ROOT CAUSE: 5 interlocking bugs made learning impossible:
1. DSR denominator floor 1e-12 produced values in millions → drowned all signal
2. Global [-1,+1] clamp destroyed Bellman equation signal (can't distinguish
catastrophic loss from mild loss)
3. v_range=20 exactly equals V_max for gamma=0.95 → Bellman target pins at
ceiling → Q-values saturate → Q-gap collapses to 0.0000
4. num_atoms=11 over 40-unit range = 4.0 per atom (C51 paper min is 51)
5. 6/7 reward components were penalties → mean_reward=-0.311 regardless of action
FIXES:
- DSR denominator floor: 1e-12 → 0.01 (prevents million-scale spikes)
- Each component individually clamped BEFORE weighting (DSR to [-1,+1],
z-score to [-3,+3], drawdown to [0,1], time decay to [0,0.3])
- Removed global [-1,+1] clamp (no longer needed with bounded components)
- profit_take_bonus: 0.1 → 0.01 (was 100x too large, caused reward hacking)
- Removed confidence scaling (positive feedback loop destabilized learning)
- Removed regime scaling (non-stationary reward confused the model)
- Dynamic v_range from gamma: v_range = 2.5/(1-gamma)*1.2 (always covers Q range)
- num_atoms minimum: 11 → 51 (C51 paper standard)
- gamma default: 0.99 → 0.95
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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