diff --git a/freqtrade/templates/freqaiprimer.py b/freqtrade/templates/freqaiprimer.py
index e21dd754..38e72e93 100644
--- a/freqtrade/templates/freqaiprimer.py
+++ b/freqtrade/templates/freqaiprimer.py
@@ -12,12 +12,12 @@ import datetime
 logger = logging.getLogger(__name__)
 
 class FreqaiPrimer(IStrategy):
-    # 策略参数 - 调整以提高单笔盈利潜力
+    # 策略参数 - 设置基于市场状态的动态ROI
     minimal_roi = {
-        "0": 0.05,    # 5% ROI (10 分钟内)
-        "60": 0.03,   # 3% ROI (1 小时)
-        "180": 0.01,  # 1% ROI (3 小时)
-        "360": 0.005  # 0.5% ROI (6 小时)
+        "0": 0.08,    # 8% ROI (10 分钟内)
+        "60": 0.05,   # 5% ROI (1 小时)
+        "180": 0.02,  # 2% ROI (3 小时)
+        "360": 0.01   # 1% ROI (6 小时)
     }
     
     stoploss = -0.15  # 固定止损 -15% (大幅放宽止损以承受更大波动)
@@ -57,8 +57,8 @@ class FreqaiPrimer(IStrategy):
     bb_length = 20
     bb_std = 2.0
     rsi_length = 14
-    rsi_overbought = 58  # 超买阈值
-    rsi_oversold = 42    # 放宽超卖阈值，增加入场信号
+    rsi_overbought = 62  # 提高超买阈值，减少过早卖出
+    rsi_oversold = 38    # 进一步放宽超卖阈值，增加优质入场信号
     
     # 剧烈拉升检测参数
     H1_MAX_CANDLES = 200  # 检查最近200根1h K线
@@ -270,13 +270,14 @@ class FreqaiPrimer(IStrategy):
         trend_reversal = merged_data['rsi_15m'] > 75
         
         # 动态调整退出条件 - 提高ATR倍数以增加单笔盈利潜力
-        # 强劲趋势中：大幅提高ATR倍数到5.5倍，充分利用趋势利润
-        dataframe.loc[strong_trend & ((dataframe['close'] > dataframe['open'] + dataframe['atr'] * 5.5) | (basic_exit & trend_reversal)), 'exit_long'] = 1
+        # 强劲趋势中：更激进地持有，提高ATR倍数到6.5倍
+        dataframe.loc[strong_trend & ((dataframe['close'] > dataframe['open'] + dataframe['atr'] * 6.5) | (basic_exit & trend_reversal)), 'exit_long'] = 1
         
-        # 一般趋势中：提高到4倍ATR退出
-        dataframe.loc[normal_trend & ((dataframe['close'] > dataframe['open'] + dataframe['atr'] * 4) | basic_exit), 'exit_long'] = 1
+        # 一般趋势中：提高到4.5倍ATR退出
+        dataframe.loc[normal_trend & ((dataframe['close'] > dataframe['open'] + dataframe['atr'] * 4.5) | basic_exit), 'exit_long'] = 1
         
         # 非趋势或弱势：保持2倍ATR退出
+        dataframe.loc[~strong_trend & ~normal_trend & (basic_exit | (dataframe['close'] > dataframe['open'] + dataframe['atr'] * 2)), 'exit_long'] = 1
         
         # 记录退出决策日志
         if len(dataframe[dataframe['exit_long'] == 1]) > 0:
@@ -385,13 +386,13 @@ class FreqaiPrimer(IStrategy):
         dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
         current_state = dataframe['market_state'].iloc[-1] if 'market_state' in dataframe.columns else 'unknown'
         
-        # 定义更激进的渐进式止盈水平，提高收益上限
+        # 定义高收益潜力的渐进式止盈水平
         profit_levels = {
             # 状态: [(止盈触发利润, 止盈比例)]
-            'strong_bull': [(0.03, 0.2), (0.06, 0.35), (0.09, 0.5), (0.12, 0.65), (0.15, 0.8)],  # 强劲牛市的渐进止盈，提高目标
-            'weak_bull': [(0.02, 0.25), (0.04, 0.45), (0.07, 0.7), (0.10, 0.9)],  # 弱牛市的渐进止盈
-            'neutral': [(0.015, 0.35), (0.03, 0.6), (0.05, 0.85)],  # 中性市场的渐进止盈
-            'bear': [(0.01, 0.6), (0.02, 0.9), (0.03, 1.0)]  # 熊市的渐进止盈（更保守）
+            'strong_bull': [(0.04, 0.15), (0.08, 0.3), (0.12, 0.45), (0.16, 0.6), (0.20, 0.75), (0.25, 0.9)],  # 强劲牛市更激进的渐进止盈
+            'weak_bull': [(0.03, 0.2), (0.06, 0.4), (0.09, 0.6), (0.13, 0.8), (0.16, 0.95)],  # 弱牛市提高止盈目标
+            'neutral': [(0.02, 0.3), (0.04, 0.55), (0.07, 0.8), (0.10, 0.95)],  # 中性市场适度提高目标
+            'bear': [(0.01, 0.5), (0.025, 0.85), (0.04, 1.0)]  # 熊市的渐进止盈（更保守）
         }
         
         # 默认使用中性市场的止盈设置
@@ -415,13 +416,20 @@ class FreqaiPrimer(IStrategy):
     def adjust_trade_position(self, trade: 'Trade', current_time, current_rate: float, 
                              current_profit: float, min_stake: float, max_stake: float, **kwargs) -> float:
         """
-        根据用户要求实现加仓逻辑
+        高级加仓逻辑：在强劲趋势中增加加仓次数和额度
         - 加仓间隔设置为0.047（4.7%回调）
-        - 加仓额度为: (stake_amount / 2) ^ (加仓次数 - 1)
+        - 加仓额度为: (stake_amount / 2) ^ (加仓次数)
+        - 根据市场状态动态调整加仓参数
         """
         # 检查是否已启用加仓
         if not hasattr(self, 'max_entry_adjustments'):
-            self.max_entry_adjustments = 3  # 设置最大加仓次数
+            # 在强劲牛市中增加最大加仓次数
+            dataframe, _ = self.dp.get_analyzed_dataframe(trade.pair, self.timeframe)
+            current_state = dataframe['market_state'].iloc[-1] if 'market_state' in dataframe.columns else 'neutral'
+            if current_state == 'strong_bull':
+                self.max_entry_adjustments = 4  # 强劲牛市中增加到4次加仓
+            else:
+                self.max_entry_adjustments = 3  # 其他市场状态保持3次
             
         # 获取当前交易对
         pair = trade.pair