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v2.1: 趋势强度过滤 + 供需区评分精简

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Beast Trader
2026-06-08 16:37:00 +08:00
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strategy.py
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@ -1,13 +1,14 @@
"""
Structure Flow Strategy v2.0
Structure Flow Strategy v2.1
=======================
变更记录：
v1.6 (2026-06-07): 最优基线 — +3659.63%, 190笔, 69.3% trailing胜率
v2.0 (2026-06-08): ===== B1: 入场延迟一根1H bar确认 =====
信号触发后，不立即入场，等下一根1H bar收盘。
如果收盘价仍在S/R附近（支撑上方1.5%以内 / 阻力下方1.5%以内），
确认入场；否则放弃本次信号。
目的：过滤假突破，减少被噪音震出的止损交易。
v2.0 (2026-06-08): B1 入场延迟确认 — 方向正确但降频严重
v2.1 (2026-06-08): ===== D1: 趋势强度过滤 =====
在4H级别评估趋势强度：最近2个Swing Point的间距变化。
如果趋势在扩张（HH/HL间距增大），允许入场；
如果趋势在收缩（HH/HL间距缩小或震荡），过滤信号。
目的：只在趋势明确时交易，避免震荡市反复止损。
"""
from datetime import datetime
@ -18,14 +19,13 @@ from freqtrade.strategy import IStrategy, IntParameter, informative
from freqtrade.persistence import Trade
class StructureFlowStrategyV20(IStrategy):
class StructureFlowStrategyV21(IStrategy):
"""
Structure Flow Strategy v2.0 — B1: 入场延迟确认
Structure Flow Strategy v2.1 — D1: 趋势强度过滤
v2.0改动（相对于v1.6）：
1. 入场延迟1根bar：信号触发后，等下一根bar收盘确认
2. 确认条件：收盘价仍在S/R附近（做多在support上方1.5%内，做空在resistance下方1.5%内）
3. 保留v1.6所有逻辑：冷却期、活支撑/阻力、D1趋势过滤
v2.1改动（相对于v1.6）：
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。
只有趋势在扩张（或至少不收缩）时才允许入场。
"""
can_short = True
@ -44,8 +44,9 @@ class StructureFlowStrategyV20(IStrategy):
pin_bar_wick_ratio = IntParameter(50, 70, default=60, space="buy")
max_stop_dist = IntParameter(20, 50, default=50, space="buy")
cooldown_bars = IntParameter(3, 12, default=6, space="buy")
# v2.0 新增：入场确认阈值 — close必须在S/R附近多少%以内才算确认
entry_confirm_pct = IntParameter(10, 50, default=50, space="buy") # x/1000 = 1.0%~5.0%, default 5.0%
# v2.1 新增：趋势强度最小扩张比例（x/100 = 0%~50%）
# 0 = 只要不收缩就行；越大要求趋势扩张越强
trend_strength_min = IntParameter(-50, 20, default=-20, space="buy") # -20=允许SP轻微收缩, 最佳值
# =====================
# 工具：Swing Point 检测
@ -229,6 +230,49 @@ class StructureFlowStrategyV20(IStrategy):
resistance_tested_and_held = touched_resistance & held_resistance
dataframe["resistance_alive"] = resistance_tested_and_held.rolling(3, min_periods=1).max() > 0
# ================================
# v2.1 新增：趋势强度评估
# ================================
# 计算最近2个Swing Point之间的间距变化
# 上升趋势：HH间距 + HL间距都在扩大 → 趋势强
# 下降趋势：LH间距 + LL间距都在扩大 → 趋势强
# 间距缩小 → 趋势减弱/震荡
sh_prices = []
sl_prices = []
trend_strength_up = np.full(len(dataframe), np.nan)
trend_strength_down = np.full(len(dataframe), np.nan)
for i in range(len(dataframe)):
if pd.notna(sh.iloc[i]):
sh_prices.append(sh.iloc[i])
if len(sh_prices) > 4:
sh_prices.pop(0)
if pd.notna(sl.iloc[i]):
sl_prices.append(sl.iloc[i])
if len(sl_prices) > 4:
sl_prices.pop(0)
# 上升趋势强度：HH[-1] vs HH[-2], HL[-1] vs HL[-2]
if len(sh_prices) >= 2 and len(sl_prices) >= 2:
# HH间距：最近两个Swing High的差值百分比
hh_dist = (sh_prices[-1] - sh_prices[-2]) / sh_prices[-2] if sh_prices[-2] > 0 else 0
# HL间距：最近两个Swing Low的差值百分比
hl_dist = (sl_prices[-1] - sl_prices[-2]) / sl_prices[-2] if sl_prices[-2] > 0 else 0
# 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）
trend_strength_up[i] = hh_dist + hl_dist
# 下降趋势强度（取反：间距缩小是负值）
trend_strength_down[i] = -(hh_dist + hl_dist)
dataframe["trend_strength_up"] = pd.Series(trend_strength_up, index=dataframe.index)
dataframe["trend_strength_down"] = pd.Series(trend_strength_down, index=dataframe.index)
# 趋势强度是否足够（扩张中）
min_strength = self.trend_strength_min.value / 100.0 # 0~0.30
dataframe["strong_uptrend"] = dataframe["trend_strength_up"] > min_strength
dataframe["strong_downtrend"] = dataframe["trend_strength_down"] > min_strength
return dataframe
# ================================================================
@ -261,6 +305,7 @@ class StructureFlowStrategyV20(IStrategy):
"trend_up_4h", "trend_down_4h",
"in_demand_4h", "in_supply_4h",
"support_alive_4h", "resistance_alive_4h",
"strong_uptrend_4h", "strong_downtrend_4h",
"bullish_signal", "bearish_signal",
]
for col in bool_cols:
@ -270,29 +315,19 @@ class StructureFlowStrategyV20(IStrategy):
return dataframe
# =====================
# 入场信号 — v2.0 延迟确认
# 入场信号
# =====================
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
入场逻辑（1H 时间框架）。
v2.0 核心改动：B1 — 入场延迟一根1H bar确认
做多条件:
1. D1 上升结构（trend_up_1d）
2. 4H 需求区域（in_demand_4h）
3. 1H 看涨 K 线形态（bullish_signal）
4. 止损距离 ≤ max_stop_dist%
5. 支撑位是"活"的（support_alive_4h）
6. 6h内没有过同方向入场信号（冷却期）
7. [v2.0 NEW] 上一根bar触发了信号，当前bar收盘确认：
做多：close 仍在 support_4h 上方 entry_confirm_pct% 以内
做空：close 仍在 resistance_4h 下方 entry_confirm_pct% 以内
v2.1 核心改动：D1 — 趋势强度过滤
做多额外条件：4H上升趋势在扩张（strong_uptrend_4h）
做空额外条件：4H下降趋势在扩张（strong_downtrend_4h）
"""
max_dist = self.max_stop_dist.value / 100.0
cooldown = self.cooldown_bars.value
confirm_pct = self.entry_confirm_pct.value / 1000.0 # 1.0%~3.0%
# NaN 安全处理
bool_cols = [
@ -300,17 +335,14 @@ class StructureFlowStrategyV20(IStrategy):
"trend_up_4h", "trend_down_4h",
"in_demand_4h", "in_supply_4h",
"support_alive_4h", "resistance_alive_4h",
"strong_uptrend_4h", "strong_downtrend_4h",
"bullish_signal", "bearish_signal",
]
for col in bool_cols:
if col in dataframe.columns:
dataframe[col] = dataframe[col].fillna(False)
# =====================
# 原始v1.6入场条件（不变）
# =====================
# ── 做多原始条件 ──
# ── 做多 ──
long_stop_dist = (dataframe["open"] - dataframe["support_4h"]) / dataframe["open"]
long_base = (
@ -320,13 +352,14 @@ class StructureFlowStrategyV20(IStrategy):
& (long_stop_dist <= max_dist)
& (long_stop_dist > 0.003)
& dataframe["support_alive_4h"]
# v2.1: 趋势强度 — 4H上升趋势必须在扩张
& dataframe["strong_uptrend_4h"]
)
# 冷却期
long_recent = long_base.rolling(cooldown, min_periods=1).max().shift(1) == 0
long_signal = long_base & long_recent
dataframe.loc[long_base & long_recent, "enter_long"] = 1
# ── 做空原始条件 ──
# ── 做空 ──
short_stop_dist = (dataframe["resistance_4h"] - dataframe["open"]) / dataframe["open"]
short_base = (
@ -336,34 +369,12 @@ class StructureFlowStrategyV20(IStrategy):
& (short_stop_dist <= max_dist)
& (short_stop_dist > 0.003)
& dataframe["resistance_alive_4h"]
# v2.1: 趋势强度 — 4H下降趋势必须在扩张
& dataframe["strong_downtrend_4h"]
)
short_recent = short_base.rolling(cooldown, min_periods=1).max().shift(1) == 0
short_signal = short_base & short_recent
# =====================
# v2.0: B1 — 入场延迟一根bar确认
# =====================
# 上一根bar的信号（shift(1)）
prev_long_signal = long_signal.shift(1).fillna(False)
prev_short_signal = short_signal.shift(1).fillna(False)
# 确认条件：当前bar的close仍在S/R附近
# 做多：close在support上方确认区间内（support * 1.0 ~ support * (1+confirm_pct)）
long_confirm = (
(dataframe["close"] >= dataframe["support_4h"]) &
(dataframe["close"] <= dataframe["support_4h"] * (1 + confirm_pct))
)
# 做空：close在resistance下方确认区间内（resistance * (1-confirm_pct) ~ resistance * 1.0）
short_confirm = (
(dataframe["close"] <= dataframe["resistance_4h"]) &
(dataframe["close"] >= dataframe["resistance_4h"] * (1 - confirm_pct))
)
# 最终入场：上一根bar有信号 + 当前bar确认
dataframe.loc[prev_long_signal & long_confirm, "enter_long"] = 1
dataframe.loc[prev_short_signal & short_confirm, "enter_short"] = 1
dataframe.loc[short_base & short_recent, "enter_short"] = 1
return dataframe
@ -397,13 +408,6 @@ class StructureFlowStrategyV20(IStrategy):
) -> float:
"""
止损逻辑：完全基于价格结构，零指标（与v1.6相同）。
止损位：
做多 → support_4h - 0.1%缓冲
做空 → resistance_4h + 0.1%缓冲
support_4h / resistance_4h 随新Swing Point自动更新，
天然形成追踪止损效果。
"""
dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
if dataframe is None or len(dataframe) == 0:
@ -445,6 +449,8 @@ class StructureFlowStrategyV20(IStrategy):
"filters": {
"support_alive_4h": {"color": "green", "type": "line"},
"resistance_alive_4h": {"color": "red", "type": "line"},
"strong_uptrend_4h": {"color": "blue", "type": "line"},
"strong_downtrend_4h": {"color": "orange", "type": "line"},
},
},
}