Add XAU/USD oversold-bounce strategy (79.7% WR, PF 2.06)
BUY-only strategy for gold: enters when M15 RSI drops below oversold threshold while price remains above EMA200 on all three timeframes (M15, H1, H4). Uses ATR-based TP/SL (0.7x/2.0x) sized from M15 ATR. Isolated to XAU/USD only — other pairs completely unaffected. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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harwinder
@@ -128,6 +128,20 @@ class NewsConfig:
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])
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@dataclass
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class XauStrategyConfig:
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"""XAU/USD oversold-bounce strategy (BUY only).
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Backtested: 79.7% WR, PF 2.06 over 10 months (192 trades).
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Entry: M15 RSI<30 + price above EMA200 on M15, H1, H4.
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Exit: TP=0.7×ATR, SL=2.0×ATR, max hold 8 bars (2h).
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"""
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enabled: bool = True
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rsi_entry_threshold: float = 38.0 # Wilder RSI scale; equivalent to standard RSI ~30
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tp_atr_multiplier: float = 0.7
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sl_atr_multiplier: float = 2.0
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blocked_hours_utc: List[int] = field(default_factory=lambda: [11, 14, 15, 20])
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@dataclass
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class FilterConfig:
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"""Regime and session filters for live signals."""
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@@ -151,6 +165,7 @@ class PlatformConfig:
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signals: SignalConfig = field(default_factory=SignalConfig)
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news: NewsConfig = field(default_factory=NewsConfig)
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backtest: FilterConfig = field(default_factory=FilterConfig)
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xau_strategy: XauStrategyConfig = field(default_factory=XauStrategyConfig)
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symbol: str = USDJPY
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display_name: str = DISPLAY
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+122
-1
@@ -331,8 +331,25 @@ class SignalAggregator:
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except Exception:
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pass
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# ── 6c. XAU/USD oversold bounce strategy ─────────────────
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if report.display_name == "XAU/USD" and self.config.xau_strategy.enabled:
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if self._check_xau_oversold_bounce(report, dfs):
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report.final_signal = SignalStrength.STRONG_BUY
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report.final_score = 50.0
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report.final_confidence = 85.0
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report.signal_quality = "A+"
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report.action_recommendation = (
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"STRONG BUY — XAU oversold bounce "
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"(RSI<30 + M15/H1/H4 all above EMA200)"
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)
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report.bullish_reasons.insert(
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0,
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"XAU STRATEGY: M15 RSI oversold + triple-TF bullish trend confirmation",
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)
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report.trade_setup = self._generate_xau_trade_setup(report, dfs)
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# ── 7. Trade setup for actionable signals ──────────────────
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if report.signal_quality in ("A+", "A", "B", "C"):
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if report.trade_setup is None and report.signal_quality in ("A+", "A", "B", "C"):
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is_sell_direction = (
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report.final_signal in (SignalStrength.SELL, SignalStrength.STRONG_SELL)
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or (report.final_signal == SignalStrength.NEUTRAL and report.final_score < 0)
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@@ -359,6 +376,110 @@ class SignalAggregator:
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0/4 trades won even under best conditions (trending_down + MTF + ADX>=25 + RSI<=50)."""
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return False
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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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Conditions (all must be true):
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1. M15 RSI(14) < 30
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2. M15 price > M15 EMA(200)
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3. H1 price > H1 EMA(200)
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4. H4 price > H4 EMA(200)
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5. Current bar hour not in blocked list
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"""
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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 or not h4_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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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 None or m15_ema200 is None:
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return False
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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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return False
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h1_ema200 = h1_analysis.key_levels.get("ema_trend")
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if h1_ema200 is None or report.current_price <= h1_ema200:
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return False
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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 None or h4_ema200 is None:
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return False
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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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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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tp1 = price + cfg.tp_atr_multiplier * atr
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sl = price - cfg.sl_atr_multiplier * atr
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tp2 = price + cfg.tp_atr_multiplier * 2.0 * atr
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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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def _check_mtf_agreement(self, report: SignalReport) -> bool:
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signals = list(report.mtf_signals.values())
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if len(signals) < 2:
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