抬高入场门槛
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zhangkun9038@dingtalk.com
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482e4ec3af
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@ -204,7 +204,7 @@ class FreqaiPrimer(IStrategy):
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}
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},
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"fit_live_predictions_candles": 100,
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"live_retrain_candles": 100,
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"live_retrain_candles": 50, # 加快训练频率，每50根K线重新训练
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}
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@staticmethod
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@ -775,18 +775,18 @@ class FreqaiPrimer(IStrategy):
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entry_tag = ""
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if is_green_channel:
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# 🟢 牛市绿色通道：持仓≤2个，25USDT入场，5条件需要满足4个
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cond1 = (dataframe["&-price_value_divergence"] < self.buy_threshold * 1.8) # 超宽松偏离度
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cond2 = (dataframe["volume_z_score"] > volume_z_score_threshold * 0.4) # 超低成交量要求
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cond3 = (dataframe["rsi"] < rsi_threshold * 1.4) # 超宽松RSI
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cond4 = (dataframe["close"] <= dataframe["bb_upperband"] * 1.05) # 允许上轨附近
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cond5 = (dataframe["stochrsi_k"] < stochrsi_threshold * 1.4) # 超宽松STOCHRSI
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# 🟢 牛市绿色通道：持仓≤2个，25USDT入场，6条件需要满足5个（适度提高门槛）
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cond1 = (dataframe["&-price_value_divergence"] < self.buy_threshold * 1.1) # 稍微收紧偏离度要求
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cond2 = (dataframe["volume_z_score"] > volume_z_score_threshold * 0.9) # 稍微提高成交量要求
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cond3 = (dataframe["rsi"] < rsi_threshold * 1.05) # 稍微收紧RSI要求
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cond4 = (dataframe["close"] <= dataframe["bb_lowerband"] * 1.01) # 稍微收紧布林带要求
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cond5 = (dataframe["stochrsi_k"] < stochrsi_threshold * 0.95) # 稍微收紧STOCHRSI要求
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cond6 = (dataframe["close"] < dataframe["ema200"] * 0.99) # 新增：价格略低于EMA200
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core_conditions = [cond1, cond2, cond3, cond4, cond5]
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# 使用向量化操作计算满足条件的数量
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satisfied_count_vector = cond1.astype(int) + cond2.astype(int) + cond3.astype(int) + cond4.astype(int) + cond5.astype(int)
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buy_condition = satisfied_count_vector >= 4
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entry_tag = "bull_green_channel"
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core_conditions = [cond1, cond2, cond3, cond4, cond5, cond6]
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satisfied_count_vector = cond1.astype(int) + cond2.astype(int) + cond3.astype(int) + cond4.astype(int) + cond5.astype(int) + cond6.astype(int)
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buy_condition = satisfied_count_vector >= 5 # 6条件需满足5个
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entry_tag = "bull_green_channel_moderate"
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# 仅在日志中使用最后一行的值
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if len(dataframe) > 0:
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@ -794,43 +794,48 @@ class FreqaiPrimer(IStrategy):
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logger.info(f"[{pair}] 🟢 牛市绿色通道：持仓{open_trades}≤2个，25USDT入场，5条件需要满足{satisfied_count}/4个")
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elif trend_status == "bullish":
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# 牛市正常通道：持仓>2个，75USDT入场，必须满足全部7个条件
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cond1 = (dataframe["&-price_value_divergence"] < self.buy_threshold * 1.5) # 放宽到1.5倍
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cond2 = (dataframe["volume_z_score"] > volume_z_score_threshold * 0.7) # 降低成交量要求
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cond3 = (dataframe["rsi"] < rsi_threshold * 1.2) # 放宽RSI要求
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cond4 = (dataframe["close"] <= dataframe["bb_upperband"]) # 可以在上轨附近入场
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cond5 = (dataframe["stochrsi_k"] < stochrsi_threshold * 1.2) # 放宽STOCHRSI要求
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cond6 = pd.Series([True] * len(dataframe), index=dataframe.index) # 取消熊市过滤
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cond7 = pd.Series([True] * len(dataframe), index=dataframe.index) # 取消超买过滤
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buy_condition = cond1 & cond2 & cond3 & cond4 & cond5 & cond6 & cond7
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entry_tag = "bull_normal"
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logger.info(f"[{pair}] 🚀 牛市正常通道：持仓{open_trades}>2个，75USDT入场，必须满足全部7个条件")
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# 牛市正常通道：持仓>2个时适度提高门槛
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cond1 = (dataframe["&-price_value_divergence"] < self.buy_threshold * 0.95) # 稍微收紧偏离度
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cond2 = (dataframe["volume_z_score"] > volume_z_score_threshold * 1.05) # 稍微提高成交量要求
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cond3 = (dataframe["rsi"] < rsi_threshold * 0.95) # 稍微收紧RSI要求
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cond4 = (dataframe["close"] <= dataframe["bb_lowerband"] * 0.99) # 稍微收紧布林带要求
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cond5 = (dataframe["stochrsi_k"] < stochrsi_threshold * 0.9) # 稍微收紧STOCHRSI要求
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cond6 = pd.Series([True] * len(dataframe), index=dataframe.index) # 保持取消熊市过滤
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cond7 = pd.Series([True] * len(dataframe), index=dataframe.index) # 保持取消超买过滤
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cond8 = (dataframe["close"] < dataframe["ema200"] * 0.97) # 新增：价格略低于EMA200
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buy_condition = cond1 & cond2 & cond3 & cond4 & cond5 & cond6 & cond7 & cond8
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entry_tag = "bull_normal_moderate"
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logger.info(f"[{pair}] 🚀 牛市正常通道：持仓{open_trades}>2个，适度提高门槛")
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elif trend_status == "bearish":
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# 下跌趋势：严格入场条件，只抄底
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cond1 = (dataframe["&-price_value_divergence"] < self.buy_threshold * 0.7) # 严格到0.7倍
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cond2 = (dataframe["volume_z_score"] > volume_z_score_threshold * 1.3) # 提高成交量要求
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cond3 = (dataframe["rsi"] < rsi_threshold * 0.8) # 严格RSI要求
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cond4 = (dataframe["close"] <= dataframe["bb_lowerband"] * 0.95) # 必须跌破下轨
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cond5 = (dataframe["stochrsi_k"] < stochrsi_threshold * 0.8) # 严格STOCHRSI要求
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# 下跌趋势：适度提高门槛
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cond1 = (dataframe["&-price_value_divergence"] < self.buy_threshold * 0.8) # 稍微收紧偏离度
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cond2 = (dataframe["volume_z_score"] > volume_z_score_threshold * 1.2) # 稍微提高成交量要求
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cond3 = (dataframe["rsi"] < rsi_threshold * 0.85) # 稍微收紧RSI要求
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cond4 = (dataframe["close"] <= dataframe["bb_lowerband"] * 0.95) # 稍微收紧布林带
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cond5 = (dataframe["stochrsi_k"] < stochrsi_threshold * 0.85) # 稍微收紧STOCHRSI
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cond6 = ~bearish_signal_aligned # 保持熊市过滤
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cond7 = ~stochrsi_overbought_aligned # 保持超买过滤
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buy_condition = cond1 & cond2 & cond3 & cond4 & cond5 & cond6 & cond7
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entry_tag = "bearish"
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logger.info(f"[{pair}] 📉 下跌趋势策略：严格入场条件")
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cond8 = (dataframe["close"] < dataframe["ema200"] * 0.95) # 新增：价格低于EMA200
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cond9 = (dataframe["volume"] > dataframe["volume"].rolling(20).mean() * 1.1) # 稍微提高放量确认
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buy_condition = cond1 & cond2 & cond3 & cond4 & cond5 & cond6 & cond7 & cond8 & cond9
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entry_tag = "bearish_moderate"
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logger.info(f"[{pair}] 📉 下跌趋势：适度提高门槛")
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else: # ranging
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# 震荡趋势：使用原策略
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cond1 = (dataframe["&-price_value_divergence"] < self.buy_threshold)
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cond2 = (dataframe["volume_z_score"] > volume_z_score_threshold)
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cond3 = (dataframe["rsi"] < rsi_threshold)
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cond4 = (dataframe["close"] <= dataframe["bb_lowerband"])
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cond5 = (dataframe["stochrsi_k"] < stochrsi_threshold)
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# 震荡趋势：适度提高门槛
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cond1 = (dataframe["&-price_value_divergence"] < self.buy_threshold * 0.9) # 稍微收紧偏离度
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cond2 = (dataframe["volume_z_score"] > volume_z_score_threshold * 1.1) # 稍微提高成交量要求
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cond3 = (dataframe["rsi"] < rsi_threshold * 0.9) # 稍微收紧RSI要求
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cond4 = (dataframe["close"] <= dataframe["bb_lowerband"] * 0.97) # 稍微收紧布林带
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cond5 = (dataframe["stochrsi_k"] < stochrsi_threshold * 0.9) # 稍微收紧STOCHRSI
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cond6 = ~bearish_signal_aligned
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cond7 = ~stochrsi_overbought_aligned
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buy_condition = cond1 & cond2 & cond3 & cond4 & cond5 & cond6 & cond7
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entry_tag = "ranging"
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logger.info(f"[{pair}] ⚖️ 震荡趋势策略：标准入场条件")
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cond8 = (dataframe["close"] < dataframe["ema200"] * 0.98) # 新增：价格略低于EMA200
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cond9 = (dataframe["adx"] > 20) # 保持趋势强度过滤
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buy_condition = cond1 & cond2 & cond3 & cond4 & cond5 & cond6 & cond7 & cond8 & cond9
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entry_tag = "ranging_moderate"
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logger.info(f"[{pair}] ⚖️ 震荡趋势：适度提高门槛")
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# 绿色通道和趋势状态的条件已经设置好buy_condition
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conditions.append(buy_condition)
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@ -865,7 +870,7 @@ class FreqaiPrimer(IStrategy):
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# 存储信号强度到dataframe
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dataframe.loc[buy_condition, 'signal_strength'] = signal_strength
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dataframe.loc[buy_condition, 'immediate_entry'] = signal_strength >= 75 # 75分以上立即入场
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dataframe.loc[buy_condition, 'immediate_entry'] = signal_strength >= 80 # 80分以上立即入场
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# 调试日志 - 仅在日志中使用最后一行的值
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if len(dataframe) > 0:
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