Files
foxhunt/archive/reports/backtest_marginal_example.md
jgrusewski 2df1ea92e1 feat(ml): WAVE 29 DQN Codebase Cleanup & Refactoring Campaign
BREAKING CHANGES:
- Removed orphaned dqn.rs monolithic trainer (4,975 lines)
- Removed orphaned dqn_ensemble.rs module (816 lines)
- Removed orphaned tft.rs and tft_complete_int8_integration_test.rs
- TFT trainer split into modular directory structure

DQN Module Refactoring:
- Split trainers/dqn.rs into modular structure (config.rs, statistics.rs, trainer.rs)
- Fixed hyperopt 39D search space (continuous params only)
- Boolean flags (use_dueling, use_double_dqn, use_per, use_noisy_nets) are now FIXED architectural decisions
- use_distributional defaults to false (Candle BUG #36 - scatter_add gradient issues)

Clean Module Structure:
- ml/src/trainers/dqn/ directory with proper mod.rs exports
- ml/src/trainers/tft/ directory with config.rs, types.rs, model.rs, trainer.rs, tests.rs
- All P0 features validated: TD-error clamping, batch diversity, LR scheduler, priority staleness

Documentation:
- Added comprehensive docs in docs/codebase-cleanup/
- ADR-001 for DQN refactoring decisions
- Rainbow DQN component matrix and quick reference guides

Build Status: Compiles with zero errors

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

Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-27 23:46:13 +01:00

1.7 KiB

DQN Backtesting Report

Model: DQN-Marginal-Example Baseline: DQN-Trial35-Baseline Generated: 2025-11-04 07:56:33 UTC


Performance Summary

Metric Value Target Status
Total Return 5.30% >0%
Sharpe Ratio 1.20 >1.5
Max Drawdown 22.80% <20%
Win Rate 48.0% >50%
Alpha vs B&H 0.80% >0%

Comparison to Baseline

Metric Baseline New Model Change Direction
Returns 12.10% 5.30% -6.80% ↘️
Sharpe 1.80 1.20 -0.60 ↘️
Drawdown 18.30% 22.80% +4.50% ↘️
Win Rate 52.0% 48.0% -4.0% ↘️
Alpha 1.50% 0.80% -0.70% ↘️

Trade Statistics

Metric Value
Total Trades 125
Avg Trade Return 0.042%
Win Rate 48.00%
Trades vs Baseline -13

Deployment Recommendation

Status: ⚠️ REVIEW - Marginal Performance

Model passes 2/5 production criteria. Performance is marginal and requires careful review.

Concerns:

  • Low Sharpe ratio (1.20 < 1.5)
  • Excessive drawdown (22.80% > 20%)
  • Poor win rate (48.0% < 50%)

Action: Conduct detailed risk assessment and consider additional testing before deployment.

Production Criteria Checklist

  • Criteria Passed: 2/5
  • Total Return: PASS (5.30% > 0%)
  • Sharpe Ratio: FAIL (1.20 > 1.5)
  • Max Drawdown: FAIL (22.80% < 20%)
  • Win Rate: FAIL (48.0% > 50%)
  • Alpha vs B&H: PASS (0.80% > 0%)

Report generated automatically by Foxhunt ML Evaluation Framework