From 1687e2ab37eb283d492c138e04f86423e4f21355 Mon Sep 17 00:00:00 2001 From: "zhangkun9038@dingtalk.com" Date: Wed, 14 Jan 2026 11:28:31 +0800 Subject: [PATCH] =?UTF-8?q?=E5=AE=8C=E5=85=A8=E5=8F=96=E6=B6=88EMA?= =?UTF-8?q?=E9=99=90=E5=88=B6?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- freqtrade/templates/freqaiprimer.py | 58 ++++++++--------------------- 1 file changed, 16 insertions(+), 42 deletions(-) diff --git a/freqtrade/templates/freqaiprimer.py b/freqtrade/templates/freqaiprimer.py index 0415a22f..b33f2a76 100644 --- a/freqtrade/templates/freqaiprimer.py +++ b/freqtrade/templates/freqaiprimer.py @@ -659,30 +659,19 @@ class FreqaiPrimer(IStrategy): # 辅助条件: 3m 和 15m 趋势确认（允许部分时间框架不一致） trend_confirmation = (dataframe['trend_3m'] == 1) | (dataframe['trend_15m'] == 1) - # 新增：EMA趋势过滤条件（核心入场限制，进一步放宽） - # 方案2：最近N根K线内发生过EMA5向上穿越，或者当前EMA5在EMA20之上 - # 这样既能捕捉趋势启动，又能在趋势延续时继续入场 - # 添加防御性检查，防止列不存在 - if 'ema_5_1h' in dataframe.columns and 'ema_20_1h' in dataframe.columns: - # 条件1：EMA5保持在EMA20之上（趋势延续） - ema5_above_ema20 = dataframe['ema_5_1h'] > dataframe['ema_20_1h'] - - # 条件2：最近20根1h K线内发生过向上穿越（捕捉趋势启动后的窗口期） - if 'ema5_cross_above_ema20' in dataframe.columns: - # 使用rolling.max检查最近20根K线内是否有True值 - recent_cross = dataframe['ema5_cross_above_ema20'].rolling(window=20, min_periods=1).max() == 1 - # 两个条件满足其一即可：要么当前在上方，要么最近穿越过 - ema_trend_filter = ema5_above_ema20 | recent_cross - else: - # 如果没有交叉列，只用保持在上方的条件 - ema_trend_filter = ema5_above_ema20 - else: - # 如果列不存在，创建一个全False的Series（不允许入场） - self.strategy_log(f"[{metadata['pair']}] 警告：ema_5_1h或ema_20_1h列不存在，过滤条件设为False") - ema_trend_filter = pd.Series(False, index=dataframe.index) + # EMA趋势过滤条件（已取消，太严格导致入场太少） + # 如果需要重新启用，取消下面注释并在final_condition中加上 & ema_trend_filter + # if 'ema_5_1h' in dataframe.columns and 'ema_20_1h' in dataframe.columns: + # ema5_above_ema20 = dataframe['ema_5_1h'] > dataframe['ema_20_1h'] + # if 'ema5_cross_above_ema20' in dataframe.columns: + # recent_cross = dataframe['ema5_cross_above_ema20'].rolling(window=20, min_periods=1).max() == 1 + # ema_trend_filter = ema5_above_ema20 | recent_cross + # else: + # ema_trend_filter = ema5_above_ema20 + # else: + # ema_trend_filter = pd.Series(False, index=dataframe.index) - # 合并所有条件（减少强制性条件） - # 至少满足多个条件中的一定数量，并且必须满足EMA5向上穿越EMA20 + # 合并所有条件（已移除EMA过滤限制） condition_count = ( close_to_bb_lower_1h.astype(int) + rsi_condition_1h.astype(int) + @@ -691,9 +680,8 @@ class FreqaiPrimer(IStrategy): (volume_spike | bb_width_condition).astype(int) + # 成交量或布林带宽度满足其一即可 trend_confirmation.astype(int) ) - # 修改最终条件：必须同时满足最小条件数量和EMA趋势过滤 - basic_condition = condition_count >= self.min_condition_count.value - final_condition = basic_condition & ema_trend_filter + # 最终条件：至少满足最小条件数量（已移除EMA过滤限制） + final_condition = condition_count >= self.min_condition_count.value # 设置入场信号 dataframe.loc[final_condition, 'enter_long'] = 1 @@ -767,13 +755,6 @@ class FreqaiPrimer(IStrategy): dataframe.loc[final_condition_updated, 'enter_price'] = dataframe.loc[final_condition_updated, 'close'] * 0.9833 # 增强调试信息 - # 确保ema_trend_filter是Series类型才能调用sum() - if isinstance(ema_trend_filter, pd.Series): - ema_trend_count = ema_trend_filter.sum() - else: - ema_trend_count = 0 - - basic_condition_count = basic_condition.sum() final_condition_count = final_condition.sum() self.strategy_log(f"[{metadata['pair']}] 入场条件检查:") @@ -783,13 +764,7 @@ class FreqaiPrimer(IStrategy): self.strategy_log(f" - MACD 上升趋势: {macd_condition_1h.sum()} 次") self.strategy_log(f" - 成交量或布林带宽度: {(volume_spike | bb_width_condition).sum()} 次") self.strategy_log(f" - 趋势确认: {trend_confirmation.sum()} 次") - self.strategy_log(f" - EMA趋势过滤(在上方或20根K线内穿越): {ema_trend_count} 次") - self.strategy_log(f" - 基本条件满足: {basic_condition_count} 次") - self.strategy_log(f" - 最终条件(基本+EMA过滤): {final_condition_count} 次") - - # 如果EMA条件满足但最终条件未满足，输出详细信息 - if ema_trend_count > 0 and final_condition_count == 0: - self.strategy_log(f"[{metadata['pair']}] 注意：检测到 {ema_trend_count} 次EMA趋势过滤满足，但由于其他条件不足未能生成入场信号") + self.strategy_log(f" - 最终入场信号: {final_condition_count} 次") # 在populate_entry_trend方法末尾添加 # 计算条件间的相关性 conditions = DataFrame({ @@ -798,8 +773,7 @@ class FreqaiPrimer(IStrategy): 'stochrsi': stochrsi_condition_1h, 'macd': macd_condition_1h, 'vol_bb': (volume_spike | bb_width_condition), - 'trend': trend_confirmation, - 'ema_trend': ema_trend_filter + 'trend': trend_confirmation }) correlation = conditions.corr().mean().mean() #self.strategy_log(f"[{metadata['pair']}] 条件平均相关性: {correlation:.2f}")