Root cause: training environment differs from validation backtest in 3 ways:
1. 100-bar episodes force exits (val runs continuous) → position-gated done
2. Rank normalization destroys sparse trade-level reward → remove it
3. Different Sharpe computation (per-trade vs per-bar, different annualization)
Single execution path:
Phase 1: Episode alignment (100→5000 bars, position-gated done, soft reset)
Phase 2: Reward alignment (remove rank norm, raw trade P&L to replay)
Phase 3: Metrics alignment (un-annualized per-trade Sharpe, both paths)
Expected: training Sharpe within 2× of validation with same weights.
Removes 5 unnecessary shaping components that fought the broken signal.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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