1、vp策略
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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, Union
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import talib
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from src.core_data import Bar, Order
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from src.indicators.base_indicators import Indicator
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from src.indicators.indicators import Empty
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from src.strategies.base_strategy import Strategy
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from src.algo.TrendLine import calculate_latest_trendline_values
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class _SignalGenerator:
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"""
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内部帮助类，用于封装单个策略（趋势或回归）的霍克斯过程信号生成所需的所有状态和逻辑。
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"""
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def __init__(self, hawkes_kappa: float, hawkes_lookback: int, volume_norm_n: int):
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self.hawkes_kappa = hawkes_kappa
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self.hawkes_lookback = hawkes_lookback
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self.volume_norm_n = volume_norm_n
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# 状态变量
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self._last_hawkes_unscaled: float = 0.0
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self._hawkes_window: np.ndarray = np.array([], dtype=np.float64)
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self._hawkes_alpha: float = np.exp(-self.hawkes_kappa)
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self._volume_window: np.ndarray = np.zeros(self.volume_norm_n, dtype=np.float64)
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self._volume_sum: float = 0.0
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self._volume_sum_sq: float = 0.0
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self._volume_pointer: int = 0
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self._is_volume_window_full: bool = False
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def reset(self):
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"""重置所有状态"""
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self._last_hawkes_unscaled = 0.0
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self._hawkes_window = np.array([], dtype=np.float64)
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self._volume_window.fill(0)
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self._volume_sum = 0.0
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self._volume_sum_sq = 0.0
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self._volume_pointer = 0
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self._is_volume_window_full = False
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def initialize_state(self, initial_volumes: np.ndarray):
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"""用历史数据批量初始化状态"""
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normalized_volumes = []
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for vol in initial_volumes:
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self._update_volume_stats_incrementally(vol)
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mean, std = self._get_current_volume_stats()
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z_score = 0.0 if std <= 1e-9 else (vol - mean) / std
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normalized_volumes.append(z_score)
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temp_hawkes_history = np.zeros_like(normalized_volumes, dtype=np.float64)
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if len(normalized_volumes) > 0:
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temp_hawkes_history[0] = normalized_volumes[0]
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for i in range(1, len(normalized_volumes)):
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temp_hawkes_history[i] = temp_hawkes_history[i - 1] * self._hawkes_alpha + normalized_volumes[i]
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self._last_hawkes_unscaled = temp_hawkes_history[-1] if len(temp_hawkes_history) > 0 else 0.0
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self._hawkes_window = (temp_hawkes_history * self.hawkes_kappa)[-self.hawkes_lookback:]
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def update_state_incrementally(self, latest_volume: float):
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"""在每个bar上增量更新状态"""
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self._update_volume_stats_incrementally(latest_volume)
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mean, std = self._get_current_volume_stats()
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normalized_volume = 0.0 if std <= 1e-9 else (latest_volume - mean) / std
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new_hawkes_unscaled = self._last_hawkes_unscaled * self._hawkes_alpha + normalized_volume
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self._last_hawkes_unscaled = new_hawkes_unscaled
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new_hawkes_scaled = new_hawkes_unscaled * self.hawkes_kappa
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if self._hawkes_window.size < self.hawkes_lookback:
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self._hawkes_window = np.append(self._hawkes_window, new_hawkes_scaled)
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else:
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self._hawkes_window = np.roll(self._hawkes_window, -1)
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self._hawkes_window[-1] = new_hawkes_scaled
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def _update_volume_stats_incrementally(self, latest_volume: float):
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oldest_volume = self._volume_window[self._volume_pointer]
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self._volume_sum += latest_volume - oldest_volume
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self._volume_sum_sq += latest_volume ** 2 - oldest_volume ** 2
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self._volume_window[self._volume_pointer] = latest_volume
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self._volume_pointer = (self._volume_pointer + 1) % self.volume_norm_n
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if not self._is_volume_window_full and self._volume_pointer == 0:
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self._is_volume_window_full = True
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def _get_current_volume_stats(self) -> (float, float):
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n = self.volume_norm_n if self._is_volume_window_full else self._volume_pointer
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if n == 0: return 0.0, 0.0
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mean = self._volume_sum / n
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variance = max(0, (self._volume_sum_sq / n) - mean ** 2)
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std = np.sqrt(variance)
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return mean, std
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def get_latest_hawkes_value(self) -> Optional[float]:
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return self._hawkes_window[-1] if self._hawkes_window.size > 0 else None
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def get_hawkes_quantile(self, percentile: float) -> Optional[float]:
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return np.quantile(self._hawkes_window, percentile) if self._hawkes_window.size > 0 else None
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class DualModeTrendlineHawkesStrategy(Strategy):
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"""
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趋势线与霍克斯过程双重确认策略 (V11 - 完全独立信号版):
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- 为趋势(Trend)和均值回归(Reversion)策略分别维护一套完全独立的信号生成器。
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- 每个策略使用各自的 trendline_n, hawkes_kappa, hawkes_lookback, volume_norm_n 参数。
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- 信号生成完全分离，确保逻辑独立性。
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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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trend_enabled: bool = True,
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reversion_enabled: bool = True,
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conflict_resolution_mode: str = 'trend_priority',
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trend_params: Dict[str, Any] = None,
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reversion_params: Dict[str, Any] = None,
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enable_log: bool = True,
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indicators: Union[Indicator, List[Indicator]] = None,
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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.trend_enabled = trend_enabled
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self.reversion_enabled = reversion_enabled
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if conflict_resolution_mode not in ['trend_priority', 'reversion_priority', 'none']:
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raise ValueError("conflict_resolution_mode 必须是 'trend_priority', 'reversion_priority', 或 'none'")
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self.conflict_resolution_mode = conflict_resolution_mode
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default_params = {
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"trade_volume": 1,
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"order_direction": ["BUY", "SELL"],
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"hawkes_entry_percent": 0.95,
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"hawkes_exit_percent": 0.50,
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"enable_atr_stop_loss": True,
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"atr_period": 14,
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"atr_multiplier": 2.0,
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"trendline_n": 50,
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"hawkes_kappa": 0.1,
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"hawkes_lookback": 50,
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"volume_norm_n": 50,
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}
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self.trend_params = default_params.copy()
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if trend_params: self.trend_params.update(trend_params)
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self.reversion_params = default_params.copy()
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if reversion_params: self.reversion_params.update(reversion_params)
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# --- 【核心修改】创建两个独立的信号生成器实例 ---
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self.trend_generator = _SignalGenerator(
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hawkes_kappa=self.trend_params['hawkes_kappa'],
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hawkes_lookback=self.trend_params['hawkes_lookback'],
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volume_norm_n=self.trend_params['volume_norm_n']
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)
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self.reversion_generator = _SignalGenerator(
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hawkes_kappa=self.reversion_params['hawkes_kappa'],
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hawkes_lookback=self.reversion_params['hawkes_lookback'],
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volume_norm_n=self.reversion_params['volume_norm_n']
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)
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self.pos_meta: Dict[str, Dict[str, Any]] = {}
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self.indicators = indicators or [Empty(), Empty()]
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self._is_initialized = False
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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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self.trend_generator.reset()
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self.reversion_generator.reset()
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self._is_initialized = False
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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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min_bars_required = max(
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self.trend_params['trendline_n'] + 2, self.reversion_params['trendline_n'] + 2,
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self.trend_params['hawkes_lookback'] + 2, self.reversion_params['hawkes_lookback'] + 2,
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self.trend_params['volume_norm_n'] + 2, self.reversion_params['volume_norm_n'] + 2,
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self.trend_params['atr_period'] + 2, self.reversion_params['atr_period'] + 2
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)
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if len(bar_history) < min_bars_required:
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return
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latest_volume = float(bar_history[-1].volume)
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# --- 【核心修改】初始化或更新两个独立的生成器 ---
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if not self._is_initialized:
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initial_volumes = np.array([b.volume for b in bar_history[:-1]], dtype=float)
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self.log("首次运行，正在初始化趋势信号生成器...")
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self.trend_generator.initialize_state(initial_volumes)
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self.log("正在初始化回归信号生成器...")
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self.reversion_generator.initialize_state(initial_volumes)
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self._is_initialized = True
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self.trend_generator.update_state_incrementally(latest_volume)
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self.reversion_generator.update_state_incrementally(latest_volume)
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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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# --- 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_type = meta.get('strategy_type', 'trend')
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# 根据开仓类型选择正确的参数和生成器
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params, generator = (self.trend_params, self.trend_generator) if strategy_type == 'trend' \
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else (self.reversion_params, self.reversion_generator)
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latest_hawkes_value = generator.get_latest_hawkes_value()
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latest_hawkes_lower = generator.get_hawkes_quantile(params['hawkes_exit_percent'])
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close_reason = None
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if latest_hawkes_value is not None and latest_hawkes_lower is not None and latest_hawkes_value < latest_hawkes_lower:
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close_reason = f"[{strategy_type.upper()}] 霍克斯出场信号(强度: {latest_hawkes_value:.4f} < 阈值: {latest_hawkes_lower:.4f})"
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if params['enable_atr_stop_loss'] and 'stop_loss_price' in meta and meta['stop_loss_price'] is not None:
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if (meta['direction'] == "BUY" and bar_history[-1].close < meta['stop_loss_price']) or \
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(meta['direction'] == "SELL" and bar_history[-1].close > meta['stop_loss_price']):
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close_reason = f"[{strategy_type.upper()}] ATR止损触发"
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if close_reason:
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self.log(close_reason)
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self.send_market_order("CLOSE_LONG" if meta['direction'] == "BUY" else "CLOSE_SHORT", abs(pos))
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if symbol in self.pos_meta: del self.pos_meta[symbol]
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return
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# --- 开仓逻辑 ---
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if pos == 0:
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trend_signal, reversion_signal = None, None
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close_prices = np.array([b.close for b in bar_history])
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prev_close, last_close = bar_history[-2].close, bar_history[-1].close
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# 1. 检查趋势策略信号
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if self.trend_enabled:
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prices_for_trendline = close_prices[-self.trend_params['trendline_n'] - 1:-1]
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trend_upper, trend_lower = calculate_latest_trendline_values(prices_for_trendline)
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if trend_upper is not None:
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upper_break = last_close > trend_upper and prev_close < trend_upper
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lower_break = last_close < trend_lower and prev_close > trend_lower
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hawkes_val = self.trend_generator.get_latest_hawkes_value()
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hawkes_thresh = self.trend_generator.get_hawkes_quantile(self.trend_params['hawkes_entry_percent'])
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if hawkes_val is not None and hawkes_thresh is not None and hawkes_val > hawkes_thresh and (
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upper_break or lower_break):
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direction = "BUY" if upper_break else "SELL"
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if direction in self.trend_params['order_direction']:
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trend_signal = direction
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# 2. 检查均值回归策略信号
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if self.reversion_enabled:
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prices_for_trendline = close_prices[-self.reversion_params['trendline_n'] - 1:-1]
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trend_upper, trend_lower = calculate_latest_trendline_values(prices_for_trendline)
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if trend_upper is not None:
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upper_break = last_close > trend_upper and prev_close < trend_upper
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lower_break = last_close < trend_lower and prev_close > trend_lower
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hawkes_val = self.reversion_generator.get_latest_hawkes_value()
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hawkes_thresh = self.reversion_generator.get_hawkes_quantile(
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self.reversion_params['hawkes_entry_percent'])
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if hawkes_val is not None and hawkes_thresh is not None and hawkes_val > hawkes_thresh and (
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upper_break or lower_break):
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direction = "SELL" if upper_break else "BUY" # 方向相反
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if direction in self.reversion_params['order_direction']:
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reversion_signal = direction
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# 3. 解决信号冲突和下单
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final_direction, final_params, strategy_type, generator = None, None, None, None
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if trend_signal and not reversion_signal:
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final_direction, final_params, strategy_type, generator = trend_signal, self.trend_params, 'trend', self.trend_generator
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elif not trend_signal and reversion_signal:
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final_direction, final_params, strategy_type, generator = reversion_signal, self.reversion_params, 'reversion', self.reversion_generator
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elif trend_signal and reversion_signal:
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self.log(
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f"开仓信号冲突: 趋势={trend_signal}, 回归={reversion_signal}. 模式: {self.conflict_resolution_mode}")
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if self.conflict_resolution_mode == 'trend_priority':
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final_direction, final_params, strategy_type, generator = trend_signal, self.trend_params, 'trend', self.trend_generator
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elif self.conflict_resolution_mode == 'reversion_priority':
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final_direction, final_params, strategy_type, generator = reversion_signal, self.reversion_params, 'reversion', self.reversion_generator
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if final_direction:
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sl_price = None
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if final_params['enable_atr_stop_loss']:
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atr_val = self._calculate_atr(bar_history[:-1], final_params['atr_period'])
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if atr_val is not None:
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sl_price = open_price - atr_val * final_params[
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'atr_multiplier'] if final_direction == "BUY" else open_price + atr_val * final_params[
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'atr_multiplier']
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self.log(
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f"[{strategy_type.upper()}] 开仓信号确认 (霍克斯强度: {generator.get_latest_hawkes_value():.4f} > 阈值: {generator.get_hawkes_quantile(final_params['hawkes_entry_percent']):.4f})")
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self.send_open_order(final_direction, open_price, final_params['trade_volume'], sl_price, strategy_type)
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# --- 辅助函数 (与之前版本相同) ---
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def _calculate_atr(self, bar_history: List[Bar], period: int) -> Optional[float]:
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# ... (代码不变)
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if len(bar_history) < period + 1: return None
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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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closes = np.array([b.close for b in bar_history], dtype=float)
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atr_values = talib.ATR(highs, lows, closes, timeperiod=period)
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return atr_values[-1] if not np.isnan(atr_values[-1]) else None
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def send_open_order(self, direction: str, entry_price: float, volume: int, stop_loss_price: Optional[float],
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strategy_type: str):
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# ... (代码不变)
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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="BUY" if direction == "BUY" else "SELL", volume=volume,
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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] = {"direction": direction, "volume": volume, "entry_price": entry_price,
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"stop_loss_price": stop_loss_price, "strategy_type": strategy_type}
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self.log(f"[{strategy_type.upper()}] 发送开仓订单: {direction} {volume}手")
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def send_market_order(self, direction: str, volume: int):
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# ... (代码不变)
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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")
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def on_rollover(self, old_symbol: str, new_symbol: str):
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# ... (代码不变)
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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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File diff suppressed because one or more lines are too long
@@ -0,0 +1,284 @@
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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, Union
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import talib # <-- 【新增】导入talib库
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from src.core_data import Bar, Order
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from src.indicators.base_indicators import Indicator
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from src.indicators.indicators import Empty
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from src.strategies.base_strategy import Strategy
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from src.algo.TrendLine import calculate_latest_trendline_values
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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, Union
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import talib
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class TrendlineHawkesStrategy(Strategy):
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"""
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趋势线与霍克斯过程双重确认策略 (V8 - O(1) 滚动统计终极版):
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- 对交易量Z-score的计算进行了极致优化，采用增量方式维护滚动窗口的统计量。
|
||||
- 每次更新均值和标准差的计算复杂度从 O(N) 降为 O(1)。
|
||||
- 这是目前性能最高的实现方式，适用于非常高频的场景。
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
context: Any,
|
||||
main_symbol: str,
|
||||
# --- 所有参数与V7完全相同 ---
|
||||
trade_volume: int = 1,
|
||||
order_direction: Optional[List[str]] = None,
|
||||
reverse_logic: bool = False,
|
||||
trendline_n: int = 50,
|
||||
hawkes_kappa: float = 0.1,
|
||||
hawkes_lookback: int = 50,
|
||||
hawkes_entry_percent: float = 0.95,
|
||||
hawkes_exit_percent: float = 0.25,
|
||||
volume_norm_n: int = 50,
|
||||
enable_atr_stop_loss: bool = True,
|
||||
atr_period: int = 14,
|
||||
atr_multiplier: float = 1.0,
|
||||
enable_log: bool = True,
|
||||
indicators: Union[Indicator, List[Indicator]] = None,
|
||||
):
|
||||
super().__init__(context, main_symbol, enable_log)
|
||||
# --- 参数赋值 (与V7相同) ---
|
||||
# ... (省略) ...
|
||||
self.main_symbol = main_symbol
|
||||
self.trade_volume = trade_volume
|
||||
self.order_direction = order_direction or ["BUY", "SELL"]
|
||||
self.reverse_logic = reverse_logic
|
||||
self.trendline_n = trendline_n
|
||||
self.hawkes_kappa = hawkes_kappa
|
||||
self.hawkes_lookback = hawkes_lookback
|
||||
self.hawkes_entry_percent = hawkes_entry_percent
|
||||
self.hawkes_exit_percent = hawkes_exit_percent
|
||||
self.volume_norm_n = volume_norm_n
|
||||
self.enable_atr_stop_loss = enable_atr_stop_loss
|
||||
self.atr_period = atr_period
|
||||
self.atr_multiplier = atr_multiplier
|
||||
self.pos_meta: Dict[str, Dict[str, Any]] = {}
|
||||
if indicators is None:
|
||||
indicators = [Empty(), Empty()]
|
||||
self.indicators = indicators
|
||||
|
||||
# --- 霍克斯过程状态 (与V7相同) ---
|
||||
self._last_hawkes_unscaled: float = 0.0
|
||||
self._hawkes_window: np.ndarray = np.array([], dtype=np.float64)
|
||||
self._hawkes_alpha = np.exp(-self.hawkes_kappa)
|
||||
|
||||
# --- 【核心修改】O(1) 滚动统计状态 ---
|
||||
# 预分配一个固定长度的数组作为循环缓冲区
|
||||
self._volume_window: np.ndarray = np.zeros(self.volume_norm_n, dtype=np.float64)
|
||||
self._volume_sum: float = 0.0 # 窗口内元素的和
|
||||
self._volume_sum_sq: float = 0.0 # 窗口内元素平方的和
|
||||
self._volume_pointer: int = 0 # 指向窗口中最旧元素的指针
|
||||
self._is_volume_window_full: bool = False # 窗口是否已填满的标志
|
||||
|
||||
def on_init(self):
|
||||
super().on_init()
|
||||
self.pos_meta.clear()
|
||||
# 重置霍克斯状态
|
||||
self._last_hawkes_unscaled = 0.0
|
||||
self._hawkes_window = np.array([], dtype=np.float64)
|
||||
# 【核心修改】重置所有滚动统计状态
|
||||
self._volume_window.fill(0)
|
||||
self._volume_sum = 0.0
|
||||
self._volume_sum_sq = 0.0
|
||||
self._volume_pointer = 0
|
||||
self._is_volume_window_full = False
|
||||
|
||||
# 【核心修改】_initialize_state 和 _update_state_incrementally 被重构
|
||||
def _initialize_state(self, initial_volumes: np.ndarray):
|
||||
"""
|
||||
在策略开始时调用一次，用历史数据填充所有状态。
|
||||
这个函数现在也会以增量方式填充滚动统计量。
|
||||
"""
|
||||
print("首次运行，正在以增量方式初始化所有状态...")
|
||||
|
||||
# 1. 增量填充交易量窗口并计算历史Z-score
|
||||
normalized_volumes = []
|
||||
for vol in initial_volumes:
|
||||
# 调用增量更新函数，该函数会更新窗口、和、平方和
|
||||
self._update_volume_stats_incrementally(vol)
|
||||
# 计算Z-score
|
||||
mean, std = self._get_current_volume_stats()
|
||||
z_score = 0.0
|
||||
if std > 1e-9:
|
||||
z_score = (vol - mean) / std
|
||||
normalized_volumes.append(z_score)
|
||||
|
||||
# 2. 使用标准化的交易量历史来初始化霍克斯过程 (逻辑与V7相同)
|
||||
print("正在基于标准化的交易量初始化霍克斯过程...")
|
||||
alpha = self._hawkes_alpha
|
||||
temp_hawkes_history = np.zeros_like(normalized_volumes, dtype=np.float64)
|
||||
if len(normalized_volumes) > 0:
|
||||
temp_hawkes_history[0] = normalized_volumes[0]
|
||||
for i in range(1, len(normalized_volumes)):
|
||||
temp_hawkes_history[i] = temp_hawkes_history[i - 1] * alpha + normalized_volumes[i]
|
||||
|
||||
# 3. 记录最后的状态
|
||||
self._last_hawkes_unscaled = temp_hawkes_history[-1] if len(temp_hawkes_history) > 0 else 0.0
|
||||
self._hawkes_window = (temp_hawkes_history * self.hawkes_kappa)[-self.hawkes_lookback:]
|
||||
|
||||
print("状态初始化完成。")
|
||||
|
||||
def _update_volume_stats_incrementally(self, latest_volume: float):
|
||||
"""O(1) 增量更新交易量窗口的统计数据"""
|
||||
# 获取即将被替换的最旧的元素
|
||||
oldest_volume = self._volume_window[self._volume_pointer]
|
||||
|
||||
# 更新和与平方和
|
||||
self._volume_sum += latest_volume - oldest_volume
|
||||
self._volume_sum_sq += latest_volume ** 2 - oldest_volume ** 2
|
||||
|
||||
# 在循环缓冲区中替换旧值
|
||||
self._volume_window[self._volume_pointer] = latest_volume
|
||||
|
||||
# 移动指针
|
||||
self._volume_pointer += 1
|
||||
if self._volume_pointer >= self.volume_norm_n:
|
||||
self._volume_pointer = 0
|
||||
self._is_volume_window_full = True # 窗口在指针第一次循环时被填满
|
||||
|
||||
def _get_current_volume_stats(self) -> (float, float):
|
||||
"""O(1) 获取当前的均值和标准差"""
|
||||
# 在窗口未满时，我们按实际元素数量计算
|
||||
n = self.volume_norm_n if self._is_volume_window_full else self._volume_pointer
|
||||
if n == 0:
|
||||
return 0.0, 0.0
|
||||
|
||||
mean = self._volume_sum / n
|
||||
# 为防止浮点误差导致极小的负数，使用 max(0, ...)
|
||||
variance = max(0, (self._volume_sum_sq / n) - mean ** 2)
|
||||
std = np.sqrt(variance)
|
||||
|
||||
return mean, std
|
||||
|
||||
def _update_state_incrementally(self, latest_volume: float):
|
||||
"""【重构】每个Bar上调用的主增量更新函数"""
|
||||
# 1. O(1) 更新交易量统计
|
||||
self._update_volume_stats_incrementally(latest_volume)
|
||||
|
||||
# 2. O(1) 计算最新Z-score
|
||||
mean, std = self._get_current_volume_stats()
|
||||
normalized_volume = 0.0
|
||||
if std > 1e-9:
|
||||
normalized_volume = (latest_volume - mean) / std
|
||||
|
||||
# 3. 更新霍克斯过程 (逻辑与V7相同)
|
||||
new_hawkes_unscaled = self._last_hawkes_unscaled * self._hawkes_alpha + normalized_volume
|
||||
self._last_hawkes_unscaled = new_hawkes_unscaled
|
||||
|
||||
new_hawkes_scaled = new_hawkes_unscaled * self.hawkes_kappa
|
||||
if self._hawkes_window.size < self.hawkes_lookback:
|
||||
self._hawkes_window = np.append(self._hawkes_window, new_hawkes_scaled)
|
||||
else:
|
||||
self._hawkes_window = np.roll(self._hawkes_window, -1)
|
||||
self._hawkes_window[-1] = new_hawkes_scaled
|
||||
|
||||
# on_open_bar 逻辑不变，它只负责调用 _update_state_incrementally
|
||||
def on_open_bar(self, open_price: float, symbol: str):
|
||||
bar_history = self.get_bar_history()
|
||||
min_bars_required = max(self.trendline_n + 2, self.hawkes_lookback + 2, self.volume_norm_n + 2,
|
||||
self.atr_period + 2)
|
||||
if len(bar_history) < min_bars_required:
|
||||
return
|
||||
|
||||
# 状态更新 (调用重构后的函数)
|
||||
if self._hawkes_window.size == 0:
|
||||
initial_volumes = np.array([b.volume for b in bar_history], dtype=float)
|
||||
self._initialize_state(initial_volumes[:-1])
|
||||
|
||||
self._update_state_incrementally(float(bar_history[-1].volume))
|
||||
|
||||
# --- 后续交易逻辑 (与V7完全相同) ---
|
||||
# ... (此处省略，代码与V7的 on_open_bar 后半部分完全一样) ...
|
||||
self.cancel_all_pending_orders(symbol)
|
||||
pos = self.get_current_positions().get(symbol, 0)
|
||||
latest_hawkes_value = self._hawkes_window[-1]
|
||||
latest_hawkes_lower = np.quantile(self._hawkes_window, self.hawkes_exit_percent)
|
||||
meta = self.pos_meta.get(symbol)
|
||||
if meta and pos != 0:
|
||||
close_reason = None
|
||||
if latest_hawkes_value < latest_hawkes_lower:
|
||||
close_reason = f"霍克斯出场信号(强度: {latest_hawkes_value:.4f} < 阈值: {latest_hawkes_lower:.4f})"
|
||||
if self.enable_atr_stop_loss and 'stop_loss_price' in meta and meta['stop_loss_price'] is not None:
|
||||
last_close = bar_history[-1].close
|
||||
stop_loss_price = meta['stop_loss_price']
|
||||
if (meta['direction'] == "BUY" and last_close < stop_loss_price) or \
|
||||
(meta['direction'] == "SELL" and last_close > stop_loss_price):
|
||||
close_reason = f"ATR止损触发(收盘价: {last_close:.2f}, 止损价: {stop_loss_price:.2f})"
|
||||
if close_reason:
|
||||
self.log(close_reason)
|
||||
self.send_market_order("CLOSE_LONG" if meta['direction'] == "BUY" else "CLOSE_SHORT", abs(pos))
|
||||
if symbol in self.pos_meta: del self.pos_meta[symbol]
|
||||
return
|
||||
if pos == 0:
|
||||
latest_hawkes_upper = np.quantile(self._hawkes_window, self.hawkes_entry_percent)
|
||||
close_prices = np.array([b.close for b in bar_history])
|
||||
prices_for_trendline = close_prices[-self.trendline_n - 1:-1]
|
||||
trend_upper, trend_lower = calculate_latest_trendline_values(prices_for_trendline)
|
||||
if trend_upper is not None and trend_lower is not None:
|
||||
prev_close, last_close = bar_history[-2].close, bar_history[-1].close
|
||||
upper_break = last_close > trend_upper and prev_close < trend_upper and self.indicators[0].is_condition_met(*self.get_indicator_tuple())
|
||||
lower_break = last_close < trend_lower and prev_close > trend_lower and self.indicators[1].is_condition_met(*self.get_indicator_tuple())
|
||||
hawkes_confirm = latest_hawkes_value > latest_hawkes_upper
|
||||
if hawkes_confirm and (upper_break or lower_break):
|
||||
direction = "BUY"
|
||||
if upper_break:
|
||||
direction = "SELL" if self.reverse_logic else "BUY"
|
||||
elif lower_break:
|
||||
direction = "BUY" if self.reverse_logic else "SELL"
|
||||
if direction in self.order_direction:
|
||||
sl_price = None
|
||||
if self.enable_atr_stop_loss:
|
||||
atr_val = self._calculate_atr(bar_history[:-1], self.atr_period)
|
||||
if atr_val is not None:
|
||||
sl_price = open_price - atr_val * self.atr_multiplier if direction == "BUY" else open_price + atr_val * self.atr_multiplier
|
||||
self.log(f"ATR({self.atr_period})={atr_val:.4f}, 止损价设置为: {sl_price:.2f}")
|
||||
self.log(
|
||||
f"开仓信号确认(霍克斯强度: {latest_hawkes_value:.4f} > 阈值: {latest_hawkes_upper:.4f})")
|
||||
self.send_open_order(direction, open_price, self.trade_volume, sl_price)
|
||||
|
||||
# ATR计算函数及其他下单函数与V7完全相同
|
||||
def _calculate_atr(self, bar_history: List[Bar], period: int) -> Optional[float]:
|
||||
if len(bar_history) < period + 1: return None
|
||||
highs = np.array([b.high for b in bar_history], dtype=float)
|
||||
lows = np.array([b.low for b in bar_history], dtype=float)
|
||||
closes = np.array([b.close for b in bar_history], dtype=float)
|
||||
atr_values = talib.ATR(highs, lows, closes, timeperiod=period)
|
||||
latest_atr = atr_values[-1]
|
||||
return latest_atr if not np.isnan(latest_atr) else None
|
||||
|
||||
def send_open_order(self, direction: str, entry_price: float, volume: int, stop_loss_price: Optional[float] = None):
|
||||
current_time = self.get_current_time()
|
||||
order_id = f"{self.symbol}_{direction}_{current_time.strftime('%Y%m%d%H%M%S')}"
|
||||
order_direction = "BUY" if direction == "BUY" else "SELL"
|
||||
order = Order(id=order_id, symbol=self.symbol, direction=order_direction, volume=volume, price_type="MARKET",
|
||||
submitted_time=current_time, offset="OPEN")
|
||||
self.send_order(order)
|
||||
|
||||
self.pos_meta[self.symbol] = {
|
||||
"direction": direction,
|
||||
"volume": volume,
|
||||
"entry_price": entry_price,
|
||||
"stop_loss_price": stop_loss_price
|
||||
}
|
||||
self.log(f"发送开仓订单: {direction} {volume}手 @ Market Price (执行价约 {entry_price:.2f})")
|
||||
|
||||
def send_market_order(self, direction: str, volume: int):
|
||||
current_time = self.get_current_time()
|
||||
order_id = f"{self.symbol}_{direction}_{current_time.strftime('%Y%m%d%H%M%S')}"
|
||||
order = Order(id=order_id, symbol=self.symbol, direction=direction, volume=volume, price_type="MARKET",
|
||||
submitted_time=current_time, offset="CLOSE")
|
||||
self.send_order(order)
|
||||
self.log(f"发送平仓订单: {direction} {volume}手 @ Market Price")
|
||||
|
||||
def on_rollover(self, old_symbol: str, new_symbol: str):
|
||||
super().on_rollover(old_symbol, new_symbol)
|
||||
self.cancel_all_pending_orders(new_symbol)
|
||||
self.pos_meta.clear()
|
||||
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
@@ -0,0 +1,169 @@
|
||||
import numpy as np
|
||||
import talib
|
||||
from typing import Optional, Dict, Any, List, Tuple, Union
|
||||
|
||||
from src.algo.TrendLine import calculate_latest_trendline_values
|
||||
# 假设这些是你项目中的基础模块
|
||||
from src.core_data import Bar, Order
|
||||
from src.indicators.base_indicators import Indicator
|
||||
from src.indicators.indicators import Empty
|
||||
from src.strategies.base_strategy import Strategy
|
||||
|
||||
|
||||
class TrendlineBreakoutStrategy(Strategy):
|
||||
"""
|
||||
趋势线突破策略 V3 (优化版):
|
||||
1. 策略逻辑与 V2 相同，但趋势线计算被重构为一个独立的、
|
||||
高性能的辅助方法。
|
||||
2. 该方法只计算最新的趋势线值，避免不必要的数组生成。
|
||||
|
||||
开仓信号:
|
||||
- 做多: 上一根收盘价上穿下趋势线
|
||||
- 做空: 上一根收盘价下穿上趋势线
|
||||
|
||||
平仓逻辑:
|
||||
- 采用 ATR 滑动止损 (Trailing Stop)。
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
context: Any,
|
||||
main_symbol: str,
|
||||
trendline_n: int = 50,
|
||||
trade_volume: int = 1,
|
||||
order_direction: Optional[List[str]] = None,
|
||||
atr_period: int = 14,
|
||||
atr_multiplier: float = 1.0,
|
||||
enable_log: bool = True,
|
||||
indicators: Union[Indicator, List[Indicator]] = None,
|
||||
):
|
||||
super().__init__(context, main_symbol, enable_log)
|
||||
self.main_symbol = main_symbol
|
||||
self.trendline_n = trendline_n
|
||||
self.trade_volume = trade_volume
|
||||
self.order_direction = order_direction or ["BUY", "SELL"]
|
||||
self.atr_period = atr_period
|
||||
self.atr_multiplier = atr_multiplier
|
||||
self.pos_meta: Dict[str, Dict[str, Any]] = {}
|
||||
if indicators is None:
|
||||
indicators = [Empty(), Empty()]
|
||||
self.indicators = indicators
|
||||
|
||||
if self.trendline_n < 3:
|
||||
raise ValueError("trendline_n 必须大于或等于 3")
|
||||
|
||||
log_message = (
|
||||
f"TrendlineBreakoutStrategy (V3 Optimized) 初始化:\n"
|
||||
f"交易标的={self.main_symbol}, 交易量={self.trade_volume}\n"
|
||||
f"趋势线周期={self.trendline_n}, ATR周期={self.atr_period}, ATR倍数={self.atr_multiplier}"
|
||||
)
|
||||
self.log(log_message)
|
||||
|
||||
|
||||
def _calculate_atr(self, bar_history: List[Bar]) -> Optional[float]:
|
||||
# (此函数与上一版本完全相同，保持不变)
|
||||
if len(bar_history) < self.atr_period + 1: return None
|
||||
highs = np.array([b.high for b in bar_history])
|
||||
lows = np.array([b.low for b in bar_history])
|
||||
closes = np.array([b.close for b in bar_history])
|
||||
atr = talib.ATR(highs, lows, closes, timeperiod=self.atr_period)
|
||||
return atr[-1] if not np.isnan(atr[-1]) else None
|
||||
|
||||
def on_init(self):
|
||||
super().on_init()
|
||||
self.pos_meta.clear()
|
||||
|
||||
def on_open_bar(self, open_price: float, symbol: str):
|
||||
bar_history = self.get_bar_history()
|
||||
min_bars_required = self.trendline_n + 2
|
||||
if len(bar_history) < min_bars_required:
|
||||
return
|
||||
|
||||
self.cancel_all_pending_orders(symbol)
|
||||
pos = self.get_current_positions().get(symbol, 0)
|
||||
|
||||
# 1. 优先处理平仓逻辑 (逻辑不变)
|
||||
meta = self.pos_meta.get(symbol)
|
||||
if meta and pos != 0:
|
||||
current_atr = self._calculate_atr(bar_history[:-1])
|
||||
if current_atr:
|
||||
trailing_stop = meta['trailing_stop']
|
||||
direction = meta['direction']
|
||||
last_close = bar_history[-1].close
|
||||
if direction == "BUY":
|
||||
new_stop_level = last_close - current_atr * self.atr_multiplier
|
||||
trailing_stop = max(trailing_stop, new_stop_level)
|
||||
else: # SELL
|
||||
new_stop_level = last_close + current_atr * self.atr_multiplier
|
||||
trailing_stop = min(trailing_stop, new_stop_level)
|
||||
self.pos_meta[symbol]['trailing_stop'] = trailing_stop
|
||||
if (direction == "BUY" and open_price <= trailing_stop) or \
|
||||
(direction == "SELL" and open_price >= trailing_stop):
|
||||
self.log(f"ATR滑动止损触发: 价格 {open_price:.2f} 触及止损位 {trailing_stop:.2f}")
|
||||
self.send_market_order("CLOSE_LONG" if direction == "BUY" else "CLOSE_SHORT", abs(pos))
|
||||
del self.pos_meta[symbol]
|
||||
return
|
||||
|
||||
# 2. 开仓逻辑 (调用优化后的方法)
|
||||
if pos == 0:
|
||||
prices_for_trendline = np.array([b.close for b in bar_history[-self.trendline_n - 1:-1]])
|
||||
|
||||
# --- 调用新的独立方法 ---
|
||||
trendline_val_upper, trendline_val_lower = calculate_latest_trendline_values(prices_for_trendline)
|
||||
|
||||
if trendline_val_upper is None or trendline_val_lower is None:
|
||||
return # 无法计算趋势线，跳过
|
||||
|
||||
prev_close = bar_history[-2].close
|
||||
last_close = bar_history[-1].close
|
||||
|
||||
current_atr = self._calculate_atr(bar_history[:-1])
|
||||
if not current_atr:
|
||||
return
|
||||
|
||||
# if "BUY" in self.order_direction and last_close > trendline_val_upper and self.indicators[0].is_condition_met(*self.get_indicator_tuple()):
|
||||
# self.log(f"做多信号: Close({last_close:.2f}) 上穿下趋势线({trendline_val_upper:.2f})")
|
||||
# self.send_open_order("BUY", open_price, self.trade_volume, current_atr)
|
||||
#
|
||||
# elif "SELL" in self.order_direction and last_close < trendline_val_lower and self.indicators[1].is_condition_met(*self.get_indicator_tuple()):
|
||||
# self.log(f"做空信号: Close({last_close:.2f}) 下穿上趋势线({trendline_val_lower:.2f})")
|
||||
# self.send_open_order("SELL", open_price, self.trade_volume, current_atr)
|
||||
|
||||
if "BUY" in self.order_direction and last_close > trendline_val_upper and self.indicators[0].is_condition_met(*self.get_indicator_tuple()):
|
||||
self.log(f"做多信号: Close({last_close:.2f}) 上穿下趋势线({trendline_val_upper:.2f})")
|
||||
self.send_open_order("BUY", open_price, self.trade_volume, current_atr)
|
||||
|
||||
elif "SELL" in self.order_direction and last_close < trendline_val_lower and self.indicators[1].is_condition_met(*self.get_indicator_tuple()):
|
||||
self.log(f"做空信号: Close({last_close:.2f}) 下穿上趋势线({trendline_val_lower:.2f})")
|
||||
self.send_open_order("SELL", open_price, self.trade_volume, current_atr)
|
||||
|
||||
|
||||
# send_open_order, send_market_order, on_rollover 等方法与上一版本完全相同，保持不变
|
||||
def send_open_order(self, direction: str, entry_price: float, volume: int, current_atr: float):
|
||||
if direction == "BUY":
|
||||
initial_stop = entry_price - current_atr * self.atr_multiplier
|
||||
else:
|
||||
initial_stop = entry_price + current_atr * self.atr_multiplier
|
||||
current_time = self.get_current_time()
|
||||
order_id = f"{self.symbol}_{direction}_{current_time.strftime('%Y%m%d%H%M%S')}"
|
||||
order_direction = "BUY" if direction == "BUY" else "SELL"
|
||||
order = Order(id=order_id, symbol=self.symbol, direction=order_direction, volume=volume, price_type="MARKET",
|
||||
submitted_time=current_time, offset="OPEN")
|
||||
self.send_order(order)
|
||||
self.pos_meta[self.symbol] = {"direction": direction, "volume": volume, "entry_price": entry_price,
|
||||
"trailing_stop": initial_stop}
|
||||
self.log(
|
||||
f"发送开仓订单: {direction} {volume}手 @ Market Price (执行价约 {entry_price:.2f}), 初始ATR止损位: {initial_stop:.2f}")
|
||||
|
||||
def send_market_order(self, direction: str, volume: int):
|
||||
current_time = self.get_current_time()
|
||||
order_id = f"{self.symbol}_{direction}_{current_time.strftime('%Y%m%d%H%M%S')}"
|
||||
order = Order(id=order_id, symbol=self.symbol, direction=direction, volume=volume, price_type="MARKET",
|
||||
submitted_time=current_time, offset="CLOSE")
|
||||
self.send_order(order)
|
||||
self.log(f"发送平仓订单: {direction} {volume}手 @ Market Price")
|
||||
|
||||
def on_rollover(self, old_symbol: str, new_symbol: str):
|
||||
super().on_rollover(old_symbol, new_symbol)
|
||||
self.cancel_all_pending_orders(new_symbol)
|
||||
self.pos_meta.clear()
|
||||
File diff suppressed because it is too large
Load Diff
File diff suppressed because one or more lines are too long
@@ -0,0 +1,178 @@
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
from typing import Optional, Dict, Any, List
|
||||
|
||||
# 假设这些是你项目中的模块
|
||||
from src.core_data import Bar, Order
|
||||
from src.strategies.base_strategy import Strategy
|
||||
from src.algo.TrendLine import calculate_latest_trendline_values
|
||||
from src.algo.HawksProcess import calculate_hawkes_bands
|
||||
|
||||
|
||||
class TrendlineHawkesStrategy(Strategy):
|
||||
"""
|
||||
趋势线与霍克斯过程双重确认策略 (V2 - 支持逻辑反转):
|
||||
|
||||
入场信号 (双重确认):
|
||||
1. 趋势线事件: 收盘价突破上轨(标准模式做多)或下轨(标准模式做空)。
|
||||
2. 霍克斯确认: 同时，成交量霍克斯强度必须高于其近期高位分位数。
|
||||
|
||||
出场逻辑 (基于霍克斯过程):
|
||||
- 当成交量霍克斯强度从高位回落至近期低位分位数以下时，平仓。
|
||||
|
||||
逻辑反转 (`reverse_logic=True`):
|
||||
- 趋势线突破上轨时，开【空】仓。
|
||||
- 趋势线突破下轨时，开【多】仓。
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
context: Any,
|
||||
main_symbol: str,
|
||||
trade_volume: int = 1,
|
||||
order_direction: Optional[List[str]] = None,
|
||||
# --- 新增: 逻辑反转开关 ---
|
||||
reverse_logic: bool = False,
|
||||
# --- 趋势线参数 ---
|
||||
trendline_n: int = 50,
|
||||
# --- 霍克斯过程参数 ---
|
||||
hawkes_kappa: float = 0.1,
|
||||
hawkes_lookback: int = 50,
|
||||
hawkes_entry_percent: float = 0.95,
|
||||
hawkes_exit_percent: float = 0.50,
|
||||
enable_log: bool = True,
|
||||
):
|
||||
super().__init__(context, main_symbol, enable_log)
|
||||
self.main_symbol = main_symbol
|
||||
self.trade_volume = trade_volume
|
||||
self.order_direction = order_direction or ["BUY", "SELL"]
|
||||
|
||||
# --- 新增 ---
|
||||
self.reverse_logic = reverse_logic
|
||||
|
||||
self.trendline_n = trendline_n
|
||||
self.hawkes_kappa = hawkes_kappa
|
||||
self.hawkes_lookback = hawkes_lookback
|
||||
self.hawkes_entry_percent = hawkes_entry_percent
|
||||
self.hawkes_exit_percent = hawkes_exit_percent
|
||||
|
||||
self.pos_meta: Dict[str, Dict[str, Any]] = {}
|
||||
|
||||
if self.trendline_n < 3:
|
||||
raise ValueError("trendline_n 必须大于或等于 3")
|
||||
|
||||
log_message = (
|
||||
f"TrendlineHawkesStrategy 初始化:\n"
|
||||
f"【逻辑模式】: {'反转 (Reversal)' if self.reverse_logic else '标准 (Breakout)'}\n"
|
||||
f"趋势线周期={self.trendline_n}\n"
|
||||
f"霍克斯参数: kappa={self.hawkes_kappa}, lookback={self.hawkes_lookback}, "
|
||||
f"entry_pct={self.hawkes_entry_percent}, exit_pct={self.hawkes_exit_percent}"
|
||||
)
|
||||
self.log(log_message)
|
||||
|
||||
def on_init(self):
|
||||
# (此函数保持不变)
|
||||
super().on_init()
|
||||
self.pos_meta.clear()
|
||||
|
||||
def on_open_bar(self, open_price: float, symbol: str):
|
||||
bar_history = self.get_bar_history()
|
||||
min_bars_required = max(self.trendline_n + 2, self.hawkes_lookback + 2)
|
||||
if len(bar_history) < min_bars_required:
|
||||
return
|
||||
|
||||
self.cancel_all_pending_orders(symbol)
|
||||
pos = self.get_current_positions().get(symbol, 0)
|
||||
|
||||
# --- 数据准备 (与之前相同) ---
|
||||
close_prices = np.array([b.close for b in bar_history])
|
||||
volume_series = pd.Series(
|
||||
[b.volume for b in bar_history],
|
||||
index=pd.to_datetime([b.datetime for b in bar_history])
|
||||
)
|
||||
|
||||
vol_hawkes, hawkes_upper_band, hawkes_lower_band = calculate_hawkes_bands(
|
||||
volume_series, self.hawkes_lookback, self.hawkes_kappa,
|
||||
self.hawkes_entry_percent, self.hawkes_exit_percent
|
||||
)
|
||||
|
||||
latest_hawkes_value = vol_hawkes.iloc[-1]
|
||||
latest_hawkes_upper = hawkes_upper_band.iloc[-1]
|
||||
latest_hawkes_lower = hawkes_lower_band.iloc[-1]
|
||||
|
||||
# 1. 优先处理平仓逻辑 (逻辑保持不变)
|
||||
meta = self.pos_meta.get(symbol)
|
||||
if meta and pos != 0:
|
||||
if latest_hawkes_value < latest_hawkes_lower:
|
||||
self.log(f"霍克斯出场信号: 强度({latest_hawkes_value:.2f}) < 阈值({latest_hawkes_lower:.2f})")
|
||||
self.send_market_order("CLOSE_LONG" if meta['direction'] == "BUY" else "CLOSE_SHORT", abs(pos))
|
||||
del self.pos_meta[symbol]
|
||||
return
|
||||
|
||||
# 2. 开仓逻辑 (加入反转判断)
|
||||
if pos == 0:
|
||||
prices_for_trendline = close_prices[-self.trendline_n - 1:-1]
|
||||
trend_upper, trend_lower = calculate_latest_trendline_values(prices_for_trendline)
|
||||
|
||||
if trend_upper is None or trend_lower is None:
|
||||
return
|
||||
|
||||
prev_close = bar_history[-2].close
|
||||
last_close = bar_history[-1].close
|
||||
|
||||
# --- a) 定义基础的突破【事件】 ---
|
||||
upper_break_event = last_close > trend_upper and prev_close < trend_upper
|
||||
lower_break_event = last_close < trend_lower and prev_close > trend_lower
|
||||
|
||||
# --- b) 定义霍克斯【确认】---
|
||||
hawkes_confirmation = latest_hawkes_value > latest_hawkes_upper
|
||||
|
||||
# 只有当基础事件和霍克斯确认都发生时，才考虑开仓
|
||||
if hawkes_confirmation and (upper_break_event or lower_break_event):
|
||||
|
||||
# --- c) 【核心修改】根据 reverse_logic 决定最终交易方向 ---
|
||||
trade_direction = None
|
||||
|
||||
if upper_break_event: # 价格向上突破上轨
|
||||
# 标准模式：做多 (动量)
|
||||
# 反转模式：做空 (力竭反转)
|
||||
trade_direction = "SELL" if self.reverse_logic else "BUY"
|
||||
|
||||
elif lower_break_event: # 价格向下突破下轨
|
||||
# 标准模式：做空 (动量)
|
||||
# 反转模式：做多 (恐慌探底反转)
|
||||
trade_direction = "BUY" if self.reverse_logic else "SELL"
|
||||
|
||||
# d) 执行交易
|
||||
if trade_direction and trade_direction in self.order_direction:
|
||||
event_type = "向上突破" if upper_break_event else "向下突破"
|
||||
logic_type = "反转" if self.reverse_logic else "标准"
|
||||
self.log(
|
||||
f"{logic_type}模式 {trade_direction} 信号: "
|
||||
f"价格{event_type} & 霍克斯强度({latest_hawkes_value:.2f}) > 阈值({latest_hawkes_upper:.2f})"
|
||||
)
|
||||
self.send_open_order(trade_direction, open_price, self.trade_volume)
|
||||
|
||||
# send_open_order, send_market_order, on_rollover 等方法保持不变
|
||||
def send_open_order(self, direction: str, entry_price: float, volume: int):
|
||||
current_time = self.get_current_time()
|
||||
order_id = f"{self.symbol}_{direction}_{current_time.strftime('%Y%m%d%H%M%S')}"
|
||||
order_direction = "BUY" if direction == "BUY" else "SELL"
|
||||
order = Order(id=order_id, symbol=self.symbol, direction=order_direction, volume=volume, price_type="MARKET",
|
||||
submitted_time=current_time, offset="OPEN")
|
||||
self.send_order(order)
|
||||
self.pos_meta[self.symbol] = {"direction": direction, "volume": volume, "entry_price": entry_price}
|
||||
self.log(f"发送开仓订单: {direction} {volume}手 @ Market Price (执行价约 {entry_price:.2f})")
|
||||
|
||||
def send_market_order(self, direction: str, volume: int):
|
||||
current_time = self.get_current_time()
|
||||
order_id = f"{self.symbol}_{direction}_{current_time.strftime('%Y%m%d%H%M%S')}"
|
||||
order = Order(id=order_id, symbol=self.symbol, direction=direction, volume=volume, price_type="MARKET",
|
||||
submitted_time=current_time, offset="CLOSE")
|
||||
self.send_order(order)
|
||||
self.log(f"发送平仓订单: {direction} {volume}手 @ Market Price")
|
||||
|
||||
def on_rollover(self, old_symbol: str, new_symbol: str):
|
||||
super().on_rollover(old_symbol, new_symbol)
|
||||
self.cancel_all_pending_orders(new_symbol)
|
||||
self.pos_meta.clear()
|
||||
@@ -0,0 +1,194 @@
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
from typing import Optional, Dict, Any, List, Union
|
||||
|
||||
# 假设这些是你项目中的模块
|
||||
from src.core_data import Bar, Order
|
||||
from src.indicators.base_indicators import Indicator
|
||||
from src.indicators.indicators import Empty
|
||||
from src.strategies.base_strategy import Strategy
|
||||
from src.algo.TrendLine import calculate_latest_trendline_values
|
||||
|
||||
|
||||
class TrendlineHawkesStrategy(Strategy):
|
||||
"""
|
||||
趋势线与霍克斯过程双重确认策略 (V4 - 终极性能版):
|
||||
- 霍克斯过程和滚动分位数都实现为高效的有状态增量计算。
|
||||
- 使用固定长度的Numpy数组作为滚动窗口，避免Pandas.rolling的开销和不一致性。
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
context: Any,
|
||||
main_symbol: str,
|
||||
# ... 参数与V3完全相同 ...
|
||||
trade_volume: int = 1,
|
||||
order_direction: Optional[List[str]] = None,
|
||||
reverse_logic: bool = False,
|
||||
trendline_n: int = 50,
|
||||
hawkes_kappa: float = 0.1,
|
||||
hawkes_lookback: int = 50,
|
||||
hawkes_entry_percent: float = 0.95,
|
||||
hawkes_exit_percent: float = 0.50,
|
||||
enable_log: bool = True,
|
||||
indicators: Union[Indicator, List[Indicator]] = None,
|
||||
):
|
||||
super().__init__(context, main_symbol, enable_log)
|
||||
# ... 参数赋值与V3完全相同 ...
|
||||
self.main_symbol = main_symbol
|
||||
self.trade_volume = trade_volume
|
||||
self.order_direction = order_direction or ["BUY", "SELL"]
|
||||
self.reverse_logic = reverse_logic
|
||||
self.trendline_n = trendline_n
|
||||
self.hawkes_kappa = hawkes_kappa
|
||||
self.hawkes_lookback = hawkes_lookback
|
||||
self.hawkes_entry_percent = hawkes_entry_percent
|
||||
self.hawkes_exit_percent = hawkes_exit_percent
|
||||
self.pos_meta: Dict[str, Dict[str, Any]] = {}
|
||||
if indicators is None:
|
||||
indicators = [Empty(), Empty()]
|
||||
self.indicators = indicators
|
||||
|
||||
# --- 【核心修改】状态缓存重构 ---
|
||||
# 只缓存上一个时间点的霍克斯强度值 (未缩放)
|
||||
self._last_hawkes_unscaled: float = 0.0
|
||||
# 只维护一个固定长度的滚动窗口，用于计算分位数
|
||||
self._hawkes_window: np.ndarray = np.array([], dtype=np.float64)
|
||||
# 衰减因子
|
||||
self._hawkes_alpha = np.exp(-self.hawkes_kappa)
|
||||
|
||||
# ... 日志与V3相同 ...
|
||||
|
||||
def _initialize_state(self, initial_volumes: np.ndarray):
|
||||
"""
|
||||
仅在策略开始时调用一次，用于填充初始的滚动窗口。
|
||||
"""
|
||||
print("首次运行，正在初始化霍克斯状态和滚动窗口...")
|
||||
alpha = self._hawkes_alpha
|
||||
kappa = self.hawkes_kappa
|
||||
|
||||
# 完整计算一次历史强度，只为填充窗口
|
||||
temp_hawkes_history = np.zeros_like(initial_volumes, dtype=np.float64)
|
||||
if len(initial_volumes) > 0:
|
||||
temp_hawkes_history[0] = initial_volumes[0] if not np.isnan(initial_volumes[0]) else 0.0
|
||||
for i in range(1, len(initial_volumes)):
|
||||
temp_hawkes_history[i] = temp_hawkes_history[i - 1] * alpha + (
|
||||
initial_volumes[i] if not np.isnan(initial_volumes[i]) else 0.0)
|
||||
|
||||
# 记录最后一个点的强度值，作为下一次增量计算的起点
|
||||
self._last_hawkes_unscaled = temp_hawkes_history[-1] if len(temp_hawkes_history) > 0 else 0.0
|
||||
|
||||
# 用历史强度值的最后 hawkes_lookback 个点来填充滚动窗口
|
||||
self._hawkes_window = (temp_hawkes_history * kappa)[-self.hawkes_lookback:]
|
||||
print("状态初始化完成。")
|
||||
|
||||
def _update_state_incrementally(self, latest_volume: float):
|
||||
"""
|
||||
【增量计算】在每个新的Bar上调用，更新强度值和滚动窗口。
|
||||
"""
|
||||
# 1. 计算最新的霍克斯强度值 (未缩放)
|
||||
new_hawkes_unscaled = self._last_hawkes_unscaled * self._hawkes_alpha + (
|
||||
latest_volume if not np.isnan(latest_volume) else 0.0)
|
||||
|
||||
# 2. 更新上一个点的状态，为下一次计算做准备
|
||||
self._last_hawkes_unscaled = new_hawkes_unscaled
|
||||
|
||||
# 3. 将新的缩放后的强度值推入滚动窗口
|
||||
new_hawkes_scaled = new_hawkes_unscaled * self.hawkes_kappa
|
||||
|
||||
# np.roll 会高效地将数组元素移动，然后我们将新值放在第一个位置
|
||||
# 这比 append + delete 的效率高得多
|
||||
self._hawkes_window = np.roll(self._hawkes_window, -1)
|
||||
self._hawkes_window[-1] = new_hawkes_scaled
|
||||
|
||||
def on_init(self):
|
||||
super().on_init()
|
||||
self.pos_meta.clear()
|
||||
# 重置状态
|
||||
self._last_hawkes_unscaled = 0.0
|
||||
self._hawkes_window = np.array([], dtype=np.float64)
|
||||
|
||||
def on_open_bar(self, open_price: float, symbol: str):
|
||||
bar_history = self.get_bar_history()
|
||||
min_bars_required = max(self.trendline_n + 2, self.hawkes_lookback + 2)
|
||||
if len(bar_history) < min_bars_required:
|
||||
return
|
||||
|
||||
# --- 【核心修改】霍克斯过程的状态更新 ---
|
||||
# 检查是否是第一次运行
|
||||
if self._hawkes_window.size == 0:
|
||||
initial_volumes = np.array([b.volume for b in bar_history], dtype=float)
|
||||
self._initialize_state(initial_volumes[:-1]) # 用到上一根bar为止的数据初始化
|
||||
|
||||
# 增量更新当前bar的状态
|
||||
self._update_state_incrementally(float(bar_history[-1].volume))
|
||||
|
||||
# --- 后续逻辑使用更新后的状态进行计算 ---
|
||||
self.cancel_all_pending_orders(symbol)
|
||||
pos = self.get_current_positions().get(symbol, 0)
|
||||
|
||||
# 【核心修改】直接在固定长度的窗口上计算分位数
|
||||
# 这比pandas.rolling快几个数量级，且结果稳定
|
||||
latest_hawkes_value = self._hawkes_window[-1]
|
||||
latest_hawkes_upper = np.quantile(self._hawkes_window, self.hawkes_entry_percent)
|
||||
latest_hawkes_lower = np.quantile(self._hawkes_window, self.hawkes_exit_percent)
|
||||
|
||||
# 1. 平仓逻辑 (完全不变)
|
||||
meta = self.pos_meta.get(symbol)
|
||||
if meta and pos != 0:
|
||||
if latest_hawkes_value < latest_hawkes_lower:
|
||||
self.log(f"霍克斯出场信号...") # 日志简化
|
||||
self.send_market_order("CLOSE_LONG" if meta['direction'] == "BUY" else "CLOSE_SHORT", abs(pos))
|
||||
del self.pos_meta[symbol]
|
||||
return
|
||||
|
||||
# 2. 开仓逻辑 (完全不变)
|
||||
if pos == 0:
|
||||
close_prices = np.array([b.close for b in bar_history])
|
||||
prices_for_trendline = close_prices[-self.trendline_n - 1:-1]
|
||||
trend_upper, trend_lower = calculate_latest_trendline_values(prices_for_trendline)
|
||||
|
||||
if trend_upper is not None and trend_lower is not None:
|
||||
prev_close = bar_history[-2].close
|
||||
last_close = bar_history[-1].close
|
||||
upper_break_event = last_close > trend_upper and prev_close < trend_upper and self.indicators[0].is_condition_met(*self.get_indicator_tuple())
|
||||
lower_break_event = last_close < trend_lower and prev_close > trend_lower and self.indicators[1].is_condition_met(*self.get_indicator_tuple())
|
||||
hawkes_confirmation = latest_hawkes_value > latest_hawkes_upper
|
||||
|
||||
if hawkes_confirmation and (upper_break_event or lower_break_event):
|
||||
trade_direction = None
|
||||
if upper_break_event:
|
||||
trade_direction = "SELL" if self.reverse_logic else "BUY"
|
||||
elif lower_break_event:
|
||||
trade_direction = "BUY" if self.reverse_logic else "SELL"
|
||||
|
||||
if trade_direction and trade_direction in self.order_direction:
|
||||
self.log(f"开仓信号确认...") # 日志简化
|
||||
self.send_open_order(trade_direction, open_price, self.trade_volume)
|
||||
|
||||
# send_open_order, send_market_order, on_rollover 等方法保持不变
|
||||
# ... (代码省略，与之前版本相同) ...
|
||||
|
||||
# send_open_order, send_market_order, on_rollover 等方法保持不变
|
||||
def send_open_order(self, direction: str, entry_price: float, volume: int):
|
||||
current_time = self.get_current_time()
|
||||
order_id = f"{self.symbol}_{direction}_{current_time.strftime('%Y%m%d%H%M%S')}"
|
||||
order_direction = "BUY" if direction == "BUY" else "SELL"
|
||||
order = Order(id=order_id, symbol=self.symbol, direction=order_direction, volume=volume, price_type="MARKET",
|
||||
submitted_time=current_time, offset="OPEN")
|
||||
self.send_order(order)
|
||||
self.pos_meta[self.symbol] = {"direction": direction, "volume": volume, "entry_price": entry_price}
|
||||
self.log(f"发送开仓订单: {direction} {volume}手 @ Market Price (执行价约 {entry_price:.2f})")
|
||||
|
||||
def send_market_order(self, direction: str, volume: int):
|
||||
current_time = self.get_current_time()
|
||||
order_id = f"{self.symbol}_{direction}_{current_time.strftime('%Y%m%d%H%M%S')}"
|
||||
order = Order(id=order_id, symbol=self.symbol, direction=direction, volume=volume, price_type="MARKET",
|
||||
submitted_time=current_time, offset="CLOSE")
|
||||
self.send_order(order)
|
||||
self.log(f"发送平仓订单: {direction} {volume}手 @ Market Price")
|
||||
|
||||
def on_rollover(self, old_symbol: str, new_symbol: str):
|
||||
super().on_rollover(old_symbol, new_symbol)
|
||||
self.cancel_all_pending_orders(new_symbol)
|
||||
self.pos_meta.clear()
|
||||
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user