1、新增傅里叶策略

2、新增策略管理、策略重启功能

futures_trading_strategies/MA/KalmanStrategy/KalmanStrategy3.py

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+import numpy as np
+import talib
+from typing import Optional, Any, List, Dict
+from src.core_data import Bar, Order
+from src.strategies.base_strategy import Strategy
+
+
+class TVDZScoreStrategy(Strategy):
+    """
+    内嵌 TVD (Condat 算法) + Z-Score ATR 的趋势突破策略。
+    无任何外部依赖（如 pytv），纯 NumPy 实现。
+    """
+
+    def __init__(
+        self,
+        context: Any,
+        main_symbol: str,
+        enable_log: bool,
+        trade_volume: int,
+        tvd_lam: float = 50.0,
+        atr_window: int = 14,
+        z_window: int = 100,
+        vol_threshold: float = -0.5,
+        entry_threshold_atr: float = 3.0,
+        stop_atr_multiplier: float = 3.0,
+        order_direction: Optional[List[str]] = None,
+    ):
+        super().__init__(context, main_symbol, enable_log)
+        self.trade_volume = trade_volume
+        self.order_direction = order_direction or ["BUY", "SELL"]
+        self.tvd_lam = tvd_lam
+        self.atr_window = atr_window
+        self.z_window = z_window
+        self.vol_threshold = vol_threshold
+        self.entry_threshold_atr = entry_threshold_atr
+        self.stop_atr_multiplier = stop_atr_multiplier
+
+        self.position_meta: Dict[str, Any] = self.context.load_state()
+        self.main_symbol = main_symbol
+        self.order_id_counter = 0
+
+        self.log(f"TVDZScoreStrategy Initialized | λ={tvd_lam}, VolThresh={vol_threshold}")
+
+    @staticmethod
+    def _tvd_condat(y, lam):
+        """Condat's O(N) TVD algorithm."""
+        n = y.size
+        if n == 0:
+            return y.copy()
+        x = y.astype(np.float64)
+        k = 0
+        k0 = 0
+        vmin = x[0] - lam
+        vmax = x[0] + lam
+        for i in range(1, n):
+            if x[i] < vmin:
+                while k < i:
+                    x[k] = vmin
+                    k += 1
+                k0 = i
+                vmin = x[i] - lam
+                vmax = x[i] + lam
+            elif x[i] > vmax:
+                while k < i:
+                    x[k] = vmax
+                    k += 1
+                k0 = i
+                vmin = x[i] - lam
+                vmax = x[i] + lam
+            else:
+                vmin = max(vmin, x[i] - lam)
+                vmax = min(vmax, x[i] + lam)
+                if vmin > vmax:
+                    k = k0
+                    s = np.sum(x[k0:i+1])
+                    s /= (i - k0 + 1)
+                    x[k0:i+1] = s
+                    k = i + 1
+                    k0 = k
+                    if k0 < n:
+                        vmin = x[k0] - lam
+                        vmax = x[k0] + lam
+        while k < n:
+            x[k] = vmin
+            k += 1
+        return x
+
+    def _compute_zscore_atr_last(self, high, low, close) -> float:
+        n = len(close)
+        min_req = self.atr_window + self.z_window - 1
+        if n < min_req:
+            return np.nan
+        start = max(0, n - (self.z_window + self.atr_window))
+        seg_h, seg_l, seg_c = high[start:], low[start:], close[start:]
+        atr_full = talib.ATR(seg_h, seg_l, seg_c, timeperiod=self.atr_window)
+        atr_valid = atr_full[self.atr_window - 1:]
+        if len(atr_valid) < self.z_window:
+            return np.nan
+        window_atr = atr_valid[-self.z_window:]
+        mu = np.mean(window_atr)
+        sigma = np.std(window_atr)
+        last_atr = window_atr[-1]
+        return (last_atr - mu) / sigma if sigma > 1e-12 else 0.0
+
+    def on_open_bar(self, open_price: float, symbol: str):
+        self.symbol = symbol
+        bar_history = self.get_bar_history()
+        if len(bar_history) < max(100, self.atr_window + self.z_window):
+            return
+
+        closes = np.array([b.close for b in bar_history], dtype=np.float64)
+        highs = np.array([b.high for b in bar_history], dtype=np.float64)
+        lows = np.array([b.low for b in bar_history], dtype=np.float64)
+
+        # === TVD 平滑 ===
+        tvd_prices = self._tvd_condat(closes, self.tvd_lam)
+        tvd_price = tvd_prices[-1]
+
+        # === Z-Score ATR ===
+        current_atr = talib.ATR(highs, lows, closes, timeperiod=self.atr_window)[-1]
+        if current_atr <= 0:
+            return
+
+        deviation = closes[-1] - tvd_price
+        deviation_in_atr = deviation / current_atr
+
+        position_volume = self.get_current_positions().get(self.symbol, 0)
+        if position_volume != 0:
+            self.manage_open_position(position_volume, bar_history[-1], current_atr, tvd_price)
+            return
+
+        direction = None
+        if "BUY" in self.order_direction and deviation_in_atr > self.entry_threshold_atr:
+            direction = "BUY"
+        elif "SELL" in self.order_direction and deviation_in_atr < -self.entry_threshold_atr:
+            direction = "SELL"
+
+        if direction:
+            self.log(f"Signal Fired | Dir: {direction}, Dev: {deviation_in_atr:.2f} ATR")
+            entry_price = closes[-1]
+            stop_loss = (
+                entry_price - self.stop_atr_multiplier * current_atr
+                if direction == "BUY"
+                else entry_price + self.stop_atr_multiplier * current_atr
+            )
+            meta = {"entry_price": entry_price, "stop_loss": stop_loss}
+            self.send_market_order(direction, self.trade_volume, "OPEN", meta)
+            self.save_state(self.position_meta)
+
+    def manage_open_position(self, volume: int, current_bar: Bar, current_atr: float, tvd_price: float):
+        meta = self.position_meta.get(self.symbol)
+        if not meta:
+            return
+        stop_loss = meta["stop_loss"]
+        if (volume > 0 and current_bar.low <= stop_loss) or (volume < 0 and current_bar.high >= stop_loss):
+            self.log(f"Stop Loss Hit at {stop_loss:.4f}")
+            self.close_position("CLOSE_LONG" if volume > 0 else "CLOSE_SHORT", abs(volume))
+
+    def close_position(self, direction: str, volume: int):
+        self.send_market_order(direction, volume, offset="CLOSE")
+        if self.symbol in self.position_meta:
+            del self.position_meta[self.symbol]
+            self.save_state(self.position_meta)
+
+    def send_market_order(self, direction: str, volume: int, offset: str, meta: Optional[Dict] = None):
+        if offset == "OPEN" and meta:
+            self.position_meta[self.symbol] = meta
+        order_id = f"{self.symbol}_{direction}_MARKET_{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 on_rollover(self, old_symbol: str, new_symbol: str):
+        super().on_rollover(old_symbol, new_symbol)
+        self.position_meta = {}
+        self.log("Rollover: Strategy state reset.")