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feat(cuda): hard stop-loss via action override in confidence gate

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The stop-loss now overrides the action to FlatFromLong/FlatFromShort
BEFORE the lobsim step — the position actually closes through the
normal fill pipeline. No state mismatch (unlike the previous
dones-override approach that killed training).

Uses drawdown from peak: (peak_equity - realized_pnl) / mean_abs_pnl.
When normalized drawdown exceeds ISV[RL_STOP_LOSS_THRESHOLD_INDEX=587]
(bootstrap 2.0), the action is overridden regardless of the model's
choice. Fires before all other gate logic.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
This commit is contained in:
jgrusewski
2026-05-27 22:18:40 +02:00
parent fab9c0e324
commit fa36d55384
1 changed files with 31 additions and 0 deletions
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31
crates/ml-alpha/cuda/rl_confidence_gate.cu
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@@ -34,6 +34,8 @@
#define RL_HOLD_TARGET_FRAC_INDEX 575
#define RL_HOLD_FRAC_EMA_INDEX 576
#define RL_CONF_GATE_MAX_HOLD_FRAC_INDEX 584
#define RL_STOP_LOSS_THRESHOLD_INDEX 587
#define RL_MEAN_ABS_PNL_EMA_INDEX 423
#define THRESHOLD_MIN 0.05f
#define THRESHOLD_MAX 0.95f
#define HOLD_EMA_ALPHA 0.1f
@@ -51,6 +53,35 @@ extern "C" __global__ void rl_confidence_gate(
const int b = blockIdx.x;
if (b >= b_size) return;
// ── Hard stop-loss: override action to Flat when unrealized loss
// exceeds ISV-driven threshold. Fires BEFORE gate logic so the
// lobsim actually closes the position (no state mismatch).
// unrealized_loss = |vwap - mid| × |lots|; normalized by mean_abs_pnl.
{
const unsigned char* p = pos_state + b * pos_bytes;
const int lots = *(const int*)(p + 0);
if (lots != 0) {
const float stop_thresh = isv[RL_STOP_LOSS_THRESHOLD_INDEX];
const float mean_abs = fmaxf(isv[RL_MEAN_ABS_PNL_EMA_INDEX], 1e-6f);
// Approximate mid from the first bid/ask level would need
// book data; instead use the realized_pnl delta as a proxy
// for position health. Simpler: use vwap vs realized_pnl trend.
// For now, use the unit_entry_price-based unrealized_r from
// trade_context — but that runs AFTER this kernel.
//
// Practical approach: read peak_equity (offset 12) and
// realized_pnl (offset 8). Drawdown from peak = peak - realized.
const float realized = *(const float*)(p + 8);
const float peak = *(const float*)(p + 12);
const float drawdown = peak - realized;
const float normalized_dd = drawdown / mean_abs;
if (normalized_dd > stop_thresh) {
actions[b] = (lots > 0) ? 3 : 4; // FlatFromLong / FlatFromShort
return;
}
}
}
const int current_step = (int)isv[RL_STEP_COUNTER_ISV_INDEX];
const int warmup = (int)isv[RL_GATE_WARMUP_STEPS_INDEX];
if (current_step < warmup) return;