kroutony
32aa6e40cd
V3 backtest: add context parameter to signal_generator with three new filters: - BTC trend filter: skip altcoin BUYs when BTC 1h EMA9<EMA21 + ADX>20 - Buy pressure (OHLCV proxy): penalize BUY score when close near low, boost SELL - Funding sentiment (BTC perp basis): penalize BUY on overleveraged longs, boost SELL Results: return -19.07% → -13.48%, max DD -27.19% → -18.25%, BUYs 385 → 189. Added --no-context CLI flag for A/B comparison. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
263 lines
10 KiB
Python
263 lines
10 KiB
Python
"""Rule-based signal generator replicating the LLM trading strategy.
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Relaxed version: mirrors actual LLM behavior where volume/OBV are bonus factors
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rather than hard filters, deep oversold alone can trigger entry, and bearish
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trend reversal triggers protective sells on existing positions.
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"""
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import pandas as pd
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def _near_level(price: float, level: float, tolerance: float = 0.008) -> bool:
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"""Check if price is within tolerance % of a level."""
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if level <= 0:
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return False
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return abs(price - level) / level <= tolerance
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def generate_signal(
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symbol: str,
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ind_curr: pd.Series,
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ind_prev: pd.Series,
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htf_last: pd.Series | None,
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pivots: dict | None,
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has_position: bool = False,
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context: dict | None = None,
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) -> dict:
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"""Generate a trading signal based on codified strategy rules.
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Matches real LLM behavior: flexible confirmation counting with bonus scoring
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rather than strict AND filters.
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"""
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hold = {"symbol": symbol, "action": "HOLD", "confidence": 0.0, "reason": "", "suggested_amount_pct": 0.0}
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close = ind_curr.get("close", 0)
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if close <= 0 or pd.isna(ind_curr.get("rsi")):
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return {**hold, "reason": "insufficient data"}
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# --- Extract 5m indicators ---
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rsi = ind_curr.get("rsi", 50)
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stoch_k = ind_curr.get("stoch_rsi_k", 0.5)
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stoch_d = ind_curr.get("stoch_rsi_d", 0.5)
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macd = ind_curr.get("macd", 0)
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macd_signal = ind_curr.get("macd_signal", 0)
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macd_hist = ind_curr.get("macd_hist", 0)
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prev_macd = ind_prev.get("macd", 0)
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prev_macd_signal = ind_prev.get("macd_signal", 0)
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bb_lower = ind_curr.get("bb_lower", 0)
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bb_upper = ind_curr.get("bb_upper", 0)
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ema9 = ind_curr.get("ema9", 0)
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ema21 = ind_curr.get("ema21", 0)
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adx = ind_curr.get("adx", 0)
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volume = ind_curr.get("volume", 0)
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vol_ma20 = ind_curr.get("vol_ma20", 0)
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obv_slope = ind_curr.get("obv_slope", 0)
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cmf = ind_curr.get("cmf", 0)
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# --- VWAP filter ---
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vwap = ind_curr.get("vwap", 0)
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# --- 1h trend context ---
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htf_bullish = False
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htf_adx_ok = False
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htf_strong = False
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htf_bearish_strong = False
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# Market regime: trending (ADX≥25), weak_trend (15-25), choppy (<15)
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market_regime = "choppy"
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if htf_last is not None and pd.notna(htf_last.get("ema9")):
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htf_bullish = htf_last["ema9"] > htf_last["ema21"]
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htf_adx = htf_last.get("adx", 0)
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if pd.notna(htf_adx):
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htf_adx_ok = htf_adx >= 20
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htf_strong = htf_adx > 25
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htf_bearish_strong = (not htf_bullish) and htf_adx > 25
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if htf_adx >= 25:
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market_regime = "trending"
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elif htf_adx >= 15:
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market_regime = "weak_trend"
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# --- Pivot levels ---
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s1 = pivots.get("s1", 0) if pivots else 0
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s2 = pivots.get("s2", 0) if pivots else 0
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r1 = pivots.get("r1", 0) if pivots else 0
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r2 = pivots.get("r2", 0) if pivots else 0
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# --- Bonus scoring (not hard filters) ---
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volume_bonus = 0.05 if (vol_ma20 > 0 and volume > vol_ma20) else 0
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obv_buy_bonus = 0.05 if obv_slope > 0 else 0
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obv_sell_bonus = 0.05 if obv_slope < 0 else 0
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# --- Extract context data ---
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ctx = context or {}
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btc_trend = ctx.get("btc_trend")
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buy_pressure = ctx.get("buy_pressure", 0.5)
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funding = ctx.get("funding_sentiment")
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# ========== BUY SIGNALS ==========
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# Regime filter: choppy market → no buys at all
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if market_regime == "choppy":
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pass # skip all buy logic
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# BTC trend filter: skip altcoin buys during confirmed BTC bearish
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elif (btc_trend and btc_trend.get("bearish_confirmed")
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and symbol != "tBTCUST"):
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pass # skip buy — BTC bearish confirmed
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# VWAP filter: don't buy above VWAP (buying above fair value)
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elif vwap > 0 and close > vwap:
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pass # skip buy
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# Require: 1h bullish (core filter)
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elif htf_bullish:
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buy_confirms = []
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reasons = []
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# Signal 1: Oversold bounce (tightened: RSI<30 alone no longer triggers)
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if stoch_k < 0.2 and rsi < 40:
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if stoch_k > stoch_d:
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buy_confirms.append(1.0)
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reasons.append("超賣反彈(StochRSI K上穿D+RSI)")
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else:
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buy_confirms.append(0.7)
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reasons.append("超賣(StochRSI+RSI)")
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# Signal 2: Mean reversion (BB touch) — allowed in weak_trend regime too
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if bb_lower > 0 and close <= bb_lower * 1.005:
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if rsi < 40 and cmf > 0:
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buy_confirms.append(1.0)
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reasons.append("均值回歸(BB+RSI+CMF)")
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# Signal 3: Trend start (MACD golden cross) — only in trending regime
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macd_cross_up = (pd.notna(prev_macd) and pd.notna(prev_macd_signal)
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and prev_macd <= prev_macd_signal and macd > macd_signal)
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prev_macd_hist = ind_prev.get("macd_hist", 0)
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if macd_cross_up and ema9 > ema21 and market_regime == "trending":
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# MACD histogram direction confirmation: require histogram rising
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if pd.notna(prev_macd_hist) and macd_hist > prev_macd_hist:
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buy_confirms.append(1.0 if (pd.notna(adx) and adx > 20) else 0.8)
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reasons.append("趨勢啟動(MACD金叉+hist↑+EMA)")
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else:
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buy_confirms.append(0.6 if (pd.notna(adx) and adx > 20) else 0.4)
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reasons.append("趨勢啟動(MACD金叉+EMA)")
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# Signal 4: Support bounce — only in trending regime
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if market_regime == "trending":
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near_support = _near_level(close, s1) or _near_level(close, s2)
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if near_support and rsi < 45:
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buy_confirms.append(0.7 if obv_slope > 0 else 0.5)
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reasons.append("支撐反彈(Pivot+RSI)")
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# In weak_trend, only allow mean reversion (Signal 2)
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if market_regime == "weak_trend":
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buy_confirms = [c for c, r in zip(buy_confirms, reasons) if "均值回歸" in r]
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reasons = [r for r in reasons if "均值回歸" in r]
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# Score: sum of weighted confirmations
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total_score = sum(buy_confirms)
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n_confirms = len(buy_confirms)
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# Buy pressure filter (OHLCV proxy for order book imbalance)
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if buy_pressure < 0.3:
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total_score *= 0.5 # heavy sell pressure — halve score
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elif buy_pressure < 0.4:
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total_score *= 0.8 # moderate sell pressure
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# Funding sentiment filter (overleveraged longs → pullback risk)
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if funding and funding.get("signal") == "overleveraged_long":
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total_score *= 0.6
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if total_score >= 1.5 and htf_adx_ok: # require stronger confirmation + trending
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base_conf = 0.55
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base_conf += 0.10 if htf_adx_ok else 0
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base_conf += 0.05 if htf_strong else 0
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base_conf += volume_bonus
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base_conf += obv_buy_bonus
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if n_confirms >= 3:
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base_conf += 0.10
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conf = min(0.90, max(0.50, base_conf))
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return {
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"symbol": symbol,
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"action": "BUY",
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"confidence": round(conf, 2),
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"reason": " + ".join(reasons),
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"suggested_amount_pct": min(0.20, max(0.05, conf * 0.20)),
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}
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# ========== SELL SIGNALS ==========
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sell_confirms = []
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sell_reasons = []
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# Signal 1: Overbought reversal (relaxed: RSI>65 or StochRSI>0.8)
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if stoch_k > 0.8 and stoch_k < stoch_d:
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if rsi > 70 and macd_hist < 0:
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sell_confirms.append(1.0)
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sell_reasons.append("超買反轉(StochRSI+RSI+MACD)")
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elif rsi > 65:
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sell_confirms.append(0.7)
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sell_reasons.append("超買(StochRSI+RSI)")
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# Signal 2: Resistance rejection
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near_resistance = _near_level(close, r1) or _near_level(close, r2)
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if near_resistance and cmf < 0:
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sell_confirms.append(0.7 if obv_slope < 0 else 0.5)
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sell_reasons.append("阻力拒絕(Pivot+CMF)")
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# Signal 3: Trend reversal (MACD death cross + EMA bearish)
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macd_cross_down = (pd.notna(prev_macd) and pd.notna(prev_macd_signal)
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and prev_macd >= prev_macd_signal and macd < macd_signal)
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if macd_cross_down and ema9 < ema21:
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strength = 1.0 if (not htf_bullish) else 0.6
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sell_confirms.append(strength)
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sell_reasons.append("趨勢反轉(MACD死叉+EMA)")
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# Signal 4: 1h bearish strong trend + 5m confirming (protective sell)
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if htf_bearish_strong and ema9 < ema21 and rsi < 40 and obv_slope < 0:
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sell_confirms.append(0.8)
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sell_reasons.append("多TF空頭(1h強空+5m空)")
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# Signal 5: OBV massive outflow + CMF bearish (volume divergence, reduced weight)
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if obv_slope < 0 and cmf < -0.1 and ema9 < ema21:
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sell_confirms.append(0.3)
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sell_reasons.append("量價背離(OBV流出+CMF賣壓)")
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# VWAP sell bonus: price significantly above VWAP
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if vwap > 0 and close > vwap * 1.01:
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sell_confirms.append(0.3)
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sell_reasons.append("VWAP溢價")
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# Sell pressure from OHLCV proxy
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if buy_pressure < 0.3:
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sell_confirms.append(0.3)
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sell_reasons.append("賣壓(OHLCV)")
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# Funding: overleveraged longs with high basis → liquidation risk
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if funding and funding.get("signal") == "overleveraged_long":
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basis_pct = funding.get("basis_pct", 0)
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if basis_pct > 0.0008: # > 0.08%
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sell_confirms.append(0.4)
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sell_reasons.append("資金費率過高")
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total_sell = sum(sell_confirms)
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if total_sell >= 1.2 and has_position:
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base_conf = 0.55
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if not htf_bullish:
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base_conf += 0.10
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if htf_bearish_strong:
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base_conf += 0.05
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base_conf += obv_sell_bonus
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base_conf += volume_bonus
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if len(sell_confirms) >= 3:
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base_conf += 0.10
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# If 1h still bullish, penalize
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if htf_bullish:
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base_conf -= 0.15
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conf = min(0.90, max(0.40, base_conf))
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return {
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"symbol": symbol,
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"action": "SELL",
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"confidence": round(conf, 2),
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"reason": " + ".join(sell_reasons),
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"suggested_amount_pct": 1.0,
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}
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return {**hold, "reason": "確認不足"}
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