入场报价折扣率动态化

freqtrade/templates/freqaiprimer.py

@@ -50,6 +50,9 @@ class FreqaiPrimer(IStrategy):
     TREND_FINAL_BULLISH_THRESHOLD = 55  # 上涨趋势最终阈值
     TREND_FINAL_BEARISH_THRESHOLD = 13  # 下跌趋势最终阈值
     
+    # 🎯 绿色通道折扣常量（不走Hyperopt，单独维护）
+    GREEN_CHANNEL_DISCOUNT = 0.025  # 2.5% 固定折扣
+    
     # Hyperopt 可优化参数 - 基于初步结果调整范围
     trend_final_bullish_threshold = IntParameter(20, 85, default=71, space="buy", optimize=True, load=True)  # 降低上限，避免过于保守
     trend_final_bearish_threshold = IntParameter(5, 45, default=21, space="buy", optimize=True, load=True)   # 扩大下限，捕获更多熊市机会
@@ -87,6 +90,11 @@ class FreqaiPrimer(IStrategy):
     
     exit_ranging_trend_score_max = IntParameter(95, 99, default=98, space="sell", optimize=True, load=True)
     exit_ranging_trend_score_threshold = IntParameter(80, 90, default=85, space="sell", optimize=True, load=True)
+    
+    # 🎯 入场折扣率参数（可通过hyperopt优化）
+    entry_discount_bull_normal = DecimalParameter(0.005, 0.03, default=0.010, decimals=3, space="buy", optimize=True, load=True)  # 牛市正常通道折扣 (默认1%)
+    entry_discount_ranging = DecimalParameter(0.001, 0.02, default=0.0075, decimals=3, space="buy", optimize=True, load=True)  # 震荡市折扣 (默认0.75%)
+    entry_discount_bearish = DecimalParameter(0.001, 0.015, default=0.005, decimals=3, space="buy", optimize=True, load=True)  # 熊市折扣 (默认0.5%)
 
     # --- 🛠️ 固定配置参数 ---
     stoploss = -0.15
@@ -759,6 +767,9 @@ class FreqaiPrimer(IStrategy):
             
             logger.info(f"[{pair}] 市场状态: {market_regime}, 阈值调整: {regime_adj['threshold_mult']}, 严格度调整: {regime_adj['strict_mult']}")
             
+            # 为每个入场信号定义详细的标签
+            entry_tag = ""
+            
             if is_green_channel:
                 # 🟢 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
@@ -771,6 +782,7 @@ class FreqaiPrimer(IStrategy):
                 # 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:
@@ -787,6 +799,7 @@ class FreqaiPrimer(IStrategy):
                 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":
@@ -799,6 +812,7 @@ class FreqaiPrimer(IStrategy):
                 cond6 = ~bearish_signal_aligned  # 保持熊市过滤
                 cond7 = ~stochrsi_overbought_aligned  # 保持超买过滤
                 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
@@ -811,6 +825,7 @@ class FreqaiPrimer(IStrategy):
                 cond6 = ~bearish_signal_aligned
                 cond7 = ~stochrsi_overbought_aligned
                 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
@@ -872,6 +887,7 @@ class FreqaiPrimer(IStrategy):
         if conditions:
             combined_condition = reduce(lambda x, y: x & y, conditions)
             dataframe.loc[combined_condition, 'enter_long'] = 1
+            dataframe.loc[combined_condition, 'entry_tag'] = entry_tag
 
             # 输出每个条件的状态
             logger.info(f"[{pair}] === 买入条件检查 ===")
@@ -1444,8 +1460,47 @@ class FreqaiPrimer(IStrategy):
 
     def custom_entry_price(self, pair: str, trade: Trade | None, current_time: datetime, proposed_rate: float,
                            entry_tag: str | None, side: str, **kwargs) -> float:
-        adjusted_rate = proposed_rate * (1 - 0.005)
+        """根据入场标签动态调整入场价格
-        logger.info(f"[{pair}] 自定义买入价：{adjusted_rate:.6f}（原价：{proposed_rate:.6f}）")
+        
+        基于入场信号的判定条件，为不同的市场状态提供不同的价格折扣：
+        - bull_green_channel: 牛市绿色通道（固定折扣，不走Hyperopt）
+        - bull_normal: 牛市正常通道（Hyperopt优化）
+        - ranging: 震荡市（Hyperopt优化）
+        - bearish: 熊市（Hyperopt优化）
+        
+        Args:
+            pair: 交易对
+            trade: 交易对象
+            current_time: 当前时间
+            proposed_rate: 建议价格
+            entry_tag: 入场信号标签
+            side: 交易方向
+            **kwargs: 其他参数
+            
+        Returns:
+            调整后的入场价格
+        """
+        # 根据入场标签获取对应的折扣率
+        if entry_tag == "bull_green_channel":
+            discount = self.GREEN_CHANNEL_DISCOUNT  # 牛市绿色通道固定折扣
+            logger.info(f"[{pair}] 🟢 牛市绿色通道入场，固定折扣: {discount*100:.2f}%")
+        elif entry_tag == "bull_normal":
+            discount = float(self.entry_discount_bull_normal.value)  # 牛市正常通道折扣（Hyperopt优化）
+            logger.info(f"[{pair}] 🚀 牛市正常通道入场，折扣率: {discount*100:.2f}%")
+        elif entry_tag == "ranging":
+            discount = float(self.entry_discount_ranging.value)  # 震荡市折扣（Hyperopt优化）
+            logger.info(f"[{pair}] ⚖️ 震荡市入场，折扣率: {discount*100:.2f}%")
+        elif entry_tag == "bearish":
+            discount = float(self.entry_discount_bearish.value)  # 熊市折扣（Hyperopt优化）
+            logger.info(f"[{pair}] 📉 熊市入场，折扣率: {discount*100:.2f}%")
+        else:
+            discount = 0.0  # 无折扣
+            logger.info(f"[{pair}] 无入场标签，使用原价 {proposed_rate:.6f}")
+            
+        adjusted_rate = proposed_rate * (1 - discount)
+        if discount > 0:
+            logger.info(f"[{pair}] 入场标签: {entry_tag}, 原价: {proposed_rate:.6f}, 调整后: {adjusted_rate:.6f}, 折扣: {discount*100:.2f}%")
+        
         return adjusted_rate
 
     def custom_exit_price(self, pair: str, trade: Trade,