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).
This commit is contained in:
Harwinder Sekhon
+42
-139
@@ -227,38 +227,41 @@ class SignalAggregator:
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if bt.regime_filter:
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self._apply_regime_filter_live(report, dfs)
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if bt.session_filter:
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xau_active = (
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self.config.xau_strategy.enabled
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and any("XAU STRATEGY" in r for r in report.bullish_reasons)
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)
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if not xau_active:
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self._apply_session_filter_live(report)
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# Session window + blocked hours on the signal bar's CLOSE time —
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# the exact predicate the backtester's replay loop applies before
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# each bar, so live and backtest cannot diverge. Bar-close time
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# (not wall clock) makes manual mid-candle scans behave like
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# boundary auto-scans. This replaces an older wall-clock filter
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# that was guarded by a marker string no code wrote.
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if bt.session_filter and report.primary_analysis is not None:
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try:
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bar_close = (
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pd.Timestamp(report.timestamp)
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+ pd.Timedelta(
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seconds=ForexDataProvider.CANDLE_SECONDS[
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self.config.primary_timeframe
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]
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)
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)
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close_h = bar_close.hour
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_is_xau = pair_info["display"] == "XAU/USD"
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_blocked = (self.config.xau_strategy.blocked_hours_utc
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if _is_xau else bt.blocked_hours_utc)
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outside = not (bt.session_start_hour <= close_h < bt.session_end_hour)
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if outside or close_h in _blocked:
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report.warnings.append(
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f"SESSION FILTER: bar closes {close_h:02}:00 UTC — "
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+ ("outside window" if outside else "blocked hour")
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)
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report.final_signal = SignalStrength.NEUTRAL
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report.signal_quality = "F"
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report.action_recommendation = "NO TRADE — Outside tradeable session"
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report.trade_setup = None
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except Exception:
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pass
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return report
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def _apply_session_filter_live(self, report: SignalReport) -> None:
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"""Skip signals outside the configured UTC trading window."""
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bt = self.config.backtest
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now_h = datetime.now(timezone.utc).hour
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if not (bt.session_start_hour <= now_h < bt.session_end_hour):
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report.warnings.append(
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f"SESSION FILTER: {now_h:02}:00 UTC outside "
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f"{bt.session_start_hour:02}:00-{bt.session_end_hour:02}:00 — skipping"
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)
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report.final_signal = SignalStrength.NEUTRAL
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report.signal_quality = "F"
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report.action_recommendation = (
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f"NO TRADE — Outside session "
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f"({bt.session_start_hour:02}-{bt.session_end_hour:02} UTC; now {now_h:02})"
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)
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report.trade_setup = None
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else:
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report.warnings.append(
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f"Session: {now_h:02}:00 UTC inside trading window "
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f"{bt.session_start_hour:02}-{bt.session_end_hour:02}"
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)
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def _apply_regime_filter_live(
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self, report: SignalReport, dfs: Dict[Timeframe, pd.DataFrame]
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) -> None:
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@@ -931,112 +934,6 @@ class SignalAggregator:
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# ── Internals ──────────────────────────────────────────────────
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def _check_xau_oversold_bounce(
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self, report: SignalReport, dfs: Dict[Timeframe, pd.DataFrame]
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) -> bool:
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"""Return True when XAU/USD oversold-bounce conditions are met."""
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cfg = self.config.xau_strategy
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try:
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bar_hour = pd.Timestamp(report.timestamp).hour
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if bar_hour in cfg.blocked_hours_utc:
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return False
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except Exception:
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return False
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m15_analysis = None
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h4_analysis = None
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for ca in report.confirmation_analyses:
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if ca.timeframe == Timeframe.M15.value:
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m15_analysis = ca
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elif ca.timeframe == Timeframe.H4.value:
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h4_analysis = ca
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h1_analysis = report.primary_analysis
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if not m15_analysis or not h1_analysis:
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return False
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m15_rsi = m15_analysis.indicators.get("rsi")
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if not m15_rsi or m15_rsi.value >= cfg.rsi_entry_threshold:
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return False
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ema200_count = 0
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m15_ema200 = m15_analysis.key_levels.get("ema_trend")
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m15_df = dfs.get(Timeframe.M15)
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if m15_df is not None and m15_ema200 is not None:
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m15_price = float(m15_df["Close"].iloc[-1])
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if m15_price > m15_ema200:
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ema200_count += 1
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h1_ema200 = h1_analysis.key_levels.get("ema_trend")
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if h1_ema200 is not None and report.current_price > h1_ema200:
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ema200_count += 1
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if h4_analysis:
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h4_ema200 = h4_analysis.key_levels.get("ema_trend")
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h4_df = dfs.get(Timeframe.H4)
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if h4_df is not None and h4_ema200 is not None:
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h4_price = float(h4_df["Close"].iloc[-1])
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if h4_price > h4_ema200:
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ema200_count += 1
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if ema200_count < cfg.min_ema200_tfs:
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return False
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return True
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def _generate_xau_trade_setup(
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self, report: SignalReport, dfs: Dict[Timeframe, pd.DataFrame]
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) -> Optional[TradeSetup]:
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"""Generate XAU-specific trade setup with backtested TP/SL."""
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cfg = self.config.xau_strategy
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m15_analysis = None
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for ca in report.confirmation_analyses:
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if ca.timeframe == Timeframe.M15.value:
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m15_analysis = ca
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break
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if not m15_analysis:
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return None
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atr = m15_analysis.key_levels.get("atr", 0)
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if atr <= 0:
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return None
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price = report.current_price
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pip_value = 0.10
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quality_scale = self._TP_QUALITY_SCALE.get(report.signal_quality, 0.75)
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tp_mult = cfg.tp_atr_multiplier * quality_scale
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tp1 = price + tp_mult * atr
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sl = price - cfg.sl_atr_multiplier * atr
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tp2 = price + tp_mult * 1.5 * atr
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tf = self.config.signals.tp_tightening_factor
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tp1 = price + (tp1 - price) * tf
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tp2 = price + (tp2 - price) * tf
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sl_distance = price - sl
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tp_distance = tp1 - price
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rr = tp_distance / sl_distance if sl_distance > 0 else 0
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return TradeSetup(
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pair=report.symbol,
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display_name=report.display_name,
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direction="BUY",
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entry_price=price,
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stop_loss=round(sl, 2),
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take_profit_1=round(tp1, 2),
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take_profit_2=round(tp2, 2),
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risk_reward=round(rr, 2),
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risk_pips=round(sl_distance / pip_value, 1),
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reward_pips=round(tp_distance / pip_value, 1),
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pip_value=pip_value,
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)
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_TP_QUALITY_SCALE = {"A+": 2.0, "A": 1.5, "B": 1.0, "C": 1.0}
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def _generate_xau_atr_trade_setup(
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@@ -1143,15 +1040,17 @@ class SignalAggregator:
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if primary and report.market_regime.startswith("trending"):
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rsi_ind = primary.indicators.get("rsi")
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bb_ind = primary.indicators.get("bollinger")
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# Pullback bonuses require a KNOWN trend direction — the mixed
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# "trending" regime (EMAs unaligned) gets no directional bonus.
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if rsi_ind:
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rsi_val = rsi_ind.value
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if report.market_regime in ("trending_up", "trending") and score > 0 and 38 <= rsi_val <= 55:
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if report.market_regime == "trending_up" and score > 0 and 38 <= rsi_val <= 55:
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confidence += 5
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elif report.market_regime == "trending_down" and score < 0 and 45 <= rsi_val <= 62:
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confidence += 5
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if bb_ind:
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bb_pos = bb_ind.value
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if report.market_regime in ("trending_up", "trending") and score > 0 and bb_pos < 0.4:
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if report.market_regime == "trending_up" and score > 0 and bb_pos < 0.4:
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confidence += 5
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elif report.market_regime == "trending_down" and score < 0 and bb_pos > 0.6:
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confidence += 5
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@@ -1246,19 +1145,23 @@ class SignalAggregator:
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if report.market_regime.startswith("trending"):
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rsi_ind = primary.indicators.get("rsi")
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bb_ind = primary.indicators.get("bollinger")
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# Extension penalties apply in ANY strong-ADX regime; the
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# mixed "trending" regime penalizes BOTH directions (it
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# previously penalized only BUYs — the SELL side of the
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# same bullish-bias bug fixed in the RSI reinterpretation).
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if rsi_ind:
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rsi_val = rsi_ind.value
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if report.market_regime in ("trending_up", "trending") and score > 0 and rsi_val > 65:
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report.warnings.append(f"Extended — RSI {rsi_val:.0f} in uptrend")
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penalties.append(("rsi_extended", 5))
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elif report.market_regime == "trending_down" and score < 0 and rsi_val < 35:
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elif report.market_regime in ("trending_down", "trending") and score < 0 and rsi_val < 35:
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report.warnings.append(f"Extended — RSI {rsi_val:.0f} in downtrend")
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penalties.append(("rsi_extended", 5))
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if bb_ind:
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bb_pos = bb_ind.value
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if report.market_regime in ("trending_up", "trending") and score > 0 and bb_pos > 0.85:
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penalties.append(("bb_overextended", 8))
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elif report.market_regime == "trending_down" and score < 0 and bb_pos < 0.15:
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elif report.market_regime in ("trending_down", "trending") and score < 0 and bb_pos < 0.15:
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penalties.append(("bb_overextended", 8))
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# Hard block: static exhaustion + fading momentum → kill the trade
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