignals(limit) for queries
- Added getBlockedSignalsForAnalysis(olderThanMinutes) for automation
Documentation:
- Created BLOCKED_SIGNALS_TRACKING.md with SQL queries and analysis workflow
- Created SIGNAL_QUALITY_OPTIMIZATION_ROADMAP.md with 5-phase plan
- Documented data-first approach: collect 10-20 signals before optimization
Rationale:
Only 2 historical trades scored 60-64 (insufficient sample size for threshold decision).
Building data collection infrastructure before making premature optimizations.
Phase 1 (current): Collect blocked signals for 1-2 weeks
Phase 2 (next): Analyze patterns and make data-driven threshold decision
Phase 3-5 (future): Automation and ML optimization
- Add market data cache service (5min expiry) for storing TradingView metrics
- Create /api/trading/market-data webhook endpoint for continuous data updates
- Add /api/analytics/reentry-check endpoint for validating manual trades
- Update execute endpoint to auto-cache metrics from incoming signals
- Enhance Telegram bot with pre-execution analytics validation
- Support --force flag to override analytics blocks
- Use fresh ADX/ATR/RSI data when available, fallback to historical
- Apply performance modifiers: -20 for losing streaks, +10 for winning
- Minimum re-entry score 55 (vs 60 for new signals)
- Fail-open design: proceeds if analytics unavailable
- Show data freshness and source in Telegram responses
- Add comprehensive setup guide in docs/guides/REENTRY_ANALYTICS_QUICKSTART.md
Phase 1 implementation for smart manual trade validation.
- 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.
CRITICAL: Cooldown was global across ALL symbols, causing missed opportunities
Example: ETH trade at 10:00 blocked SOL trade at 10:04 (5min cooldown)
Changes:
- Added getLastTradeTimeForSymbol() function to query last trade per symbol
- Updated check-risk endpoint to use symbol-specific cooldown
- Each coin (SOL/ETH/BTC) now has independent cooldown timer
- Cooldown message shows symbol: 'Must wait X min before next SOL-PERP trade'
Result: Can trade ETH and SOL simultaneously without interference
Example: ETH LONG at 10:00, SOL SHORT at 10:01 = both allowed
- 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
- Add getLastTrade() function to database service
- Create /api/analytics/last-trade endpoint
- Display last trade with full details on analytics page
- Show entry/exit prices, P&L, position size, targets
- Visual indicators for trade direction and exit reason
- Helps quickly diagnose where trades went (TP1, TP2, or SL)
Bug: MAE/MFE was tracked in memory during trades but not saved to database on exit
Cause: updateTradeExit() wasn't receiving or saving MAE/MFE parameters
Changes:
- Added MAE/MFE fields to UpdateTradeExitParams interface
- Modified updateTradeExit() to save maxFavorableExcursion, maxAdverseExcursion, maxFavorablePrice, maxAdversePrice
- Updated both updateTradeExit() calls in Position Manager to pass MAE/MFE values
- Enhanced exit logging to show final MAE/MFE percentages
Impact: Future trades will now properly save MAE/MFE data for analytics
Note: Past 2 trades (from before this fix) don't have MAE/MFE saved
- Added getFundingRate() method to DriftService
- Capture expectedEntryPrice from oracle before order execution
- Capture fundingRateAtEntry from Drift Protocol
- Save market context fields to database (expectedEntryPrice, fundingRateAtEntry)
- Calculate entry slippage percentage in createTrade()
- Fixed template literal syntax errors in execute endpoint
Database fields populated:
- expectedEntryPrice: Oracle price before order
- entrySlippagePct: Calculated from entrySlippage
- fundingRateAtEntry: Current funding rate from Drift
Next: Phase 3 (analytics API) or test market context on next trade
- Add Position Manager state persistence to survive restarts
- Auto-restore open trades from database on startup
- Save state after TP1, SL adjustments, profit locks
- Persist to configSnapshot JSON field
- Add automatic order cancellation
- Cancel all TP/SL orders when position fully closed
- New cancelAllOrders() function in drift/orders.ts
- Prevents orphaned orders after manual closes
- Improve stop loss management
- Move SL to +0.35% after TP1 (was +0.15%)
- Gives more breathing room for retracements
- Still locks in half of TP1 profit
- Add database sync when Position Manager closes trades
- Auto-update Trade record with exit data
- Save P&L, exit reason, hold time
- Fix analytics showing stale data
- Add trade state management functions
- updateTradeState() for Position Manager persistence
- getOpenTrades() for startup restoration
- getInitializedPositionManager() for async init
- Create n8n database analytics workflows
- Daily report workflow (automated at midnight)
- Pattern analysis (hourly/daily performance)
- Stop loss effectiveness analysis
- Database analytics query workflow
- Complete setup guide (N8N_DATABASE_SETUP.md)
- 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
