diff --git a/freqtrade/templates/freqaiprimer.py b/freqtrade/templates/freqaiprimer.py index 26357874..53356fb8 100644 --- a/freqtrade/templates/freqaiprimer.py +++ b/freqtrade/templates/freqaiprimer.py @@ -204,7 +204,7 @@ class FreqaiPrimer(IStrategy): } }, "fit_live_predictions_candles": 100, - "live_retrain_candles": 50, # 加快训练频率，每50根K线重新训练 + "live_retrain_candles": 100, } @staticmethod @@ -775,18 +775,18 @@ class FreqaiPrimer(IStrategy): entry_tag = "" if is_green_channel: - # 🟢 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） - cond1 = (dataframe["&-price_value_divergence"] < self.buy_threshold * 1.1) # 稍微收紧偏离度要求 - cond2 = (dataframe["volume_z_score"] > volume_z_score_threshold * 0.9) # 稍微提高成交量要求 - cond3 = (dataframe["rsi"] < rsi_threshold * 1.05) # 稍微收紧RSI要求 - cond4 = (dataframe["close"] <= dataframe["bb_lowerband"] * 1.01) # 稍微收紧布林带要求 - cond5 = (dataframe["stochrsi_k"] < stochrsi_threshold * 0.95) # 稍微收紧STOCHRSI要求 - cond6 = (dataframe["close"] < dataframe["ema200"] * 0.99) # 新增：价格略低于EMA200 + # 🟢 牛市绿色通道：持仓≤2个，25USDT入场，5条件需要满足4个 + cond1 = (dataframe["&-price_value_divergence"] < self.buy_threshold * 1.8) # 超宽松偏离度 + cond2 = (dataframe["volume_z_score"] > volume_z_score_threshold * 0.4) # 超低成交量要求 + cond3 = (dataframe["rsi"] < rsi_threshold * 1.4) # 超宽松RSI + cond4 = (dataframe["close"] <= dataframe["bb_upperband"] * 1.05) # 允许上轨附近 + cond5 = (dataframe["stochrsi_k"] < stochrsi_threshold * 1.4) # 超宽松STOCHRSI - core_conditions = [cond1, cond2, cond3, cond4, cond5, cond6] - satisfied_count_vector = cond1.astype(int) + cond2.astype(int) + cond3.astype(int) + cond4.astype(int) + cond5.astype(int) + cond6.astype(int) - buy_condition = satisfied_count_vector >= 5 # 6条件需满足5个 - entry_tag = "bull_green_channel_moderate" + core_conditions = [cond1, cond2, cond3, cond4, cond5] + # 使用向量化操作计算满足条件的数量 + satisfied_count_vector = cond1.astype(int) + cond2.astype(int) + cond3.astype(int) + cond4.astype(int) + cond5.astype(int) + buy_condition = satisfied_count_vector >= 4 + entry_tag = "bull_green_channel" # 仅在日志中使用最后一行的值 if len(dataframe) > 0: @@ -794,48 +794,43 @@ class FreqaiPrimer(IStrategy): 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") elif trend_status == "bullish": - # 牛市正常通道：持仓>2个时适度提高门槛 - cond1 = (dataframe["&-price_value_divergence"] < self.buy_threshold * 0.95) # 稍微收紧偏离度 - cond2 = (dataframe["volume_z_score"] > volume_z_score_threshold * 1.05) # 稍微提高成交量要求 - cond3 = (dataframe["rsi"] < rsi_threshold * 0.95) # 稍微收紧RSI要求 - cond4 = (dataframe["close"] <= dataframe["bb_lowerband"] * 0.99) # 稍微收紧布林带要求 - cond5 = (dataframe["stochrsi_k"] < stochrsi_threshold * 0.9) # 稍微收紧STOCHRSI要求 - cond6 = pd.Series([True] * len(dataframe), index=dataframe.index) # 保持取消熊市过滤 - cond7 = pd.Series([True] * len(dataframe), index=dataframe.index) # 保持取消超买过滤 - cond8 = (dataframe["close"] < dataframe["ema200"] * 0.97) # 新增：价格略低于EMA200 - buy_condition = cond1 & cond2 & cond3 & cond4 & cond5 & cond6 & cond7 & cond8 - entry_tag = "bull_normal_moderate" - logger.info(f"[{pair}] 🚀 牛市正常通道：持仓{open_trades}>2个，适度提高门槛") + # 牛市正常通道：持仓>2个，75USDT入场，必须满足全部7个条件 + cond1 = (dataframe["&-price_value_divergence"] < self.buy_threshold * 1.5) # 放宽到1.5倍 + cond2 = (dataframe["volume_z_score"] > volume_z_score_threshold * 0.7) # 降低成交量要求 + cond3 = (dataframe["rsi"] < rsi_threshold * 1.2) # 放宽RSI要求 + cond4 = (dataframe["close"] <= dataframe["bb_upperband"]) # 可以在上轨附近入场 + cond5 = (dataframe["stochrsi_k"] < stochrsi_threshold * 1.2) # 放宽STOCHRSI要求 + cond6 = pd.Series([True] * len(dataframe), index=dataframe.index) # 取消熊市过滤 + cond7 = pd.Series([True] * len(dataframe), index=dataframe.index) # 取消超买过滤 + buy_condition = cond1 & cond2 & cond3 & cond4 & cond5 & cond6 & cond7 + entry_tag = "bull_normal" + 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") elif trend_status == "bearish": - # 下跌趋势：适度提高门槛 - cond1 = (dataframe["&-price_value_divergence"] < self.buy_threshold * 0.8) # 稍微收紧偏离度 - cond2 = (dataframe["volume_z_score"] > volume_z_score_threshold * 1.2) # 稍微提高成交量要求 - cond3 = (dataframe["rsi"] < rsi_threshold * 0.85) # 稍微收紧RSI要求 - cond4 = (dataframe["close"] <= dataframe["bb_lowerband"] * 0.95) # 稍微收紧布林带 - cond5 = (dataframe["stochrsi_k"] < stochrsi_threshold * 0.85) # 稍微收紧STOCHRSI + # 下跌趋势：严格入场条件，只抄底 + cond1 = (dataframe["&-price_value_divergence"] < self.buy_threshold * 0.7) # 严格到0.7倍 + cond2 = (dataframe["volume_z_score"] > volume_z_score_threshold * 1.3) # 提高成交量要求 + cond3 = (dataframe["rsi"] < rsi_threshold * 0.8) # 严格RSI要求 + cond4 = (dataframe["close"] <= dataframe["bb_lowerband"] * 0.95) # 必须跌破下轨 + cond5 = (dataframe["stochrsi_k"] < stochrsi_threshold * 0.8) # 严格STOCHRSI要求 cond6 = ~bearish_signal_aligned # 保持熊市过滤 cond7 = ~stochrsi_overbought_aligned # 保持超买过滤 - cond8 = (dataframe["close"] < dataframe["ema200"] * 0.95) # 新增：价格低于EMA200 - cond9 = (dataframe["volume"] > dataframe["volume"].rolling(20).mean() * 1.1) # 稍微提高放量确认 - buy_condition = cond1 & cond2 & cond3 & cond4 & cond5 & cond6 & cond7 & cond8 & cond9 - entry_tag = "bearish_moderate" - logger.info(f"[{pair}] 📉 下跌趋势：适度提高门槛") + buy_condition = cond1 & cond2 & cond3 & cond4 & cond5 & cond6 & cond7 + entry_tag = "bearish" + logger.info(f"[{pair}] 📉 下跌趋势策略：严格入场条件") else: # ranging - # 震荡趋势：适度提高门槛 - cond1 = (dataframe["&-price_value_divergence"] < self.buy_threshold * 0.9) # 稍微收紧偏离度 - cond2 = (dataframe["volume_z_score"] > volume_z_score_threshold * 1.1) # 稍微提高成交量要求 - cond3 = (dataframe["rsi"] < rsi_threshold * 0.9) # 稍微收紧RSI要求 - cond4 = (dataframe["close"] <= dataframe["bb_lowerband"] * 0.97) # 稍微收紧布林带 - cond5 = (dataframe["stochrsi_k"] < stochrsi_threshold * 0.9) # 稍微收紧STOCHRSI + # 震荡趋势：使用原策略 + cond1 = (dataframe["&-price_value_divergence"] < self.buy_threshold) + cond2 = (dataframe["volume_z_score"] > volume_z_score_threshold) + cond3 = (dataframe["rsi"] < rsi_threshold) + cond4 = (dataframe["close"] <= dataframe["bb_lowerband"]) + cond5 = (dataframe["stochrsi_k"] < stochrsi_threshold) cond6 = ~bearish_signal_aligned cond7 = ~stochrsi_overbought_aligned - cond8 = (dataframe["close"] < dataframe["ema200"] * 0.98) # 新增：价格略低于EMA200 - cond9 = (dataframe["adx"] > 20) # 保持趋势强度过滤 - buy_condition = cond1 & cond2 & cond3 & cond4 & cond5 & cond6 & cond7 & cond8 & cond9 - entry_tag = "ranging_moderate" - logger.info(f"[{pair}] ⚖️ 震荡趋势：适度提高门槛") + buy_condition = cond1 & cond2 & cond3 & cond4 & cond5 & cond6 & cond7 + entry_tag = "ranging" + logger.info(f"[{pair}] ⚖️ 震荡趋势策略：标准入场条件") # 绿色通道和趋势状态的条件已经设置好buy_condition conditions.append(buy_condition) @@ -870,7 +865,7 @@ class FreqaiPrimer(IStrategy): # 存储信号强度到dataframe dataframe.loc[buy_condition, 'signal_strength'] = signal_strength - dataframe.loc[buy_condition, 'immediate_entry'] = signal_strength >= 80 # 80分以上立即入场 + dataframe.loc[buy_condition, 'immediate_entry'] = signal_strength >= 75 # 75分以上立即入场 # 调试日志 - 仅在日志中使用最后一行的值 if len(dataframe) > 0: