- Updated .github/copilot-instructions.md key constraints and signal quality system description
- Updated config/trading.ts minimum score from 60 to 81 with v8 performance rationale
- Updated SIGNAL_QUALITY_SETUP_GUIDE.md intro to reflect 81 threshold
- Updated SIGNAL_QUALITY_OPTIMIZATION_ROADMAP.md current system section
- Updated BLOCKED_SIGNALS_TRACKING.md quality score requirements
Context: After v8 Money Line indicator deployed with 0.6% flip threshold,
system achieving 66.7% win rate with average quality score 94.2. Raised
minimum threshold from 60 to 81 to maintain exceptional selectivity.
Current v8 stats: 6 trades, 4 wins, $649.32 profit, 94.2 avg quality
Account growth: $540 → $1,134.92 (110% gain in 2-3 days)
- 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
