Audit fixes: mixed-regime bias, live==backtest session parity, parallel replay
Fix 1 — mixed-"trending" regime (ADX strong, EMAs unaligned) was hard-coded bullish in 5 sites: RSI reinterpretation used the uptrend playbook (RSI 38-55 -> STRONG_BUY conf 75), BUY-only confidence bonuses, BUY-only extension penalties, no counter-trend penalty. Now: extremes-only RSI (as transitioning), no directional bonuses, symmetric extension penalties. 6yr validation: H1 +67.2->+61.9R (mixed skew 16B/11S -> 4B/7S), H4 +31.6->+27.5R (the 4 bias BUYs), M15 +152.6->+154.7R, M5 +207.1->+206.1R with maxDD 28.7->24.3R. The ~8R aggregate give-back is bull-market subsidy from the bug. Fix 2 — live session filter now applies the EXACT replay-loop predicate (session window + blocked hours on the signal bar's CLOSE time, from the bar timestamp not wall clock). Replaces a wall-clock filter gated on a "XAU STRATEGY" marker that no code writes, which made live diverge from every validated book. Fix 3 — delete dead _check_xau_oversold_bounce and _generate_xau_trade_setup (unreachable; the latter hardcoded BUY and skipped the spread/RR gates). Backtester: parallel bar replay via forked workers (--workers, default auto = cores-2 capped 12). Per-bar evaluation is pure; the entry cooldown is applied in an ordered phase-2 pass. Proven byte-identical to sequential on the same window; ~300 -> 1030-1680 bars/s (6yr M5: ~26min -> 5-8min). --workers 1 = sequential path. Tests: 179 passed (new mixed-regime RSI regression test).
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@@ -116,7 +116,7 @@ The `backtest/` directory contains `gpu_backtest.py` — a GPU-accelerated backt
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Fill realism: charges a round-trip spread per trade (`--spread`; defaults to the pair's `default_spread` in PAIR_INFO), fills gap-through SL/TP at the bar open, and resolves trades against the RAW price path (the parquet cache stores raw bars; validation/cleaning runs on load — signals see cleaned data, trade resolution sees real spikes). Entry is at the next bar's open after the signal bar. Weekend/session filters evaluate bar-close (decision) time to match the live bot's wall clock.
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GPU note: CuPy needs the NVIDIA runtime pip wheels (`nvidia-cuda-runtime-cu12`, `nvidia-cuda-nvrtc-cu12`, `nvidia-curand-cu12`, `nvidia-nvjitlink-cu12`) or it silently falls back to NumPy — check the "Backend:" line in the run log. The bar-replay loop itself is single-threaded Python either way (~340 bars/s); GPU only accelerates indicator precompute and SL/TP scanning.
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GPU note: CuPy needs the NVIDIA runtime pip wheels (`nvidia-cuda-runtime-cu12`, `nvidia-cuda-nvrtc-cu12`, `nvidia-curand-cu12`, `nvidia-nvjitlink-cu12`) or it silently falls back to NumPy — check the "Backend:" line in the run log. GPU accelerates indicator precompute and SL/TP scanning; the bar-replay loop is Python (~300 bars/s/core) but fans out across forked worker processes (`--workers`, default auto = cores−2 capped at 12, ~1700 bars/s at 10). Per-bar signal evaluation is pure, so parallel and sequential books are identical (the entry cooldown is applied in an ordered pass afterwards); `--workers 1` forces the sequential path.
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## Code Conventions
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