全新的策略

freqtrade/templates/freqaiprimer.py

@@ -4,7 +4,6 @@ warnings.filterwarnings("ignore", category=UserWarning, module="pandas_ta")
 from freqtrade.strategy import IStrategy
 from pandas import DataFrame
 import pandas_ta as ta
-from freqtrade.exchange import timeframe_to_minutes
 
 class FreqaiPrimer(IStrategy):
     # 策略参数
@@ -16,7 +15,7 @@ class FreqaiPrimer(IStrategy):
     }
     
     stoploss = -0.015  # 初始止损 -1.5%
-    trailing_stop = True  # 启用追踪止损
+    trailing_stop = True
     trailing_stop_positive = 0.008  # 价格上涨 0.8% 后开始追踪
     trailing_stop_positive_offset = 0.01  # 追踪止损偏移量 1%
     
@@ -24,14 +23,13 @@ class FreqaiPrimer(IStrategy):
     can_short = False  # 禁用做空
 
     # 自定义指标参数
-    bb_length = 20  # 布林带周期
-    bb_std = 2.0    # 布林带标准差
-    rsi_length = 14 # RSI 周期
-    rsi_overbought = 70  # RSI 超买阈值
-    rsi_oversold = 30    # RSI 超卖阈值
+    bb_length = 20
+    bb_std = 2.0
+    rsi_length = 14
+    rsi_overbought = 70
+    rsi_oversold = 40  # 放宽超卖阈值到 40
 
     def informative_pairs(self):
-        # 定义辅助时间框架
         pairs = self.dp.current_whitelist()
         return [(pair, '15m') for pair in pairs] + [(pair, '1h') for pair in pairs]
 
@@ -82,20 +80,39 @@ class FreqaiPrimer(IStrategy):
             (dataframe['open'] < dataframe['close'].shift(1))
         )
 
+        # 调试：打印指标值（最后 5 行）
+        print(f"Pair: {metadata['pair']}, Last 5 rows:")
+        print(dataframe[['date', 'close', 'bb_lower_3m', 'rsi_3m', 'rsi_15m', 'rsi_1h', 'bullish_engulfing', 'volume', 'volume_ma']].tail(5))
+
         return dataframe
 
     def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
-        # 做多条件
-        dataframe.loc[
-            (
-                (dataframe['close'] <= dataframe['bb_lower_3m']) &
-                (dataframe['rsi_3m'] < self.rsi_oversold) &
-                (dataframe['rsi_15m'] < self.rsi_oversold) &
-                (dataframe['close'] <= dataframe['bb_lower_1h']) &
-                (dataframe['bullish_engulfing']) &
-                (dataframe['volume'] > dataframe['volume_ma'])
-            ),
-            'enter_long'] = 1
+        # 做多条件（进一步放宽）
+        conditions = [
+            (dataframe['close'] <= dataframe['bb_lower_3m'] * 1.05),  # 价格接近 3m 布林带下轨（允许 5% 偏差）
+            (dataframe['rsi_3m'] < self.rsi_oversold),  # 3m RSI 超卖 (< 40)
+            (dataframe['rsi_15m'] < self.rsi_oversold),  # 15m RSI 超卖 (< 40)
+            (dataframe['volume'] > dataframe['volume_ma'])  # 成交量高于均量
+        ]
+        # 看涨吞没或极低 RSI（可选）
+        conditions.append(dataframe['bullish_engulfing'] | (dataframe['rsi_3m'] < self.rsi_oversold - 10))  # RSI < 30 替代看涨吞没
+
+        # 应用条件
+        dataframe.loc[conditions[0] & conditions[1] & conditions[2] & conditions[3] & conditions[4], 'enter_long'] = 1
+
+        # 调试：检查每个条件的触发情况
+        print(f"Pair: {metadata['pair']}, Entry condition checks:")
+        print(f" - Close <= bb_lower_3m * 1.05: {(dataframe['close'] <= dataframe['bb_lower_3m'] * 1.05).sum()} candles")
+        print(f" - RSI_3m < {self.rsi_oversold}: {(dataframe['rsi_3m'] < self.rsi_oversold).sum()} candles")
+        print(f" - RSI_15m < {self.rsi_oversold}: {(dataframe['rsi_15m'] < self.rsi_oversold).sum()} candles")
+        print(f" - Volume > Volume_MA: {(dataframe['volume'] > dataframe['volume_ma']).sum()} candles")
+        print(f" - Bullish Engulfing or RSI_3m < {self.rsi_oversold - 10}: {(dataframe['bullish_engulfing'] | (dataframe['rsi_3m'] < self.rsi_oversold - 10)).sum()} candles")
+        if dataframe['enter_long'].sum() > 0:
+            print(f"Entry signals found at:")
+            print(dataframe[dataframe['enter_long'] == 1][['date', 'close', 'rsi_3m', 'rsi_15m', 'bullish_engulfing']])
+        else:
+            print("No entry signals generated.")
+
         return dataframe
 
     def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: