160 lines
6.1 KiB
Python
160 lines
6.1 KiB
Python
import numpy as np
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import talib
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from typing import Optional, Any, List, Dict
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from src.core_data import Bar, Order
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from src.strategies.base_strategy import Strategy
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class KalmanMeanReversion(Strategy):
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"""
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改进版卡尔曼均值回归策略
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1. 以 Slow Line 为止盈目标 (真正的均值回归)
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2. 严格的 ATR 止损 (防止趋势爆发)
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3. 时间衰减退出机制
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4. 趋势斜率过滤
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"""
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def __init__(
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self,
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context: Any,
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main_symbol: str,
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enable_log: bool,
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trade_volume: int,
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fast_sensitivity: float = 0.05, # 快线灵敏度
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slow_sensitivity: float = 0.01, # 慢线灵敏度 (更平滑作为均值)
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lookback_variance: int = 60,
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atr_period: int = 20,
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entry_threshold: float = 1.2, # 偏离多少个ATR入场
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stop_loss_multiplier: float = 2.0, # 止损倍数
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max_hold_bars: int = 30, # 最大持仓时间
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indicator: Any = None,
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):
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super().__init__(context, main_symbol, enable_log)
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self.trade_volume = trade_volume
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self.fast_sensitivity = fast_sensitivity
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self.slow_sensitivity = slow_sensitivity
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self.lookback_variance = lookback_variance
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self.atr_period = atr_period
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self.entry_threshold = entry_threshold
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self.stop_loss_multiplier = stop_loss_multiplier
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self.max_hold_bars = max_hold_bars
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self.indicator = indicator
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# 状态变量
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self.kf_fast = {'x': 0.0, 'P': 1.0}
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self.kf_slow = {'x': 0.0, 'P': 1.0}
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self.kalman_initialized = False
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# 记录持仓信息
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self.entry_price = 0.0
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self.entry_bar_count = 0
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self.order_id_counter = 0
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def _update_kalman(self, state: dict, measurement: float, Q: float, R: float) -> float:
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"""递归卡尔曼滤波更新"""
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p_minus = state['P'] + Q
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k_gain = p_minus / (p_minus + R)
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state['x'] = state['x'] + k_gain * (measurement - state['x'])
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state['P'] = (1 - k_gain) * p_minus
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return state['x']
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def on_open_bar(self, open_price: float, symbol: str):
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bar_history = self.get_bar_history()
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if len(bar_history) < 100:
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return
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self.cancel_all_pending_orders()
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closes = np.array([b.close for b in bar_history], dtype=float)
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last_price = closes[-1]
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# 1. 计算自适应噪声 (基于滚动方差)
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rolling_var = np.var(closes[-self.lookback_variance:])
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r_base = rolling_var if rolling_var > 0 else 1.0
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# 2. 初始化或更新卡尔曼滤波器
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if not self.kalman_initialized:
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self.kf_fast['x'] = self.kf_slow['x'] = last_price
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self.kalman_initialized = True
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return
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# 快线追踪价格，慢线代表平衡位置
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fast_line = self._update_kalman(self.kf_fast, last_price, r_base * self.fast_sensitivity, r_base)
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slow_line = self._update_kalman(self.kf_slow, last_price, r_base * self.slow_sensitivity, r_base * 10.0)
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# 3. 计算 ATR 和 偏离度
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highs = np.array([b.high for b in bar_history], dtype=float)
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lows = np.array([b.low for b in bar_history], dtype=float)
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atr = talib.ATR(highs, lows, closes, self.atr_period)[-1]
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if atr <= 0: return
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# 计算价格偏离慢线的程度 (Z-Score 的变体)
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diff_in_atr = (last_price - slow_line) / atr
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# 4. 仓位逻辑
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pos = self.get_current_positions().get(symbol, 0)
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if pos == 0:
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# --- 入场逻辑 ---
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# 只有在外部指标允许且偏离度足够大时入场
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can_trade = self.indicator is None or self.indicator.is_condition_met(*self.get_indicator_tuple())
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if can_trade:
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if diff_in_atr > self.entry_threshold:
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# 超买，做空
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self.execute_order(symbol, "SELL", "OPEN", last_price)
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elif diff_in_atr < -self.entry_threshold:
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# 超卖，做多
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self.execute_order(symbol, "BUY", "OPEN", last_price)
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else:
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# --- 出场逻辑 ---
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self.entry_bar_count += 1
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is_long = pos > 0
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should_close = False
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exit_reason = ""
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# A. 均值回归止盈：触碰或穿过慢线
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if is_long and last_price >= slow_line:
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should_close = True
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exit_reason = "Take Profit: Reached Mean"
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elif not is_long and last_price <= slow_line:
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should_close = True
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exit_reason = "Take Profit: Reached Mean"
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# B. 严谨止损：背离程度进一步扩大
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elif is_long and last_price < self.entry_price - self.stop_loss_multiplier * atr:
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should_close = True
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exit_reason = "Stop Loss: Deviation Too Large"
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elif not is_long and last_price > self.entry_price + self.stop_loss_multiplier * atr:
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should_close = True
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exit_reason = "Stop Loss: Deviation Too Large"
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# C. 时间退出：久攻不下，由于均值回归的时效性，超时即走
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elif self.entry_bar_count >= self.max_hold_bars:
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should_close = True
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exit_reason = "Time Exit: Holding Too Long"
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if should_close:
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direction = "CLOSE_LONG" if is_long else "CLOSE_SHORT"
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self.log(f"EXIT {direction}: Price={last_price}, Reason={exit_reason}")
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self.execute_order(symbol, direction, "CLOSE", last_price)
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def execute_order(self, symbol, direction, offset, price):
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"""执行订单并更新状态"""
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if offset == "OPEN":
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self.entry_price = price
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self.entry_bar_count = 0
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order_id = f"{symbol}_{direction}_{self.order_id_counter}"
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self.order_id_counter += 1
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order = Order(
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id=order_id,
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symbol=symbol,
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direction=direction,
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volume=self.trade_volume,
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price_type="MARKET",
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offset=offset
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)
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self.send_order(order) |