卡尔曼策略新增md文件
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import numpy as np
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import pandas as pd
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from typing import Optional, Dict, Any, List
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# 假设这些是你项目中的模块
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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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from src.algo.TrendLine import calculate_latest_trendline_values_v2
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class DualModeVolumeIntensityStrategy(Strategy):
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"""
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双模式成交量强度策略 (V7 - 无状态高效版):
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- 【核心命名】将 "霍克斯过程" 概念替换为更准确的 "成交量强度 (Volume Intensity)"。
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- 【核心优化】使用 NumPy 的卷积操作 (np.convolve) 代替循环，高效地计算滑动窗口的成交量强度，彻底消除路径依赖，同时保证高性能。
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- 策略行为在任何时间点只与最近的固定窗口数据相关，保证了回测与实盘的绝对一致性。
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- 完整保留了双模式（趋势/回归）和冲突解决机制。
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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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trade_volume: int = 1,
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trend_params: Dict[str, Any] = None,
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reversion_params: Dict[str, Any] = None,
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enabled_modes: Optional[List[str]] = None,
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conflict_resolution: str = 'TREND_PRIORITY',
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enable_log: bool = True,
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):
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super().__init__(context, main_symbol, enable_log)
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self.main_symbol = main_symbol
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self.trade_volume = trade_volume
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default_params = {
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"order_direction": ["BUY", "SELL"],
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"trendline_n": 50,
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# 【命名修改】参数名也同步调整
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"intensity_kappa": 0.1, # 衰减因子
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"intensity_lookback": 50, # 回看窗口
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"intensity_entry_percent": 0.95,
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"intensity_exit_percent": 0.50,
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}
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self.trend_params = default_params.copy()
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if trend_params:
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self.trend_params.update(trend_params)
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self.reversion_params = default_params.copy()
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if reversion_params:
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self.reversion_params.update(reversion_params)
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self.enabled_modes = enabled_modes or ['TREND', 'REVERSION']
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self.conflict_resolution = conflict_resolution
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self.pos_meta: Dict[str, Dict[str, Any]] = {}
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print("DualModeVolumeIntensityStrategy (V7) initialized.")
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print(f"Enabled modes: {self.enabled_modes}")
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print(f"Conflict resolution: {self.conflict_resolution}")
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print("Volume Intensity calculation is STATELESS and EFFICIENT (using np.convolve).")
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# --- 【核心修改】使用卷积实现无状态、高效的窗口计算 ---
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def _calculate_volume_intensity_window(self, volumes: np.ndarray, kappa: float, lookback: int) -> np.ndarray:
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"""
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使用一维卷积高效计算成交量强度窗口。
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这是一个纯函数，无任何副作用和路径依赖。
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:param volumes: 历史成交量序列。长度应为 2*lookback - 1。
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:param kappa: 强度衰减因子。
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:param lookback: 强度计算的回看窗口，也是返回的强度窗口的长度。
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:return: 一个长度为 `lookback` 的成交量强度值窗口。
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"""
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# 权重是指数衰减的，越近的成交量权重越高
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# weights = [exp(-kappa*lookback), ..., exp(-kappa*1)]
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weights = np.exp(-kappa * np.arange(lookback, 0, -1))
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# 使用'valid'模式的卷积，本质上是一个滑动的点积运算
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# 结果的长度将是 len(volumes) - len(weights) + 1 = (2*lookback-1) - lookback + 1 = lookback
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intensity_unscaled = np.convolve(volumes, weights, mode='valid')
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return intensity_unscaled * kappa
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def on_init(self):
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super().on_init()
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self.pos_meta.clear()
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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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# 确保有足够的数据来满足最长的回看需求
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# 趋势线需要 trendline_n + 1 个价格
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# 强度计算需要 2 * lookback - 1 个成交量
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min_bars_required = max(
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self.trend_params['trendline_n'] + 2, 2 * self.trend_params['intensity_lookback'],
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self.reversion_params['trendline_n'] + 2, 2 * self.reversion_params['intensity_lookback']
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)
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if len(bar_history) < min_bars_required:
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return
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all_volumes = np.array([b.volume for b in bar_history], dtype=float)
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# 为每个模式计算其独立的成交量强度窗口
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trend_intensity_window = np.array([], dtype=np.float64)
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if 'TREND' in self.enabled_modes:
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lookback = self.trend_params['intensity_lookback']
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# 截取计算所需的、正确长度的成交量数据
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volumes_slice = all_volumes[-(2 * lookback - 1):]
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trend_intensity_window = self._calculate_volume_intensity_window(
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volumes_slice, self.trend_params['intensity_kappa'], lookback
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)
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reversion_intensity_window = np.array([], dtype=np.float64)
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if 'REVERSION' in self.enabled_modes:
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lookback = self.reversion_params['intensity_lookback']
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volumes_slice = all_volumes[-(2 * lookback - 1):]
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reversion_intensity_window = self._calculate_volume_intensity_window(
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volumes_slice, self.reversion_params['intensity_kappa'], lookback
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)
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self.cancel_all_pending_orders(symbol)
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pos = self.get_current_positions().get(symbol, 0)
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# --- 1. 平仓逻辑 ---
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meta = self.pos_meta.get(symbol)
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if meta and pos != 0:
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strategy_mode = meta.get('strategy_mode')
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params_to_use = self.trend_params if strategy_mode == 'TREND' else self.reversion_params
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window_to_use = trend_intensity_window if strategy_mode == 'TREND' else reversion_intensity_window
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if window_to_use.size > 0:
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latest_intensity_value = window_to_use[-1]
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exit_threshold = np.quantile(window_to_use, params_to_use['intensity_exit_percent'])
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if latest_intensity_value < exit_threshold:
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self.log(f"[{strategy_mode}模式] 成交量强度平仓信号 (市场热度下降)，平仓。")
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self.send_market_order("CLOSE_LONG" if meta['direction'] == "BUY" else "CLOSE_SHORT", abs(pos))
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del self.pos_meta[symbol]
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return
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# --- 2. 开仓逻辑 ---
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if pos == 0:
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trend_signal = self._calculate_entry_signal(
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'TREND', bar_history, self.trend_params, trend_intensity_window
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) if 'TREND' in self.enabled_modes else None
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reversion_signal = self._calculate_entry_signal(
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'REVERSION', bar_history, self.reversion_params, reversion_intensity_window
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) if 'REVERSION' in self.enabled_modes else None
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# ... 冲突解决和下单逻辑保持不变 ...
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final_direction, winning_mode = self.resolve_signals(trend_signal, reversion_signal)
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if final_direction and winning_mode:
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params_to_use = self.trend_params if winning_mode == 'TREND' else self.reversion_params
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if final_direction in params_to_use['order_direction']:
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self.log(f"[{winning_mode}模式] 开仓信号确认: {final_direction}")
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self.send_open_order(final_direction, open_price, self.trade_volume, winning_mode)
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def _calculate_entry_signal(self, mode: str, bar_history: List[Bar], params: Dict, intensity_window: np.ndarray) -> \
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Optional[str]:
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if intensity_window.size == 0:
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return None
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# 1. 成交量强度确认
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latest_intensity_value = intensity_window[-1]
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entry_threshold = np.quantile(intensity_window, params['intensity_entry_percent'])
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intensity_confirmation = latest_intensity_value > entry_threshold
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if not intensity_confirmation:
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return None
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# 2. 趋势线突破事件
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close_prices = np.array([b.close for b in bar_history])
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prices_for_trendline = close_prices[-params['trendline_n'] - 1:-1]
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trend_upper, trend_lower = calculate_latest_trendline_values_v2(prices_for_trendline)
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if trend_upper is not None and trend_lower is not None:
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prev_close = bar_history[-2].close
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last_close = bar_history[-1].close
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upper_break_event = last_close > trend_upper and prev_close < trend_upper
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lower_break_event = last_close < trend_lower and prev_close > trend_lower
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if upper_break_event: return "BUY" if mode == 'TREND' else "SELL"
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if lower_break_event: return "SELL" if mode == 'TREND' else "BUY"
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return None
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def resolve_signals(self, trend_signal: Optional[str], reversion_signal: Optional[str]) -> (Optional[str],
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Optional[str]):
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if trend_signal and reversion_signal:
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self.log(f"信号冲突：趋势模式 ({trend_signal}) vs 回归模式 ({reversion_signal})")
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if self.conflict_resolution == 'TREND_PRIORITY':
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return trend_signal, 'TREND'
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elif self.conflict_resolution == 'REVERSION_PRIORITY':
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return reversion_signal, 'REVERSION'
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else:
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self.log("冲突解决策略为'NONE'，本次不开仓。")
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return None, None
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elif trend_signal:
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return trend_signal, 'TREND'
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elif reversion_signal:
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return reversion_signal, 'REVERSION'
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return None, None
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# send_open_order, send_market_order, on_rollover 等辅助函数保持不变
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# ... (代码与之前版本相同)
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def send_open_order(self, direction: str, entry_price: float, volume: int, strategy_mode: str):
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current_time = self.get_current_time()
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order_id = f"{self.symbol}_{direction}_{current_time.strftime('%Y%m%d%H%M%S')}"
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order_direction = "BUY" if direction == "BUY" else "SELL"
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order = Order(id=order_id, symbol=self.symbol, direction=order_direction, volume=volume, price_type="MARKET",
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submitted_time=current_time, offset="OPEN")
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self.send_order(order)
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self.pos_meta[self.symbol] = {
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"direction": direction,
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"volume": volume,
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"entry_price": entry_price,
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"strategy_mode": strategy_mode
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}
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self.log(f"发送开仓订单 ({strategy_mode}): {direction} {volume}手 @ Market Price (执行价约 {entry_price:.2f})")
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def send_market_order(self, direction: str, volume: int):
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current_time = self.get_current_time()
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order_id = f"{self.symbol}_{direction}_{current_time.strftime('%Y%m%d%H%M%S')}"
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order = Order(id=order_id, symbol=self.symbol, direction=direction, volume=volume, price_type="MARKET",
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submitted_time=current_time, offset="CLOSE")
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self.send_order(order)
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self.log(f"发送平仓订单: {direction} {volume}手 @ Market Price")
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def on_rollover(self, old_symbol: str, new_symbol: str):
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super().on_rollover(old_symbol, new_symbol)
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self.cancel_all_pending_orders(new_symbol)
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self.pos_meta.clear()
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