添加新的策略

2026-03-06 22:08:24 +08:00
parent d8f2269a49
commit d2107db6c0
19 changed files with 2712 additions and 19 deletions
@@ -0,0 +1,119 @@
+"""
+SOL5mStrategyV6 - 趋势跟随策略 V6（基于V5改进）
+
+核心改进：
+    - 去掉trend_reversal退出（V5中54笔全亏 -611 USDT）
+    - 完全依赖 ROI + trailing_stop + stoploss 管理退出
+    - 更激进的trailing：1.5%盈利后激活，0.6%回撤
+    - 保持V5的入场逻辑（EMA排列 + 回调入场 + RSI + MACD + ADX）
+"""
+
+from datetime import datetime
+from typing import Optional
+
+import talib.abstract as ta
+from pandas import DataFrame
+
+from freqtrade.persistence import Trade
+from freqtrade.strategy import IStrategy
+
+
+class SOL5mStrategyV6(IStrategy):
+    INTERFACE_VERSION: int = 3
+
+    timeframe = "15m"
+    can_short = True
+    startup_candle_count: int = 200
+
+    # 止损
+    stoploss = -0.025
+    use_custom_stoploss = False
+
+    # 更激进的trailing stop
+    trailing_stop = True
+    trailing_stop_positive = 0.006   # 0.6% 回撤止盈
+    trailing_stop_positive_offset = 0.015  # 1.5% 盈利后激活
+    trailing_only_offset_is_reached = True
+
+    # ROI
+    minimal_roi = {
+        "0": 0.04,       # 4%直接止盈
+        "60": 0.03,      # 1小时后 3%
+        "180": 0.02,     # 3小时后 2%
+        "360": 0.01,     # 6小时后 1%
+        "720": 0.005,    # 12小时后 0.5%
+        "1440": 0,       # 24小时后保本
+    }
+
+    order_types = {
+        "entry": "market",
+        "exit": "market",
+        "stoploss": "market",
+        "stoploss_on_exchange": False,
+    }
+
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        # EMA趋势
+        dataframe["ema20"] = ta.EMA(dataframe, timeperiod=20)
+        dataframe["ema50"] = ta.EMA(dataframe, timeperiod=50)
+        dataframe["ema100"] = ta.EMA(dataframe, timeperiod=100)
+
+        # RSI
+        dataframe["rsi"] = ta.RSI(dataframe, timeperiod=14)
+
+        # MACD
+        macd = ta.MACD(dataframe, fastperiod=12, slowperiod=26, signalperiod=9)
+        dataframe["macd"] = macd["macd"]
+        dataframe["macdsignal"] = macd["macdsignal"]
+        dataframe["macdhist"] = macd["macdhist"]
+
+        # ADX (趋势强度)
+        dataframe["adx"] = ta.ADX(dataframe, timeperiod=14)
+
+        return dataframe
+
+    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        # 做多条件（与V5相同）
+        dataframe.loc[
+            (dataframe["ema20"] > dataframe["ema50"])
+            & (dataframe["ema50"] > dataframe["ema100"])
+            & (dataframe["close"] <= dataframe["ema20"] * 1.005)
+            & (dataframe["close"] >= dataframe["ema50"])
+            & (dataframe["rsi"] > 40)
+            & (dataframe["rsi"] < 65)
+            & (dataframe["macdhist"] > 0)
+            & (dataframe["adx"] > 20),
+            ["enter_long", "enter_tag"],
+        ] = (1, "trend_pullback_long")
+
+        # 做空条件（与V5相同）
+        dataframe.loc[
+            (dataframe["ema20"] < dataframe["ema50"])
+            & (dataframe["ema50"] < dataframe["ema100"])
+            & (dataframe["close"] >= dataframe["ema20"] * 0.995)
+            & (dataframe["close"] <= dataframe["ema50"])
+            & (dataframe["rsi"] < 60)
+            & (dataframe["rsi"] > 35)
+            & (dataframe["macdhist"] < 0)
+            & (dataframe["adx"] > 20),
+            ["enter_short", "enter_tag"],
+        ] = (1, "trend_pullback_short")
+
+        return dataframe
+
+    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        # 不使用信号退出，完全依赖 ROI + trailing + stoploss
+        return dataframe
+
+    def leverage(
+        self,
+        pair: str,
+        current_time: datetime,
+        current_rate: float,
+        proposed_leverage: float,
+        max_leverage: float,
+        entry_tag: Optional[str],
+        side: str,
+        **kwargs,
+    ) -> float:
+        return 1.0