SpectralStrategy更新:FG品种

futures_trading_strategies/FG/Spectral/SpectralTrendStrategy3.py

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+import numpy as np
+import talib
+from scipy.signal import stft
+from datetime import datetime, timedelta
+from typing import Optional, Any, List, Dict
+
+from src.core_data import Bar, Order
+from src.indicators.base_indicators import Indicator
+from src.indicators.indicators import Empty, ADX
+from src.strategies.base_strategy import Strategy
+
+
+class SpectralTrendStrategy(Strategy):
+    """
+    频域能量相变策略 - 极简回归版 (动态ATR止损)
+    """
+
+    def __init__(
+            self,
+            context: Any,
+            main_symbol: str,
+            enable_log: bool,
+            trade_volume: int,
+            # --- 市场参数 ---
+            bars_per_day: int = 23,
+            # --- 策略参数 ---
+            spectral_window_days: float = 2.0,
+            low_freq_days: float = 2.0,
+            high_freq_days: float = 1.0,
+            trend_strength_threshold: float = 0.2,
+            exit_threshold: float = 0.1,
+            slope_threshold: float = 0.0,
+            max_hold_days: int = 10,
+            # --- 风控参数 ---
+            stop_loss_atr_multiplier: float = 2.0,  # 止损距离是当前ATR的几倍
+            stop_loss_atr_period: int = 14,  # ATR计算周期
+            # --- 其他 ---
+            order_direction: Optional[List[str]] = None,
+            indicators: Indicator = None,
+            model_indicator: Indicator = None,
+            reverse: bool = False,
+    ):
+        super().__init__(context, main_symbol, enable_log)
+        if order_direction is None:
+            order_direction = ['BUY', 'SELL']
+
+        self.trade_volume = trade_volume
+        self.bars_per_day = bars_per_day
+        self.spectral_window_days = spectral_window_days
+        self.low_freq_days = low_freq_days
+        self.high_freq_days = high_freq_days
+        self.trend_strength_threshold = trend_strength_threshold
+        self.exit_threshold = exit_threshold
+        self.slope_threshold = slope_threshold
+        self.max_hold_days = max_hold_days
+
+        # --- 风控参数 ---
+        self.sl_atr_multiplier = stop_loss_atr_multiplier
+        self.sl_atr_period = stop_loss_atr_period
+        # 注意：移除了 self.stop_loss_price 状态变量，改为实时计算
+
+        self.order_direction = order_direction
+        self.model_indicator = model_indicator or Empty()
+        self.indicators = indicators or Empty()
+        self.reverse = reverse
+
+        # 计算窗口大小
+        self.spectral_window = int(self.spectral_window_days * self.bars_per_day)
+        if self.spectral_window % 2 != 0:
+            self.spectral_window += 1
+
+        self.low_freq_bound = 1.0 / self.low_freq_days if self.low_freq_days > 0 else float('inf')
+        self.high_freq_bound = 1.0 / self.high_freq_days if self.high_freq_days > 0 else 0.0
+
+        self.order_id_counter = 0
+        self.entry_time = None
+        self.position_direction = None
+
+        self.log(
+            f"SpectralTrendStrategy Init. Window: {self.spectral_window}, Dynamic ATR SL: {self.sl_atr_multiplier}x")
+
+    def on_open_bar(self, open_price: float, symbol: str):
+
+        self.symbol = symbol
+        bar_history = self.get_bar_history()
+        current_time = self.get_current_time()
+
+        self.cancel_all_pending_orders(self.main_symbol)
+
+        # 确保数据长度足够计算 STFT 和 ATR
+        required_len = max(self.spectral_window, self.sl_atr_period + 5)
+        if len(bar_history) < required_len:
+            return
+
+        # 强制平仓检查 (时间)
+        # if self.entry_time and (current_time - self.entry_time) >= timedelta(days=self.max_hold_days):
+        #     self.close_all_positions(reason="MaxHoldDays")
+        #     return
+
+        # 获取数据用于 STFT
+        closes = np.array([b.close for b in bar_history[-self.spectral_window:]], dtype=float)
+
+        # --- 计算 ATR (每一根Bar都计算最新的ATR) ---
+        atr_window = self.sl_atr_period + 10
+        highs_atr = np.array([b.high for b in bar_history[-atr_window:]], dtype=float)
+        lows_atr = np.array([b.low for b in bar_history[-atr_window:]], dtype=float)
+        closes_atr = np.array([b.close for b in bar_history[-atr_window:]], dtype=float)
+
+        try:
+            atr_values = talib.ATR(highs_atr, lows_atr, closes_atr, timeperiod=self.sl_atr_period)
+            current_atr = atr_values[-1]
+        except Exception as e:
+            self.log(f"ATR Calculation Error: {e}")
+            current_atr = 0.0
+
+
+
+        # 计算核心指标
+        trend_strength, trend_slope = self.calculate_market_state(closes)
+
+        position_volume = self.get_current_positions().get(self.symbol, 0)
+
+        if self.trading:
+            if position_volume == 0:
+                self.evaluate_entry_signal(open_price, trend_strength, trend_slope)
+            else:
+                # 传入 current_atr 用于动态止损计算
+                self.manage_open_position(position_volume, trend_strength, trend_slope, open_price, current_atr)
+
+    def calculate_market_state(self, prices: np.array) -> (float, float):
+        # ... (此处逻辑保持不变) ...
+        if len(prices) < self.spectral_window:
+            return 0.0, 0.0
+
+        window_data = prices[-self.spectral_window:]
+        normalized = (window_data - np.mean(window_data)) / (np.std(window_data) + 1e-8)
+        normalized = normalized[-self.spectral_window:]
+
+        try:
+            f, t, Zxx = stft(
+                normalized,
+                fs=self.bars_per_day,
+                nperseg=self.spectral_window,
+                noverlap=max(0, self.spectral_window // 2),
+                boundary=None,
+                padded=False
+            )
+        except Exception as e:
+            return 0.0, 0.0
+
+        valid_mask = (f >= 0) & (f <= self.bars_per_day / 2)
+        f = f[valid_mask]
+        Zxx = Zxx[valid_mask, :]
+
+        if Zxx.size == 0 or Zxx.shape[1] == 0:
+            return 0.0, 0.0
+
+        current_energy = np.abs(Zxx[:, -1]) ** 2
+
+        low_freq_mask = f < self.low_freq_bound
+        high_freq_mask = f > self.high_freq_bound
+
+        low_energy = np.sum(current_energy[low_freq_mask]) if np.any(low_freq_mask) else 0.0
+        high_energy = np.sum(current_energy[high_freq_mask]) if np.any(high_freq_mask) else 0.0
+        total_energy = low_energy + high_energy + 1e-8
+
+        trend_strength = low_energy / total_energy
+
+        x = np.arange(len(normalized))
+        slope, intercept = np.polyfit(x, normalized, 1)
+
+        return trend_strength, slope
+
+    def evaluate_entry_signal(self, open_price: float, trend_strength: float, trend_slope: float):
+        """
+        入场逻辑：不再计算止损价，只负责开仓
+        """
+        if trend_strength > self.trend_strength_threshold:
+            direction = None
+
+            if "BUY" in self.order_direction and trend_slope > self.slope_threshold:
+                direction = "BUY"
+            elif "SELL" in self.order_direction and trend_slope < -self.slope_threshold:
+                direction = "SELL"
+
+            if direction:
+                if not self.indicators.is_condition_met(*self.get_indicator_tuple()):
+                    return
+
+                if not self.model_indicator.is_condition_met(*self.get_indicator_tuple()):
+                    direction = "SELL" if direction == "BUY" else "BUY"
+                if self.reverse:
+                    direction = "SELL" if direction == "BUY" else "BUY"
+
+                self.log(f"Signal: {direction} | Strength={trend_strength:.2f} | Slope={trend_slope:.4f}")
+
+                self.send_limit_order(direction, open_price, self.trade_volume, "OPEN")
+                self.entry_time = self.get_current_time()
+                self.position_direction = "LONG" if direction == "BUY" else "SHORT"
+
+    def manage_open_position(self, volume: int, trend_strength: float, trend_slope: float, current_price: float,
+                             current_atr: float):
+        """
+        离场逻辑：实时计算均价止损
+        """
+        # --- 1. 动态ATR止损检查 ---
+        # 获取持仓均价
+        avg_entry_price = self.get_average_position_price(self.symbol)
+
+        # 确保 ATR 和 均价 有效
+        if current_atr > 0 and avg_entry_price > 0:
+            is_stop_loss = False
+            exit_dir = ""
+            stop_price = 0.0
+
+            sl_distance = current_atr * self.sl_atr_multiplier
+
+            # 多头持仓：止损价 = 均价 - N * ATR
+            if volume > 0:
+                stop_price = avg_entry_price - sl_distance
+                if current_price <= stop_price:
+                    is_stop_loss = True
+                    exit_dir = "CLOSE_LONG"
+
+            # 空头持仓：止损价 = 均价 + N * ATR
+            elif volume < 0:
+                stop_price = avg_entry_price + sl_distance
+                if current_price >= stop_price:
+                    is_stop_loss = True
+                    exit_dir = "CLOSE_SHORT"
+
+            if is_stop_loss:
+                self.log(
+                    f"ATR STOP LOSS: {exit_dir} | Current={current_price:.2f} | AvgEntry={avg_entry_price:.2f} | ATR={current_atr:.2f} | StopPrice={stop_price:.2f}")
+                self.close_position(exit_dir, abs(volume))
+                self.entry_time = None
+                self.position_direction = None
+                return  # 止损触发后直接返回
+
+        # --- 2. 信号离场 (原能量逻辑) ---
+        if trend_strength < self.exit_threshold:
+            direction = "CLOSE_LONG" if volume > 0 else "CLOSE_SHORT"
+            self.log(f"Exit (Signal): {direction} | Strength={trend_strength:.2f} < {self.exit_threshold}")
+            self.close_position(direction, abs(volume))
+            self.entry_time = None
+            self.position_direction = None
+
+    # --- 交易辅助 ---
+    def close_all_positions(self, reason=""):
+        positions = self.get_current_positions()
+        if self.symbol in positions and positions[self.symbol] != 0:
+            dir = "CLOSE_LONG" if positions[self.symbol] > 0 else "CLOSE_SHORT"
+            self.log(f"Close All ({reason}): {dir}")
+            self.close_position(dir, abs(positions[self.symbol]))
+            self.entry_time = None
+            self.position_direction = None
+
+    def close_position(self, direction: str, volume: int):
+        self.send_market_order(direction, volume, offset="CLOSE")
+
+    def send_market_order(self, direction: str, volume: int, offset: str):
+        order_id = f"{self.symbol}_{direction}_MKT_{self.order_id_counter}"
+        self.order_id_counter += 1
+        order = Order(
+            id=order_id, symbol=self.symbol, direction=direction, volume=volume,
+            price_type="MARKET", submitted_time=self.get_current_time(), offset=offset
+        )
+        self.send_order(order)
+
+    def send_limit_order(self, direction: str, limit_price: float, volume: int, offset: str):
+        order_id = f"{self.symbol}_{direction}_LMT_{self.order_id_counter}"
+        self.order_id_counter += 1
+        order = Order(
+            id=order_id, symbol=self.symbol, direction=direction, volume=volume,
+            price_type="LIMIT", submitted_time=self.get_current_time(), offset=offset,
+            limit_price=limit_price
+        )
+        self.send_order(order)