feat: 盈亏计算改为账户余额% + 拖尾止损绝对值扣除

- _calculate_pnl_pct: 从金价涨跌%改为账户余额%
- _get_contract_size: 新增缓存合约规格方法
- 硬止损: 从金价%乘法改为账户$→点数→价格转换
- 拖尾止损: peak*(1-retrace) 改为 peak-retrace（绝对值扣除）
- 统一 _record_closed_trade/_calculate_unrealized_pnl 使用缓存合约规格
- RISK_CONFIG: 止损-1.5%/止盈+3.0%/拖尾激活+2.0%/回撤1.0%（均为账户%）

.restart_signal

@@ -0,0 +1 @@
+2026-05-14T14:19:14.539006

config.py

@@ -135,54 +135,55 @@ GENETIC_OPTIMIZER_CONFIG = {
 
 # 信号阈值配置（优化器结果 2026-05-10，5万根M1数据）
 SIGNAL_THRESHOLDS = {
-    "buy_threshold": 1.344,
+    "buy_threshold": 1.0315663601353515,
-    "sell_threshold": -2.980
+    "sell_threshold": -2.312867704316165
 }
 
 
 # 风险管理参数（优化器结果 2026-05-10，5万根M1数据）
 RISK_CONFIG = {
-    "stop_loss_pct": -0.046,
+    # ★ 以下百分比均为账户余额%，非金价涨跌%
-    "profit_retracement_pct": 0.030,
+    #    例：余额$1682，-1.5% = -$25 ≈ 25点金价（0.01手）
-    "min_profit_for_trailing": 0.03,
+    "stop_loss_pct": -0.015,            # -1.5% 账户
-    "take_profit_pct": 0.246,
+    "profit_retracement_pct": 0.01,     # 1.0% 账户（拖尾回撤容忍）
+    "min_profit_for_trailing": 0.02,    # +2.0% 后激活拖尾
+    "take_profit_pct": 0.03,            # +3.0% 账户
     "max_daily_loss": -0.3,
     "max_holding_minutes": 133,
     "min_profit_for_time_exit": 0.010,
     "cooldown_bars": 30,
     # ★ 硬止损倍率：MT5 服务器端 SL/TP = 软止损 × 倍率（兜底，仅 EA 挂掉时触发）
-    #    硬止损必须比软止损宽（倍率>1），否则会抢先触发导致拖尾失效
+    "hard_sl_multiplier": 1.5,   # 硬 SL = 软 SL × 1.5（-1.5%→-2.25%账户）
-    "hard_sl_multiplier": 1.5,   # 硬 SL = 软 SL × 1.5（例如软-4.6%→硬-6.9%）
+    "hard_tp_multiplier": 1.3,   # 硬 TP = 软 TP × 1.3（+3.0%→+3.9%账户）
-    "hard_tp_multiplier": 1.3,   # 硬 TP = 软 TP × 1.3（例如软+24.6%→硬+32.0%）
 }
 
 # 市场状态分析参数
 MARKET_STATE_CONFIG = {
-    "trend_period": 24,
+    "trend_period": 83,
-    "retracement_tolerance": 0.425,
+    "retracement_tolerance": 0.15567164907853615,
-    "volume_period": 21,
+    "volume_period": 29,
-    "volume_ma_period": 12
+    "volume_ma_period": 23
 }
 
 # 策略参数配置（优化器结果 2026-05-10，5万根M1数据）
 STRATEGY_CONFIG = {
     "ma_cross": {
-        "short_window": 12,
+        "short_window": 13,
-        "long_window": 30
+        "long_window": 17
     },
     "rsi": {
-        "period": 21,
+        "period": 30,
-        "overbought": 75,
+        "overbought": 68,
-        "oversold": 26
+        "oversold": 32
     },
     "bollinger": {
         "period": 20,
-        "std_dev": 2.162
+        "std_dev": 2.4663422649047333
     },
     "macd": {
-        "fast_ema": 16,
+        "fast_ema": 14,
-        "slow_ema": 34,
+        "slow_ema": 24,
-        "signal_period": 12
+        "signal_period": 9
     },
     "mean_reversion": {
         "period": 29,
@@ -190,7 +191,7 @@ STRATEGY_CONFIG = {
     },
     "momentum_breakout": {
         "period": 15,
-        "momentum_period": 17
+        "momentum_period": 13
     },
     "kdj": {
         "period": 21
@@ -199,96 +200,96 @@ STRATEGY_CONFIG = {
         "period": 42
     },
     "daily_breakout": {
-        "bars_count": 746
+        "bars_count": 2008
     },
     "wave_theory": {
         "ema_short": 3,
-        "ema_medium": 16,
+        "ema_medium": 11,
-        "ema_long": 26,
+        "ema_long": 46,
-        "wave_period": 32,
+        "wave_period": 11,
-        "range_period": 30,
+        "range_period": 35,
-        "adx_period": 23,
+        "adx_period": 20,
         "momentum_period": 10,
-        "range_threshold": 0.002,
+        "range_threshold": 0.01,
-        "adx_threshold": 23
+        "adx_threshold": 21
     }
 }
 
 # 市场趋势判断权重配置
 TREND_INDICATOR_WEIGHTS = {
-    "price_breakout": -0.0949,
+    "price_breakout": 0.1504199442999585,
-    "volume_confirmation": 0.5277,
+    "volume_confirmation": 0.12782205952949638,
     "momentum oscillator": 0.3677,
-    "moving_average": 0.1506
+    "moving_average": 0.4092273363154768
 }
 
 # 趋势判断阈值
 TREND_THRESHOLDS = {
-    "strong_trend": 0.4182,
+    "strong_trend": 0.7940886082643032,
-    "weak_trend": 0.2164,
+    "weak_trend": 0.4565953163045441,
-    "volume_spike": 1.5843,
+    "volume_spike": 2.7329673335105396,
-    "oversold": 24,
+    "oversold": 32,
-    "overbought": 80
+    "overbought": 68
 }
 
 
 # 动态权重配置（优化器结果 2026-05-10，5万根M1数据）
 DEFAULT_WEIGHTS = {
-    "ma_cross": 0.809,
+    "ma_cross": 0.32048324544087786,
-    "rsi": 1.141,
+    "rsi": 1.906009222972592,
-    "bollinger": 0.389,
+    "bollinger": 0.9232444456662969,
-    "mean_reversion": 1.106,
+    "mean_reversion": 1.1649306516234597,
-    "momentum_breakout": 0.147,
+    "momentum_breakout": 0.8769099086178171,
-    "macd": 1.181,
+    "macd": 0.748930985323352,
-    "kdj": 1.525,
+    "kdj": 1.4647470623067596,
-    "turtle": 0.559,
+    "turtle": 1.637931136008917,
-    "daily_breakout": 1.846,
+    "daily_breakout": 1.478598649389487,
-    "wave_theory": 1.361
+    "wave_theory": 0.818283180489803
 }
 
 # 市场状态策略权重配置
 MARKET_STATE_WEIGHTS = {
     "uptrend": {
-        "ma_cross": 1.50,
+        "ma_cross": 0.32048324544087786,
-        "momentum_breakout": 1.20,
+        "momentum_breakout": 0.8769099086178171,
-        "turtle": 0.25,
+        "turtle": 1.637931136008917,
-        "macd": 0.35,
+        "macd": 0.748930985323352,
-        "daily_breakout": 1.50,
+        "daily_breakout": 1.478598649389487,
-        "rsi": 1.00,
+        "rsi": 1.906009222972592,
-        "bollinger": 1.00,
+        "bollinger": 0.9232444456662969,
-        "kdj": 0.40,
+        "kdj": 1.4647470623067596,
-        "mean_reversion": 0.80,
+        "mean_reversion": 1.1649306516234597,
-        "wave_theory": 0.20
+        "wave_theory": 0.818283180489803
     },
     "downtrend": {
-        "ma_cross": 1.50,
+        "ma_cross": 0.32048324544087786,
-        "momentum_breakout": 1.20,
+        "momentum_breakout": 0.8769099086178171,
-        "turtle": 0.25,
+        "turtle": 1.637931136008917,
-        "macd": 0.35,
+        "macd": 0.748930985323352,
-        "daily_breakout": 1.50,
+        "daily_breakout": 1.478598649389487,
-        "rsi": 1.00,
+        "rsi": 1.906009222972592,
-        "bollinger": 1.00,
+        "bollinger": 0.9232444456662969,
-        "kdj": 0.40,
+        "kdj": 1.4647470623067596,
-        "mean_reversion": 0.80,
+        "mean_reversion": 1.1649306516234597,
-        "wave_theory": 0.20
+        "wave_theory": 0.818283180489803
     },
     "ranging": {
-        "rsi": 1.60,
+        "rsi": 1.906009222972592,
-        "bollinger": 1.70,
+        "bollinger": 0.9232444456662969,
-        "mean_reversion": 1.50,
+        "mean_reversion": 1.1649306516234597,
-        "kdj": 1.00,
+        "kdj": 1.4647470623067596,
-        "wave_theory": 0.50,
+        "wave_theory": 0.818283180489803,
-        "ma_cross": 0.70,
+        "ma_cross": 0.32048324544087786,
-        "macd": 0.20,
+        "macd": 0.748930985323352,
-        "turtle": 0.10,
+        "turtle": 1.637931136008917,
-        "momentum_breakout": 0.50,
+        "momentum_breakout": 0.8769099086178171,
-        "daily_breakout": 0.90
+        "daily_breakout": 1.478598649389487
     },
     "none": DEFAULT_WEIGHTS
 }
 
 # 市场趋势置信度阈值配置
 CONFIDENCE_THRESHOLDS = {
-    "high_confidence": 0.8474,
+    "high_confidence": 0.6813641209473742,
-    "medium_confidence": 0.4964
+    "medium_confidence": 0.6336441706563001
 }

core/risk/exit_rules.py

@@ -58,7 +58,8 @@ class TrailingStopRule(BaseExitRule):
         if ctx.peak_profit_pct <= min_profit:
             return "none", ""
 
-        stop_level = ctx.peak_profit_pct * (1 - retracement_pct)
+        # ★ 回撤从峰值绝对值扣除（账户%，非相对%）：峰值+2.0%回撤1.0%→止损在+1.0%
+        stop_level = ctx.peak_profit_pct - retracement_pct
         if ctx.current_profit_pct <= stop_level:
             return "close", (
                 f"追踪止损触发 "

core/risk/position.py

@@ -189,18 +189,27 @@ class PositionManager:
                 return False
 
             # ★ 计算 MT5 硬止损/硬止盈（兜底安全网）
+            #    公式：账户% × 余额 × 倍率 → 美元 → 金价点数 → 价格
             hard_sl_price = None
             hard_tp_price = None
+            contract_size = self._get_contract_size()
+            points_per_dollar = 1.0 / (position_volume * contract_size) if position_volume > 0 else 0
+
+            sl_dollars = abs(self.stop_loss_pct) * self.total_equity * self.hard_sl_mult  # 正数
+            tp_dollars = abs(self.take_profit_pct) * self.total_equity * self.hard_tp_mult
+            sl_points = sl_dollars * points_per_dollar
+            tp_points = tp_dollars * points_per_dollar
+
             if direction == 'buy':
                 if self.hard_sl_mult > 0:
-                    hard_sl_price = round(execution_price * (1 + self.stop_loss_pct * self.hard_sl_mult), 2)
+                    hard_sl_price = round(execution_price - sl_points, 2)
                 if self.hard_tp_mult > 0:
-                    hard_tp_price = round(execution_price * (1 + self.take_profit_pct * self.hard_tp_mult), 2)
+                    hard_tp_price = round(execution_price + tp_points, 2)
             else:
                 if self.hard_sl_mult > 0:
-                    hard_sl_price = round(execution_price * (1 - self.stop_loss_pct * self.hard_sl_mult), 2)
+                    hard_sl_price = round(execution_price + sl_points, 2)
                 if self.hard_tp_mult > 0:
-                    hard_tp_price = round(execution_price * (1 - self.take_profit_pct * self.hard_tp_mult), 2)
+                    hard_tp_price = round(execution_price - tp_points, 2)
 
             order_result = self.data_provider.send_order(
                 self.symbol, direction, position_volume,
@@ -309,25 +318,39 @@ class PositionManager:
 
     # ── 盈亏计算 ──
 
+    def _get_contract_size(self) -> float:
+        """获取合约规格（缓存避免重复API调用）"""
+        if not hasattr(self, '_cached_contract_size'):
+            symbol_info = self.data_provider.get_symbol_info(self.symbol)
+            self._cached_contract_size = (
+                symbol_info['trade_contract_size']
+                if symbol_info and isinstance(symbol_info, dict)
+                else 100
+            ) if symbol_info else 100
+        return self._cached_contract_size
+
     def _calculate_pnl_pct(self, position, current_price_value):
+        """★ 账户余额百分比盈亏（非金价涨跌%）"""
         entry_price = position['entry_price']
+        quantity = position.get('quantity', 0.01)
+        contract_size = self._get_contract_size()
+
         if position['position_type'] == 'long':
-            return (current_price_value - entry_price) / entry_price if entry_price != 0 else 0.0
+            dollar_pnl = (current_price_value - entry_price) * quantity * contract_size
         else:
-            return (entry_price - current_price_value) / entry_price if entry_price != 0 else 0.0
+            dollar_pnl = (entry_price - current_price_value) * quantity * contract_size
+
+        return dollar_pnl / self.total_equity if self.total_equity > 0 else 0.0
 
     def _calculate_unrealized_pnl(self) -> float:
-        """★ 新增：计算所有持仓的浮动盈亏"""
+        """计算所有持仓的浮动盈亏"""
         if not self.positions:
             return 0.0
         current_price_data = self.data_provider.get_current_price(self.symbol)
         if not current_price_data:
             return 0.0
         current_price = current_price_data['last']
-        symbol_info = self.data_provider.get_symbol_info(self.symbol)
+        contract_size = self._get_contract_size()
-        contract_size = (symbol_info['trade_contract_size']
-                         if symbol_info and isinstance(symbol_info, dict)
-                         else 100) if symbol_info else 100
         total = 0.0
         for pos in self.positions:
             if pos['position_type'] == 'long':
@@ -338,10 +361,7 @@ class PositionManager:
         return total
 
     def _record_closed_trade(self, position, close_price, close_reason):
-        symbol_info = self.data_provider.get_symbol_info(position['symbol'])
+        contract_size = self._get_contract_size()
-        contract_size = (symbol_info['trade_contract_size']
-                         if symbol_info and isinstance(symbol_info, dict)
-                         else 100) if symbol_info else 100
         if position['position_type'] == 'long':
             pnl = (close_price - position['entry_price']) * position['quantity'] * contract_size
         else:

optimization_report_20260514_141914.txt

@@ -0,0 +1,75 @@
+优化完成时间: 2026-05-14 14:19:14.534049
+最佳适应度: 169.69
+
+最佳参数:
+  ma_cross_short_window: 13
+  ma_cross_long_window: 17
+  rsi_period: 7
+  rsi_overbought: 73
+  rsi_oversold: 27
+  bollinger_period: 24
+  bollinger_std_dev: 1.9616407387901151
+  macd_fast_ema: 14
+  macd_slow_ema: 24
+  macd_signal_period: 9
+  mean_reversion_period: 30
+  mean_reversion_std_dev: 2.4663422649047333
+  momentum_breakout_period: 50
+  momentum_breakout_momentum_period: 27
+  kdj_period: 12
+  turtle_period: 30
+  wave_ema_short: 3
+  wave_ema_medium: 11
+  wave_ema_long: 46
+  wave_period: 11
+  wave_range_period: 35
+  wave_adx_period: 20
+  wave_momentum_period: 13
+  wave_range_threshold: 0.01
+  wave_adx_threshold: 21
+  daily_breakout_bars_count: 2008
+  buy_threshold: 1.0315663601353515
+  sell_threshold: -2.312867704316165
+  stop_loss_pct: -0.028495655271807224
+  profit_retracement_pct: 0.07523134661548606
+  min_profit_for_trailing: 0.005
+  take_profit_pct: 0.3970073007719148
+  max_holding_minutes: 156
+  min_profit_for_time_exit: 0.006397809476304411
+  weight_MACrossStrategy: 0.32048324544087786
+  weight_RSIStrategy: 1.906009222972592
+  weight_BollingerStrategy: 0.9232444456662969
+  weight_MeanReversionStrategy: 1.1649306516234597
+  weight_MomentumBreakoutStrategy: 0.8769099086178171
+  weight_MACDStrategy: 0.748930985323352
+  weight_KDJStrategy: 1.4647470623067596
+  weight_TurtleStrategy: 1.637931136008917
+  weight_DailyBreakoutStrategy: 1.478598649389487
+  weight_WaveTheoryStrategy: 0.818283180489803
+  market_trend_period: 83
+  market_retracement_tolerance: 0.15567164907853615
+  market_volume_period: 29
+  market_volume_ma_period: 23
+  trend_price_breakout_weight: 0.1504199442999585
+  trend_volume_confirmation_weight: 0.12782205952949638
+  trend_momentum_oscillator_weight: 0.3645053274270841
+  trend_moving_average_weight: 0.4092273363154768
+  trend_strong_threshold: 0.7940886082643032
+  trend_weak_threshold: 0.4565953163045441
+  trend_volume_spike: 2.7329673335105396
+  trend_oversold: 32
+  trend_overbought: 68
+  confidence_high: 0.6813641209473742
+  confidence_medium: 0.6336441706563001
+
+代数统计:
+  代数 1: 最佳=166.40, 平均=33.80
+  代数 2: 最佳=116.73, 平均=50.63
+  代数 3: 最佳=104.87, 平均=55.76
+  代数 4: 最佳=147.56, 平均=74.03
+  代数 5: 最佳=141.85, 平均=57.90
+  代数 6: 最佳=141.85, 平均=70.85
+  代数 7: 最佳=154.87, 平均=85.11
+  代数 8: 最佳=169.69, 平均=94.60
+  代数 9: 最佳=169.69, 平均=99.20
+  代数 10: 最佳=169.69, 平均=112.85