theforce-noai-test 里实现动态roi

freqtrade/templates/freqaiprimer.py

@@ -1,8 +1,11 @@
 import logging
 import numpy as np
+import datetime
 from functools import reduce
+from freqtrade.persistence import Trade
 import talib.abstract as ta
 from pandas import DataFrame
+from typing import Dict
 from technical import qtpylib
 from freqtrade.strategy import IStrategy
 
@@ -134,7 +137,11 @@ class FreqaiPrimer(IStrategy):
         # FreqAI 提供的预测列
         if "&-trend" in dataframe.columns:
             dataframe["in_uptrend"] = dataframe["&-trend"] > 0.5
-
+        # 将 roi_target 存入 dataframe，供后续使用
+        if "&-roi_target" in dataframe.columns:
+            dataframe["&-roi_target"] = dataframe["&-roi_target"].ffill().fillna(0.01)
+        else:
+            dataframe["&-roi_target"] = 0.01
         return dataframe
 
     def populate_entry_trend(self, df: DataFrame, metadata: dict) -> DataFrame:
@@ -176,3 +183,43 @@ class FreqaiPrimer(IStrategy):
 
         df.loc[reduce(lambda x, y: x & y, conditions), 'exit_long'] = 1
         return df
+    def adjust_trade_position(self, trade: Trade, current_time: datetime,
+                            current_rate: float, current_profit: float,
+                            min_roi: Dict[float, float], max_profit: float):
+        """
+        动态调整当前交易的止盈目标。
+        """
+
+        # 获取当前币种的 dataframe
+        pair = trade.pair
+        dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
+        last_candle = dataframe.iloc[-1]
+
+        # 获取预测的 ROI 目标
+        roi_target = last_candle.get("&-roi_target", 0.01)
+
+        # 根据预测值生成新的 ROI 表
+        if roi_target > 0.05:
+            new_minimal_roi = {
+                "0": roi_target * 1.0,
+                "10": roi_target * 0.8,
+                "30": roi_target * 0.5,
+                "60": roi_target * 0.2,
+                "120": 0.01
+            }
+        elif 0.02 <= roi_target <= 0.05:
+            new_minimal_roi = {
+                "0": roi_target * 1.0,
+                "20": roi_target * 0.7,
+                "60": roi_target * 0.3,
+                "120": 0.01
+            }
+        else:
+            new_minimal_roi = {
+                "0": max(0.01, roi_target),
+                "60": 0.01,
+                "180": 0.01
+            }
+
+        # 返回新的 minimal_roi
+        return new_minimal_roi