diff --git a/freqtrade/templates/freqaiprimer.py b/freqtrade/templates/freqaiprimer.py
index ebe225a7..36ff0273 100644
--- a/freqtrade/templates/freqaiprimer.py
+++ b/freqtrade/templates/freqaiprimer.py
@@ -638,15 +638,52 @@ class FreqaiPrimer(IStrategy):
             (dataframe['open'] < dataframe['close'].shift(1))
         )
 
-        # 计算各时间框架的趋势状态（牛/熊）
-        # 3m时间框架：ema50下穿ema200为熊，上穿为牛
-        dataframe['trend_3m'] = np.where(dataframe['ema_50_3m'] > dataframe['ema_200_3m'], 1, 0)
+        # 计算各时间框架的趋势状态（牛/熊）- 增强版V2：优先价格动量
+        # 原问题：EMA滞后严重，导致下跌市场仍判断为牛市
+        # 新方案：以价格实际涨跌为主，EMA为辅
         
-        # 15m时间框架：ema50下穿ema200为熊，上穿为牛
-        dataframe['trend_15m'] = np.where(dataframe['ema_50_15m'] > dataframe['ema_200_15m'], 1, 0)
+        # === 3m时间框架趋势判断（价格动量主导）===
+        # 条件1：价格动量（最近20根K线 = 1小时）- 主要指标
+        price_momentum_3m = dataframe['close'].pct_change(20)
+        momentum_bullish_3m = (price_momentum_3m > 0).astype(int)
+        # 条件2：EMA50 > EMA200（长期趋势）- 辅助指标
+        ema_trend_3m = (dataframe['ema_50_3m'] > dataframe['ema_200_3m']).astype(int)
+        # 综合判断：价格动量权重0.7 + EMA趋势权重0.3（价格优先）
+        dataframe['trend_3m'] = (momentum_bullish_3m * 0.7 + ema_trend_3m * 0.3).clip(0, 1)
         
-        # 1h时间框架：ema50下穿ema200为熊，上穿为牛
-        dataframe['trend_1h_ema'] = np.where(dataframe['ema_50_1h'] > dataframe['ema_200_1h'], 1, 0)
+        # === 15m时间框架趋势判断（价格动量主导）===
+        # 条件1：价格动量（最近12根K线 = 3小时）
+        price_momentum_15m = dataframe['close'].pct_change(12)
+        momentum_bullish_15m = (price_momentum_15m > 0).astype(int)
+        # 条件2：EMA50 > EMA200
+        ema_trend_15m = (dataframe['ema_50_15m'] > dataframe['ema_200_15m']).astype(int)
+        # 综合判断：价格动量0.7 + EMA0.3
+        dataframe['trend_15m'] = (momentum_bullish_15m * 0.7 + ema_trend_15m * 0.3).clip(0, 1)
+        
+        # === 1h时间框架趋势判断（多周期价格动量）⭐核心 ===
+        # 条件1：长期价格动量（最近24根K线 = 1天）- 核心指标
+        price_momentum_1h_long = dataframe['close'].pct_change(24)
+        momentum_long_bullish = (price_momentum_1h_long > 0).astype(int)
+        
+        # 条件2：中期价格动量（最近12根K线 = 12小时）
+        price_momentum_1h_mid = dataframe['close'].pct_change(12)
+        momentum_mid_bullish = (price_momentum_1h_mid > 0).astype(int)
+        
+        # 条件3：短期价格动量（最近5根K线 = 5小时）
+        price_momentum_1h_short = dataframe['close'].pct_change(5)
+        momentum_short_bullish = (price_momentum_1h_short > 0).astype(int)
+        
+        # 条件4：EMA趋势（辅助）
+        ema_trend_1h = (dataframe['ema_50_1h'] > dataframe['ema_200_1h']).astype(int)
+        
+        # 综合判断：长期动量0.35 + 中期动量0.30 + 短期动量0.25 + EMA0.10
+        # 价格动量合计90%，EMA仅10%（大幅降低EMA权重）
+        dataframe['trend_1h_ema'] = (
+            momentum_long_bullish * 0.35 + 
+            momentum_mid_bullish * 0.30 + 
+            momentum_short_bullish * 0.25 + 
+            ema_trend_1h * 0.10
+        ).clip(0, 1)
         
         # 计算熊牛得分（0-100）
         # 权重：3m熊牛权重10，15m熊牛权重35，1h熊牛权重65