jgrusewski 261bbef86e feat(wire-02): Document Wave D adaptive position sizer integration gap ...

CRITICAL FINDING: RegimeAdaptiveFeatures (Features 221-224) are fully
implemented but NOT integrated into trading decision flow.

Analysis Results:
- ✅ RegimeAdaptiveFeatures: 644 lines, 12/12 tests passing
- ✅ Database schema: regime_states, regime_transitions, adaptive_strategy_metrics
- ✅ gRPC endpoints: GetRegimeState, GetRegimeTransitions defined
- ❌ Trading Agent Service: NO regime integration in allocation.rs
- ❌ Order Generation: NO stop-loss multiplier application

Impact:
- ML models train with regime features
- Production trading IGNORES regime state
- Position sizes remain STATIC (no 0.2x-1.5x adjustment)
- Expected Sharpe improvement: 0% (instead of +25-50%)

Integration Plan (11 hours):
1. Phase 1: Database query layer (2h) - regime.rs
2. Phase 2: Allocation integration (3h) - RegimeAdaptive method
3. Phase 3: Service wiring (2h) - RegimeDetector in service
4. Phase 4: Order generation (1h) - stop-loss multipliers
5. Phase 5: Testing (3h) - regime allocation tests

Code Changes:
- New files: regime.rs (200 lines), tests (300 lines)
- Modified: allocation.rs (+100), service.rs (+50), orders.rs (+30)
- Total: ~500 new lines, ~180 modified lines

Performance: +3ms latency (acceptable for +25-50% Sharpe)
Risk: Low (feature flag + 3-level rollback plan)

Recommendation: PROCEED before 225-feature ML retraining

Files:
- AGENT_WIRE02_ADAPTIVE_SIZER_INTEGRATION.md (full analysis)
- AGENT_WIRE02_QUICK_SUMMARY.md (executive summary)

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

2025-10-19 09:45:54 +02:00

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