结合rsi回调止损

freqtrade/templates/OKXRegressionStrategy.py

@@ -285,6 +285,19 @@ class OKXRegressionStrategy(IStrategy):
         if dataframe is None:
             dataframe = DataFrame()
         dataframe['ATR_{}'.format(self.atr_period.value)] = ta.ATR(dataframe['high'], dataframe['low'], dataframe['close'], timeperiod=self.atr_period.value)
+        # 添加 RSI 和布林带指标
+        dataframe['rsi'] = ta.RSI(dataframe['close'], timeperiod=14)
+        upper, middle, lower = ta.BBANDS(dataframe['close'], timeperiod=20, nbdevup=2, nbdevdn=2)
+        dataframe['bb_upper'] = upper
+        dataframe['bb_middle'] = middle
+        dataframe['bb_lower'] = lower
+
+        # 添加高时间框架数据（例如 1h）
+        if self.config['timeframe'] != '1h':
+            dataframe_1h = self.dp.get_analyzed_dataframe(metadata['pair'], '1h')[0]
+            dataframe['trend_1h'] = dataframe_1h['close'].rolling(window=20).mean()
+        else:
+            dataframe['trend_1h'] = dataframe['close'].rolling(window=20).mean()
         return dataframe
 
 
@@ -560,3 +573,39 @@ class OKXRegressionStrategy(IStrategy):
         except Exception as e:
             logger.error(f"FreqAI fit 失败：{str(e)}")
             raise
+    def _callback_stop_loss(self, dataframe: DataFrame, metadata: dict, callback_percent: float = 0.015) -> DataFrame:
+        """
+        回调止损逻辑：当价格从近期高点回撤超过指定百分比，
+        并结合 RSI 或布林带信号，同时考虑高时间框架趋势。
+        """
+
+        # 计算滚动最高价（过去 N 根K线内的最高点）
+        rolling_high_period = 20
+        dataframe['rolling_high'] = dataframe['close'].rolling(window=rolling_high_period).max()
+
+        # 计算当前价格相对于最近高点的回撤比例
+        dataframe['callback_ratio'] = (dataframe['close'] - dataframe['rolling_high']) / dataframe['rolling_high']
+
+        # 获取 RSI 和布林带信息
+        rsi_overbought = 70
+        dataframe['in_overbought'] = dataframe['rsi'] > rsi_overbought
+        dataframe['below_bb_upper'] = dataframe['close'] < dataframe['bb_upper']
+
+        # 获取高时间框架趋势（1小时均线）
+        dataframe['trend_up'] = dataframe['close'] > dataframe['trend_1h']
+        dataframe['trend_down'] = dataframe['close'] < dataframe['trend_1h']
+
+        # 回调止损条件：
+        # 1. 当前价格回撤超过设定的百分比
+        # 2. RSI 处于超买状态 OR 价格跌破布林带上轨
+        # 3. 当前处于下降趋势（高时间框架确认）
+        callback_condition = (
+            (dataframe['callback_ratio'] <= -callback_percent) &
+            ((dataframe['in_overbought'] | (~dataframe['below_bb_upper']))) &
+            (dataframe['trend_down'])
+        )
+
+        # 应用回调止损逻辑
+        dataframe.loc[callback_condition, 'exit_long'] = 1
+
+        return dataframe