v2.2c: D1趋势总闸门 + 三层共振(1H/4H/D1) + 冷却期机制
This commit is contained in:
172
strategy.py
172
strategy.py
@ -1,14 +1,15 @@
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"""
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Structure Flow Strategy v2.2b
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=======================
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Structure Flow Strategy v2.2b — 1H S/R 实验版
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==============================================
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变更记录：
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v1.6 (2026-06-07): 最优基线 — +3659.63%, 190笔, 69.3% trailing胜率
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v2.0 (2026-06-08): B1 入场延迟确认 — 方向正确但降频严重
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v2.2b (2026-06-09): ===== 只移除 bullish_signal/bearish_signal =====
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在4H级别评估趋势强度：最近2个Swing Point的间距变化。
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如果趋势在扩张（HH/HL间距增大），允许入场；
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如果趋势在收缩（HH/HL间距缩小或震荡），过滤信号。
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目的：只在趋势明确时交易，避免震荡市反复止损。
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v2.2b (2026-06-09): 原版 — 4H级别S/R + 趋势强度
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v2.2b-1h-sr (2026-06-10): 实验版 — 将S/R从4H改为1H级别，趋势强度仍用4H
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改动：
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support_alive/resistance_alive 从4H级别 → 1H级别
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support/resistance 引用 从4H → 1H
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in_demand/in_supply 从4H → 1H
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趋势强度（strong_uptrend/downtrend）保持在4H
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"""
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from datetime import datetime
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@ -19,15 +20,7 @@ from freqtrade.strategy import IStrategy, IntParameter, informative
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from freqtrade.persistence import Trade
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class StructureFlowStrategyV22b(IStrategy):
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"""
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Structure Flow Strategy v2.2b — D1: 趋势强度过滤
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v2.2b改动（相对于v2.1）：
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在4H级别计算趋势强度：最近2个Swing High间距 + Swing Low间距的变化。
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只有趋势在扩张（或至少不收缩）时才允许入场。
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"""
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class StructureFlowStrategyV22c(IStrategy):
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can_short = True
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stoploss = -0.15
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use_custom_stoploss = True
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@ -41,12 +34,11 @@ class StructureFlowStrategyV22b(IStrategy):
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swing_lookback_d1 = IntParameter(8, 14, default=10, space="buy")
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swing_lookback_h4 = IntParameter(5, 10, default=8, space="buy")
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swing_lookback_1h = IntParameter(3, 7, default=5, space="buy") # 新增：1H swing参数
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pin_bar_wick_ratio = IntParameter(50, 70, default=60, space="buy")
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max_stop_dist = IntParameter(20, 50, default=50, space="buy")
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cooldown_bars = IntParameter(3, 12, default=6, space="buy")
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# v2.1 新增：趋势强度最小扩张比例（x/100 = 0%~50%）
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# 0 = 只要不收缩就行；越大要求趋势扩张越强
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trend_strength_min = IntParameter(-50, 20, default=-20, space="buy") # 扫描更宽范围
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trend_strength_min = IntParameter(-50, 20, default=-20, space="buy")
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# =====================
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# 工具：Swing Point 检测
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@ -189,7 +181,7 @@ class StructureFlowStrategyV22b(IStrategy):
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return dataframe
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# ================================================================
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# 信息时间框架 — 4H 中期结构
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# 信息时间框架 — 4H 趋势强度（原版保留）
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# ================================================================
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@informative("4h")
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@ -204,40 +196,8 @@ class StructureFlowStrategyV22b(IStrategy):
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dataframe["high"], dataframe["low"], dataframe["close"],
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sh, sl,
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)
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dataframe["trend_up"] = structure["trend_up"]
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dataframe["trend_down"] = structure["trend_down"]
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dataframe["support"] = structure["support"]
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dataframe["resistance"] = structure["resistance"]
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dataframe["in_demand"] = structure["in_demand"]
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dataframe["in_supply"] = structure["in_supply"]
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# ================================
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# v1.6 活支撑/阻力检查（保留）
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# ================================
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touched_support = (
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(dataframe["low"] <= dataframe["support"] * 1.005) &
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(dataframe["low"] >= dataframe["support"] * 0.995)
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)
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held_support = dataframe["close"] > dataframe["support"]
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support_tested_and_held = touched_support & held_support
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dataframe["support_alive"] = support_tested_and_held.rolling(3, min_periods=1).max() > 0
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touched_resistance = (
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(dataframe["high"] >= dataframe["resistance"] * 0.995) &
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(dataframe["high"] <= dataframe["resistance"] * 1.005)
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)
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held_resistance = dataframe["close"] < dataframe["resistance"]
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resistance_tested_and_held = touched_resistance & held_resistance
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dataframe["resistance_alive"] = resistance_tested_and_held.rolling(3, min_periods=1).max() > 0
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# ================================
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# v2.1 新增：趋势强度评估
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# ================================
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# 计算最近2个Swing Point之间的间距变化
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# 上升趋势：HH间距 + HL间距都在扩大 → 趋势强
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# 下降趋势：LH间距 + LL间距都在扩大 → 趋势强
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# 间距缩小 → 趋势减弱/震荡
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# 趋势强度计算（原版逻辑）
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sh_prices = []
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sl_prices = []
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trend_strength_up = np.full(len(dataframe), np.nan)
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@ -253,36 +213,29 @@ class StructureFlowStrategyV22b(IStrategy):
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if len(sl_prices) > 4:
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sl_prices.pop(0)
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# 上升趋势强度：HH[-1] vs HH[-2], HL[-1] vs HL[-2]
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if len(sh_prices) >= 2 and len(sl_prices) >= 2:
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# HH间距：最近两个Swing High的差值百分比
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hh_dist = (sh_prices[-1] - sh_prices[-2]) / sh_prices[-2] if sh_prices[-2] > 0 else 0
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# HL间距：最近两个Swing Low的差值百分比
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hl_dist = (sl_prices[-1] - sl_prices[-2]) / sl_prices[-2] if sl_prices[-2] > 0 else 0
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# 上升趋势强度 = HH间距 + HL间距（都正=扩张，一正一负=不确定，都负=收缩）
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trend_strength_up[i] = hh_dist + hl_dist
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# 下降趋势强度（取反：间距缩小是负值）
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trend_strength_down[i] = -(hh_dist + hl_dist)
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dataframe["trend_strength_up"] = pd.Series(trend_strength_up, index=dataframe.index)
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dataframe["trend_strength_down"] = pd.Series(trend_strength_down, index=dataframe.index)
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# 趋势强度是否足够（扩张中）
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min_strength = self.trend_strength_min.value / 100.0 # 0~0.30
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min_strength = self.trend_strength_min.value / 100.0
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dataframe["strong_uptrend"] = dataframe["trend_strength_up"] > min_strength
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dataframe["strong_downtrend"] = dataframe["trend_strength_down"] > min_strength
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return dataframe
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# ================================================================
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# 主时间框架 — 1H 指标
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# 主时间框架 — 1H 指标（含 1H S/R + 活支撑/阻力）
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# ================================================================
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def populate_indicators(
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self, dataframe: DataFrame, metadata: dict
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) -> DataFrame:
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"""1H 级别：K线形态（零指标）。"""
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# ── K线形态 ──
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bullish_pin, bearish_pin, bullish_engulf, bearish_engulf = (
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self._detect_candle_patterns(
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dataframe["open"],
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@ -299,12 +252,45 @@ class StructureFlowStrategyV22b(IStrategy):
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dataframe["bullish_signal"] = bullish_pin | bullish_engulf
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dataframe["bearish_signal"] = bearish_pin | bearish_engulf
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# NaN 安全处理
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# ── 1H级别 Swing Point + 结构（替代原4H S/R） ──
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sh_1h, sl_1h = self._detect_swing_points(
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dataframe["high"], dataframe["low"],
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self.swing_lookback_1h.value,
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)
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structure_1h = self._build_structure(
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dataframe["high"], dataframe["low"], dataframe["close"],
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sh_1h, sl_1h,
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)
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dataframe["trend_up_1h"] = structure_1h["trend_up"]
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dataframe["trend_down_1h"] = structure_1h["trend_down"]
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dataframe["support"] = structure_1h["support"]
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dataframe["resistance"] = structure_1h["resistance"]
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dataframe["in_demand"] = structure_1h["in_demand"]
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dataframe["in_supply"] = structure_1h["in_supply"]
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# ── 1H 活支撑/阻力检查 ──
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touched_support = (
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(dataframe["low"] <= dataframe["support"] * 1.005) &
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(dataframe["low"] >= dataframe["support"] * 0.995)
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)
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held_support = dataframe["close"] > dataframe["support"]
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support_tested_and_held = touched_support & held_support
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dataframe["support_alive"] = support_tested_and_held.rolling(3, min_periods=1).max() > 0
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touched_resistance = (
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(dataframe["high"] >= dataframe["resistance"] * 0.995) &
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(dataframe["high"] <= dataframe["resistance"] * 1.005)
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)
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held_resistance = dataframe["close"] < dataframe["resistance"]
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resistance_tested_and_held = touched_resistance & held_resistance
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dataframe["resistance_alive"] = resistance_tested_and_held.rolling(3, min_periods=1).max() > 0
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# ── NaN 安全处理 ──
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bool_cols = [
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"trend_up_1d", "trend_down_1d",
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"trend_up_4h", "trend_down_4h",
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"in_demand_4h", "in_supply_4h",
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"support_alive_4h", "resistance_alive_4h",
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"in_demand", "in_supply",
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"support_alive", "resistance_alive",
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"strong_uptrend_4h", "strong_downtrend_4h",
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"bullish_signal", "bearish_signal",
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]
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@ -319,21 +305,14 @@ class StructureFlowStrategyV22b(IStrategy):
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# =====================
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def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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"""
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入场逻辑（1H 时间框架）。
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v2.2b 改动：只移除 bullish_signal/bearish_signal（1H K线过滤）
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消融实验变体3：移除后收益 +19.4%，是三个可移除条件中收益提升最大的
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"""
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max_dist = self.max_stop_dist.value / 100.0
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cooldown = self.cooldown_bars.value
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# NaN 安全处理
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bool_cols = [
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"trend_up_1d", "trend_down_1d",
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"trend_up_4h", "trend_down_4h",
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"in_demand_4h", "in_supply_4h",
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"support_alive_4h", "resistance_alive_4h",
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"in_demand", "in_supply",
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"support_alive", "resistance_alive",
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"strong_uptrend_4h", "strong_downtrend_4h",
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"bullish_signal", "bearish_signal",
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]
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@ -341,34 +320,30 @@ class StructureFlowStrategyV22b(IStrategy):
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if col in dataframe.columns:
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dataframe[col] = dataframe[col].fillna(False)
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# ── 做多 ──
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long_stop_dist = (dataframe["open"] - dataframe["support_4h"]) / dataframe["open"]
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# ── 做多（使用1H S/R） ──
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long_stop_dist = (dataframe["open"] - dataframe["support"]) / dataframe["open"]
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long_base = (
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dataframe["trend_up_1d"]
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& dataframe["in_demand_4h"]
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# v2.2b: 已移除 bullish_signal（消融变体3）
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& dataframe["in_demand"]
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& (long_stop_dist <= max_dist)
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& (long_stop_dist > 0.003)
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& dataframe["support_alive_4h"]
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# v2.1: 趋势强度 — 4H上升趋势必须在扩张
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& dataframe["support_alive"]
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& dataframe["strong_uptrend_4h"]
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)
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long_recent = long_base.rolling(cooldown, min_periods=1).max().shift(1) == 0
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dataframe.loc[long_base & long_recent, "enter_long"] = 1
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# ── 做空 ──
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short_stop_dist = (dataframe["resistance_4h"] - dataframe["open"]) / dataframe["open"]
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# ── 做空（使用1H S/R） ──
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short_stop_dist = (dataframe["resistance"] - dataframe["open"]) / dataframe["open"]
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short_base = (
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dataframe["trend_down_1d"]
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& dataframe["in_supply_4h"]
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# v2.2b: 已移除 bearish_signal（消融变体3）
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& dataframe["in_supply"]
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& (short_stop_dist <= max_dist)
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& (short_stop_dist > 0.003)
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& dataframe["resistance_alive_4h"]
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# v2.1: 趋势强度 — 4H下降趋势必须在扩张
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& dataframe["resistance_alive"]
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& dataframe["strong_downtrend_4h"]
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)
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@ -382,7 +357,6 @@ class StructureFlowStrategyV22b(IStrategy):
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# =====================
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def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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"""出场逻辑 — 由结构反转触发。"""
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exit_long = ~dataframe["trend_up_1d"].fillna(True)
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dataframe.loc[exit_long, "exit_long"] = 1
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@ -392,7 +366,7 @@ class StructureFlowStrategyV22b(IStrategy):
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return dataframe
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# =====================
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# 动态止损 — 纯价格结构（基于Swing Point）
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# 动态止损（基于1H S/R）
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# =====================
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def custom_stoploss(
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@ -405,9 +379,6 @@ class StructureFlowStrategyV22b(IStrategy):
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after_fill: bool,
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**kwargs,
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) -> float:
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"""
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止损逻辑：完全基于价格结构，零指标（与v1.6相同）。
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"""
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dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
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if dataframe is None or len(dataframe) == 0:
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return -0.02 if not trade.is_short else 0.02
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@ -415,14 +386,14 @@ class StructureFlowStrategyV22b(IStrategy):
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last = dataframe.iloc[-1]
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if not trade.is_short:
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support = last.get("support_4h", np.nan)
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support = last.get("support", np.nan)
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if pd.isna(support) or support <= 0:
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return -0.02
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sl_price = support * 0.999
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sl_ratio = (sl_price / current_rate) - 1.0
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return max(sl_ratio, -0.15)
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else:
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resistance = last.get("resistance_4h", np.nan)
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resistance = last.get("resistance", np.nan)
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if pd.isna(resistance) or resistance <= 0:
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return 0.02
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sl_price = resistance * 1.001
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@ -437,8 +408,8 @@ class StructureFlowStrategyV22b(IStrategy):
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def plot_config() -> dict:
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return {
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"main_plot": {
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"support_4h": {"color": "green", "type": "line"},
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"resistance_4h": {"color": "red", "type": "line"},
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"support": {"color": "green", "type": "line"},
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"resistance": {"color": "red", "type": "line"},
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},
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"subplots": {
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"signals": {
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@ -446,10 +417,11 @@ class StructureFlowStrategyV22b(IStrategy):
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"bearish_pinbar": {"color": "red", "type": "scatter"},
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},
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"filters": {
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"support_alive_4h": {"color": "green", "type": "line"},
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"resistance_alive_4h": {"color": "red", "type": "line"},
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"support_alive": {"color": "green", "type": "line"},
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"resistance_alive": {"color": "red", "type": "line"},
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"strong_uptrend_4h": {"color": "blue", "type": "line"},
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"strong_downtrend_4h": {"color": "orange", "type": "line"},
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},
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},
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}
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