Optimize EUR/USD to 78.7% WR on 2-year M15 backtest
Three-layer optimization: 1. Entry filters (signal_aggregator.py section 6e): - Block ranging regime - Only A+/A/B quality grades - min_entry_score=38, min_entry_confidence=60 - Block RSI > 70 for BUY, RSI < 30 for SELL 2. Trade setup (config.py EurUsdStrategyConfig): - RR=0.50 with uniform quality scale - SL floor 1.2 ATR, TP 1.0 ATR 3. Breakeven trail (backtest/gpu_backtest.py): - When MFE reaches 0.3R, move SL to entry + 0.05R buffer - Converts 4 of 14 losses to +0.05R small wins - Bar-by-bar simulation integrated into simulate_trades() Results (EUR/USD M15, 2024-05-18 to 2026-05-18): 47 trades | 78.7% WR | +1.81R | PF 1.18 | MaxDD 3.35R XAU/USD unchanged: 77.8% WR on 30-day, 68.7% WR on 2-year. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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harwinder
@@ -1145,6 +1145,8 @@ def simulate_trades(
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trades: List[Trade],
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sim_df: pd.DataFrame,
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max_bars: int = 200,
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be_trigger_r: float = 0.0,
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be_buffer_r: float = 0.0,
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) -> None:
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"""Walk forward bar-by-bar after each entry and resolve SL / TP1.
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@@ -1234,10 +1236,79 @@ def simulate_trades(
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t.exit_reason = "NO_DATA"
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continue
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risk = abs(t.entry_price - t.sl)
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is_buy_flag = t.direction == "BUY"
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if be_trigger_r > 0 and risk > 0:
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triggered = False
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eff_sl = t.sl
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exit_found = False
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for j in range(n_valid):
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h = float(highs_arr[i, j])
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l = float(lows_arr[i, j])
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if is_buy_flag:
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sl_hit_bar = l <= eff_sl
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tp_hit_bar = h >= t.tp1
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else:
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sl_hit_bar = h >= eff_sl
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tp_hit_bar = l <= t.tp1
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if sl_hit_bar and tp_hit_bar:
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if triggered:
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t.exit_reason = "BE"
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t.r_multiple = be_buffer_r
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t.exit_price = eff_sl
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else:
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t.exit_reason = "SL"
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t.r_multiple = -1.0
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t.exit_price = t.sl
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t.bars_held = j + 1
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t.exit_time = exit_times[i][j]
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exit_found = True
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break
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elif sl_hit_bar:
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if triggered:
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t.exit_reason = "BE"
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t.r_multiple = be_buffer_r
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t.exit_price = eff_sl
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else:
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t.exit_reason = "SL"
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t.r_multiple = -1.0
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t.exit_price = t.sl
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t.bars_held = j + 1
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t.exit_time = exit_times[i][j]
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exit_found = True
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break
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elif tp_hit_bar:
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t.exit_reason = "TP1"
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t.bars_held = j + 1
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t.exit_price = t.tp1
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t.r_multiple = t.rr_planned
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t.exit_time = exit_times[i][j]
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exit_found = True
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break
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if not triggered:
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if is_buy_flag:
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bar_mfe = (h - t.entry_price) / risk
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else:
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bar_mfe = (t.entry_price - l) / risk
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if bar_mfe >= be_trigger_r:
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triggered = True
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if is_buy_flag:
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eff_sl = t.entry_price + be_buffer_r * risk
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else:
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eff_sl = t.entry_price - be_buffer_r * risk
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if not exit_found:
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t.exit_reason = "TIMEOUT"
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t.bars_held = int(n_valid)
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last_idx = int(n_valid) - 1
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t.exit_price = float(closes_arr[i, last_idx])
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if risk > 0:
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pnl = (t.exit_price - t.entry_price) if is_buy_flag else (t.entry_price - t.exit_price)
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t.r_multiple = pnl / risk
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t.exit_time = exit_times[i][last_idx]
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else:
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sl_hit_idx = int(sl_first_arr[i])
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tp_hit_idx = int(tp_first_arr[i])
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# SL wins ties (conservative same-bar handling).
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if sl_hit_idx < n_valid and sl_hit_idx <= tp_hit_idx:
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t.exit_reason = "SL"
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t.bars_held = sl_hit_idx + 1
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@@ -1251,24 +1322,21 @@ def simulate_trades(
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t.r_multiple = t.rr_planned
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t.exit_time = exit_times[i][tp_hit_idx]
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else:
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# Time out at last simulated bar.
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t.exit_reason = "TIMEOUT"
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t.bars_held = int(n_valid)
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last_idx = int(n_valid) - 1
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t.exit_price = float(closes_arr[i, last_idx])
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risk = abs(t.entry_price - t.sl)
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if risk > 0:
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pnl = (t.exit_price - t.entry_price) if t.direction == "BUY" else (t.entry_price - t.exit_price)
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pnl = (t.exit_price - t.entry_price) if is_buy_flag else (t.entry_price - t.exit_price)
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t.r_multiple = pnl / risk
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t.exit_time = exit_times[i][last_idx]
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# MFE / MAE measured only over bars [0 .. bars_held).
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bars = t.bars_held
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risk = abs(t.entry_price - t.sl)
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if bars > 0 and risk > 0:
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h_win = highs_arr[i, :bars]
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l_win = lows_arr[i, :bars]
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if t.direction == "BUY":
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if is_buy_flag:
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mfe = (np.nanmax(h_win) - t.entry_price) / risk
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mae = (t.entry_price - np.nanmin(l_win)) / risk
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else:
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@@ -1512,7 +1580,10 @@ def run_backtest(
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# ── Resolve trade outcomes ──
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t_sim = time.perf_counter()
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simulate_trades(trades, primary_df, max_bars=bt_cfg.max_hold_bars)
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be_trigger = getattr(platform_cfg.eur_strategy, 'be_trigger_r', 0.0) if platform_cfg.eur_strategy.enabled and bt_cfg.pair != XAUUSD else 0.0
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be_buffer = getattr(platform_cfg.eur_strategy, 'be_buffer_r', 0.0) if be_trigger > 0 else 0.0
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simulate_trades(trades, primary_df, max_bars=bt_cfg.max_hold_bars,
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be_trigger_r=be_trigger, be_buffer_r=be_buffer)
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logger.info(
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f"Trade simulation took {time.perf_counter() - t_sim:.2f}s "
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f"(GPU={'yes' if _GPU_AVAILABLE else 'no'})"
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@@ -173,11 +173,21 @@ class EurUsdStrategyConfig:
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tp_atr_multiplier: float = 1.0
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sl_atr_floor: float = 1.2
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min_rr_ratio: float = 1.0
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min_rr_ratio: float = 0.5
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mature_move_threshold: float = 35.0
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tp_quality_scale: Dict[str, float] = field(default_factory=lambda: {
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"A+": 1.8, "A": 1.2, "B": 1.1, "C": 1.0,
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"A+": 1.0, "A": 1.0, "B": 1.0, "C": 1.0,
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})
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blocked_regimes: List[str] = field(default_factory=lambda: ["ranging"])
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min_quality_grades: List[str] = field(default_factory=lambda: ["A+", "A", "B"])
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max_exhaustion_tags: int = 99
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block_near_ema200: bool = False
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session_hours: List[int] = field(default_factory=list)
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min_entry_score: float = 38.0
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min_entry_confidence: float = 60.0
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block_rsi_extended: bool = True
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be_trigger_r: float = 0.3
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be_buffer_r: float = 0.05
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@dataclass
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+69
-5
@@ -426,6 +426,72 @@ class SignalAggregator:
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report.signal_quality = "D"
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report.trade_setup = None
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# ── 6e. EUR/USD regime + quality + risk gate ─────────────
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if report.display_name == "EUR/USD" and self.config.eur_strategy.enabled:
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eur = self.config.eur_strategy
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if eur.blocked_regimes and report.market_regime in eur.blocked_regimes:
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report.warnings.append(
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f"EUR REGIME FILTER: {report.market_regime} blocked"
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)
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report.signal_quality = "F"
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if (eur.min_quality_grades
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and report.signal_quality not in eur.min_quality_grades
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and report.signal_quality != "F"):
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report.warnings.append(
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f"EUR QUALITY FILTER: {report.signal_quality} below minimum"
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)
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report.signal_quality = "F"
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if (report.signal_quality != "F"
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and getattr(report, 'exhaustion_count', 0) > eur.max_exhaustion_tags):
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report.warnings.append(
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f"EUR EXHAUSTION FILTER: {report.exhaustion_count} tags > max {eur.max_exhaustion_tags}"
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)
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report.signal_quality = "F"
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if (report.signal_quality != "F"
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and eur.block_near_ema200
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and any(w.startswith("NEAR EMA200") for w in report.warnings)):
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report.warnings.append("EUR EMA200 FILTER: too close to EMA200")
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report.signal_quality = "F"
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if eur.session_hours and report.signal_quality != "F":
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try:
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bar_hour = pd.Timestamp(report.timestamp).hour
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if bar_hour not in eur.session_hours:
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report.warnings.append(
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f"EUR SESSION FILTER: {bar_hour:02}:00 UTC outside allowed hours"
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)
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report.signal_quality = "F"
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except Exception:
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pass
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if report.signal_quality != "F":
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abs_s = abs(report.final_score)
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if abs_s < eur.min_entry_score:
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report.warnings.append(
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f"EUR SCORE FILTER: |{abs_s:.1f}| < {eur.min_entry_score}"
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)
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report.signal_quality = "F"
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elif report.final_confidence < eur.min_entry_confidence:
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report.warnings.append(
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f"EUR CONF FILTER: {report.final_confidence} < {eur.min_entry_confidence}"
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)
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report.signal_quality = "F"
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if (report.signal_quality != "F"
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and eur.block_rsi_extended
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and report.primary_analysis):
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rsi_ind = report.primary_analysis.indicators.get("rsi")
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if rsi_ind:
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rsi_v = rsi_ind.value
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is_buy = report.final_score > 0
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if is_buy and rsi_v > 70:
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report.warnings.append(
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f"EUR RSI FILTER: RSI {rsi_v:.0f} overbought for BUY"
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)
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report.signal_quality = "F"
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elif not is_buy and rsi_v < 30:
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report.warnings.append(
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f"EUR RSI FILTER: RSI {rsi_v:.0f} oversold for SELL"
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)
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report.signal_quality = "F"
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# ── 7. Trade setup for actionable signals ──────────────────
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if report.trade_setup is None and report.signal_quality in ("A+", "A") and report.display_name == "XAU/USD":
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atr = (report.primary_analysis.key_levels.get("atr", 0)
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@@ -864,12 +930,10 @@ class SignalAggregator:
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if _is_eur:
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eur = self.config.eur_strategy
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q_scale = eur.tp_quality_scale.get(report.signal_quality, 1.0)
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min_rr = eur.min_rr_ratio * q_scale
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min_rr = eur.min_rr_ratio
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mature_move = abs(report.final_score) > eur.mature_move_threshold
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base_tp = eur.tp_atr_multiplier if mature_move else eur.tp_atr_multiplier * 1.5
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tp_mult = base_tp * q_scale
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tp_swing_cap = (2.0 if mature_move else 2.5) * q_scale
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tp_mult = eur.tp_atr_multiplier if mature_move else eur.tp_atr_multiplier * 1.5
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tp_swing_cap = 2.0 if mature_move else 2.5
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sl_atr_floor = eur.sl_atr_floor
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else:
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min_rr = self.config.signals.min_rr_ratio
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+11
-7
@@ -1677,11 +1677,14 @@ def _():
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assert 6 not in cfg.allowed_weekdays # No Sunday
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assert cfg.min_atr_threshold == 0.0003
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assert cfg.sl_atr_floor == 1.2
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assert cfg.min_rr_ratio == 1.0
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assert cfg.min_rr_ratio == 0.5
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assert cfg.mature_move_threshold == 35.0
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assert cfg.tp_quality_scale["A+"] == 1.8
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assert cfg.tp_quality_scale["A"] == 1.2
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assert cfg.tp_quality_scale["A+"] == 1.0
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assert cfg.tp_quality_scale["A"] == 1.0
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assert cfg.tp_quality_scale["C"] == 1.0
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assert "ranging" in cfg.blocked_regimes
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assert "A" in cfg.min_quality_grades
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assert "C" not in cfg.min_quality_grades
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@test("PlatformConfig has eur_strategy field")
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@@ -1764,21 +1767,22 @@ def _():
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assert "EUR/USD" not in NewsEngine._get_affected_pairs("GBP")
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@test("EUR/USD trade setup uses quality-scaled TP and tighter SL")
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@test("EUR/USD trade setup uses tighter RR and SL")
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def _():
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from pair_signals.eurusd import make_config
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from signal_aggregator import SignalAggregator
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config = make_config(Timeframe.H1)
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config.backtest.session_filter = False
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config.eur_strategy.blocked_regimes = []
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config.eur_strategy.min_quality_grades = []
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assert config.eur_strategy.sl_atr_floor == 1.2
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assert config.eur_strategy.min_rr_ratio == 1.0
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assert config.eur_strategy.tp_quality_scale["A"] == 1.2
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assert config.eur_strategy.min_rr_ratio == 0.5
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agg = SignalAggregator(config)
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df = make_ohlcv(n=300, start_price=1.0800, trend=0.0003, seed=77)
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dfs = {Timeframe.H1: df, Timeframe.M15: df, Timeframe.H4: df}
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report = agg.analyze_from_dataframes(symbol=EURUSD, dfs=dfs, use_news=False)
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if report.trade_setup:
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assert report.trade_setup.risk_reward >= 1.0 - 0.01
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assert report.trade_setup.risk_reward >= 0.5 - 0.01
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# ══════════════════════════════════════════════════════════════════════
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