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
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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 DualModeTrendlineHawkesStrategy(Strategy):
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"""
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趋势线与霍克斯过程双模式策略 (V5 - 趋势/回归自适应版):
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- 支持两套独立的参数配置，分别对应趋势跟踪和均值回归逻辑。
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- 开平仓条件共享，但交易方向相反。
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- 内置冲突解决机制，用于处理两种模式同时发出开仓信号的情况。
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- 保持了V4版本高效的增量计算特性。
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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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trade_volume: int = 1,
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# 【核心修改】使用字典来配置两种模式
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trend_params: Dict[str, Any] = None,
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reversion_params: Dict[str, Any] = None,
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# 【新增】模式启用开关
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enabled_modes: Optional[List[str]] = None,
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# 【新增】信号冲突解决方案: 'TREND_PRIORITY', 'REVERSION_PRIORITY', '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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# --- 【核心修改】参数结构化 ---
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# 提供默认参数，防止用户未提供
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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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"hawkes_kappa": 0.1,
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"hawkes_lookback": 50,
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"hawkes_entry_percent": 0.95,
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"hawkes_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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# --- 【核心修改】为每个模式维护独立的状态 ---
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# 趋势模式状态
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self._trend_last_hawkes_unscaled: float = 0.0
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self._trend_hawkes_window: np.ndarray = np.array([], dtype=np.float64)
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self._trend_hawkes_alpha = np.exp(-self.trend_params['hawkes_kappa'])
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# 回归模式状态
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self._reversion_last_hawkes_unscaled: float = 0.0
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self._reversion_hawkes_window: np.ndarray = np.array([], dtype=np.float64)
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self._reversion_hawkes_alpha = np.exp(-self.reversion_params['hawkes_kappa'])
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print("DualModeTrendlineHawkesStrategy 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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# --- 辅助函数，用于状态管理 (可复用) ---
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def _initialize_hawkes_state(self, params: Dict, initial_volumes: np.ndarray) -> (float, np.ndarray):
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"""根据给定参数和历史成交量，初始化霍克斯状态。"""
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print(f"Initializing Hawkes state with lookback {params['hawkes_lookback']}...")
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alpha = np.exp(-params['hawkes_kappa'])
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kappa = params['hawkes_kappa']
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temp_hawkes_history = np.zeros_like(initial_volumes, dtype=np.float64)
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if len(initial_volumes) > 0:
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temp_hawkes_history[0] = initial_volumes[0] if not np.isnan(initial_volumes[0]) else 0.0
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for i in range(1, len(initial_volumes)):
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temp_hawkes_history[i] = temp_hawkes_history[i - 1] * alpha + (
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initial_volumes[i] if not np.isnan(initial_volumes[i]) else 0.0)
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last_hawkes_unscaled = temp_hawkes_history[-1] if len(temp_hawkes_history) > 0 else 0.0
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hawkes_window = (temp_hawkes_history * kappa)[-params['hawkes_lookback']:]
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return last_hawkes_unscaled, hawkes_window
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def _update_hawkes_state_incrementally(self, params: Dict, latest_volume: float, last_unscaled: float,
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window: np.ndarray) -> (float, np.ndarray):
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"""根据给定参数，增量更新霍克斯状态。"""
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alpha = np.exp(-params['hawkes_kappa'])
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kappa = params['hawkes_kappa']
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new_hawkes_unscaled = last_unscaled * alpha + (latest_volume if not np.isnan(latest_volume) else 0.0)
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new_hawkes_scaled = new_hawkes_unscaled * kappa
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new_window = np.roll(window, -1)
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new_window[-1] = new_hawkes_scaled
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return new_hawkes_unscaled, new_window
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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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# 重置所有状态
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self._trend_last_hawkes_unscaled = 0.0
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self._trend_hawkes_window = np.array([], dtype=np.float64)
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self._reversion_last_hawkes_unscaled = 0.0
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self._reversion_hawkes_window = np.array([], dtype=np.float64)
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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初始化两个模式
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min_bars_required = max(
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self.trend_params['trendline_n'] + 2, self.trend_params['hawkes_lookback'] + 2,
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self.reversion_params['trendline_n'] + 2, self.reversion_params['hawkes_lookback'] + 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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# --- 状态初始化与更新 ---
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# 首次运行时，为两个启用的模式初始化状态
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if self._trend_hawkes_window.size == 0 and 'TREND' in self.enabled_modes:
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initial_volumes = np.array([b.volume for b in bar_history], dtype=float)
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self._trend_last_hawkes_unscaled, self._trend_hawkes_window = self._initialize_hawkes_state(
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self.trend_params, initial_volumes[:-1]
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)
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if self._reversion_hawkes_window.size == 0 and 'REVERSION' in self.enabled_modes:
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initial_volumes = np.array([b.volume for b in bar_history], dtype=float)
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self._reversion_last_hawkes_unscaled, self._reversion_hawkes_window = self._initialize_hawkes_state(
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self.reversion_params, initial_volumes[:-1]
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)
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# 增量更新两个模式的状态
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latest_volume = float(bar_history[-1].volume)
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if 'TREND' in self.enabled_modes:
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self._trend_last_hawkes_unscaled, self._trend_hawkes_window = self._update_hawkes_state_incrementally(
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self.trend_params, latest_volume, self._trend_last_hawkes_unscaled, self._trend_hawkes_window
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)
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if 'REVERSION' in self.enabled_modes:
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self._reversion_last_hawkes_unscaled, self._reversion_hawkes_window = self._update_hawkes_state_incrementally(
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self.reversion_params, latest_volume, self._reversion_last_hawkes_unscaled,
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self._reversion_hawkes_window
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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 = self._trend_hawkes_window if strategy_mode == 'TREND' else self._reversion_hawkes_window
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if window_to_use.size > 0:
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latest_hawkes_value = window_to_use[-1]
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latest_hawkes_lower = np.quantile(window_to_use, params_to_use['hawkes_exit_percent'])
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if latest_hawkes_value < latest_hawkes_lower:
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self.log(f"[{strategy_mode}模式] 霍克斯出场信号触发，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 = None
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reversion_signal = None
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# 分别计算两个模式的信号
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if 'TREND' in self.enabled_modes:
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trend_signal = self._calculate_entry_signal(
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'TREND', bar_history, self.trend_params, self._trend_hawkes_window
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)
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if 'REVERSION' in self.enabled_modes:
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reversion_signal = self._calculate_entry_signal(
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'REVERSION', bar_history, self.reversion_params, self._reversion_hawkes_window
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)
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final_direction = None
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winning_mode = None
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# --- 信号冲突解决 ---
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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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final_direction = trend_signal
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winning_mode = 'TREND'
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elif self.conflict_resolution == 'REVERSION_PRIORITY':
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final_direction = reversion_signal
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winning_mode = 'REVERSION'
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else: # 'NONE'
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self.log("冲突解决策略为'NONE'，本次不开仓。")
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elif trend_signal:
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final_direction = trend_signal
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winning_mode = 'TREND'
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elif reversion_signal:
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final_direction = reversion_signal
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winning_mode = 'REVERSION'
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# 执行最终决策
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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, hawkes_window: np.ndarray) -> \
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Optional[str]:
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"""计算单个模式的入场信号，返回 'BUY', 'SELL' 或 None。"""
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if hawkes_window.size == 0:
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return None
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# 霍克斯确认
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latest_hawkes_value = hawkes_window[-1]
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latest_hawkes_upper = np.quantile(hawkes_window, params['hawkes_entry_percent'])
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hawkes_confirmation = latest_hawkes_value > latest_hawkes_upper
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if not hawkes_confirmation:
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return None
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# 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:
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# 趋势模式：向上突破 -> 买入
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# 回归模式：向上突破 -> 卖出 (认为是假突破，价格将回归)
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return "BUY" if mode == 'TREND' else "SELL"
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elif lower_break_event:
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# 趋势模式：向下突破 -> 卖出
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# 回归模式：向下突破 -> 买入 (认为是超卖，价格将反弹)
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return "SELL" if mode == 'TREND' else "BUY"
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return None
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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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# 【核心修改】记录仓位属于哪个模式
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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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File diff suppressed because one or more lines are too long
@@ -0,0 +1,169 @@
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import numpy as np
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import talib
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from typing import Optional, Dict, Any, List, Tuple, Union
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from src.algo.TrendLine import calculate_latest_trendline_values
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# 假设这些是你项目中的基础模块
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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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class TrendlineBreakoutStrategy(Strategy):
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"""
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趋势线突破策略 V3 (优化版):
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1. 策略逻辑与 V2 相同，但趋势线计算被重构为一个独立的、
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高性能的辅助方法。
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2. 该方法只计算最新的趋势线值，避免不必要的数组生成。
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开仓信号:
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- 做多: 上一根收盘价上穿下趋势线
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- 做空: 上一根收盘价下穿上趋势线
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平仓逻辑:
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- 采用 ATR 滑动止损 (Trailing Stop)。
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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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trendline_n: int = 50,
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trade_volume: int = 1,
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order_direction: Optional[List[str]] = None,
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atr_period: int = 14,
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atr_multiplier: float = 1.0,
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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.trendline_n = trendline_n
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self.trade_volume = trade_volume
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self.order_direction = order_direction or ["BUY", "SELL"]
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self.atr_period = atr_period
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self.atr_multiplier = atr_multiplier
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self.pos_meta: Dict[str, Dict[str, Any]] = {}
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if indicators is None:
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indicators = [Empty(), Empty()]
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self.indicators = indicators
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if self.trendline_n < 3:
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raise ValueError("trendline_n 必须大于或等于 3")
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log_message = (
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f"TrendlineBreakoutStrategy (V3 Optimized) 初始化:\n"
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f"交易标的={self.main_symbol}, 交易量={self.trade_volume}\n"
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f"趋势线周期={self.trendline_n}, ATR周期={self.atr_period}, ATR倍数={self.atr_multiplier}"
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)
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self.log(log_message)
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def _calculate_atr(self, bar_history: List[Bar]) -> Optional[float]:
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# (此函数与上一版本完全相同，保持不变)
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if len(bar_history) < self.atr_period + 1: return None
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highs = np.array([b.high for b in bar_history])
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lows = np.array([b.low for b in bar_history])
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closes = np.array([b.close for b in bar_history])
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atr = talib.ATR(highs, lows, closes, timeperiod=self.atr_period)
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return atr[-1] if not np.isnan(atr[-1]) else None
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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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min_bars_required = self.trendline_n + 2
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if len(bar_history) < min_bars_required:
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return
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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. 优先处理平仓逻辑 (逻辑不变)
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meta = self.pos_meta.get(symbol)
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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 +1,188 @@
|
||||
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, calculate_latest_trendline_values_v2
|
||||
|
||||
|
||||
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,
|
||||
):
|
||||
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]] = {}
|
||||
|
||||
# --- 【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_v2(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
|
||||
lower_break_event = last_close < trend_lower and prev_close > trend_lower
|
||||
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
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 +1,188 @@
|
||||
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
|
||||
|
||||
|
||||
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,
|
||||
):
|
||||
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]] = {}
|
||||
|
||||
# --- 【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
|
||||
lower_break_event = last_close < trend_lower and prev_close > trend_lower
|
||||
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
File diff suppressed because one or more lines are too long
@@ -0,0 +1,328 @@
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
from typing import Optional, Dict, Any, List, Union
|
||||
import talib
|
||||
|
||||
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 _SignalGenerator:
|
||||
"""
|
||||
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。
|
||||
"""
|
||||
|
||||
def __init__(self, hawkes_kappa: float, hawkes_lookback: int, volume_norm_n: int):
|
||||
self.hawkes_kappa = hawkes_kappa
|
||||
self.hawkes_lookback = hawkes_lookback
|
||||
self.volume_norm_n = volume_norm_n
|
||||
|
||||
# 状态变量
|
||||
self._last_hawkes_unscaled: float = 0.0
|
||||
self._hawkes_window: np.ndarray = np.array([], dtype=np.float64)
|
||||
self._hawkes_alpha: float = np.exp(-self.hawkes_kappa)
|
||||
self._volume_window: np.ndarray = np.zeros(self.volume_norm_n, dtype=np.float64)
|
||||
self._volume_sum: float = 0.0
|
||||
self._volume_sum_sq: float = 0.0
|
||||
self._volume_pointer: int = 0
|
||||
self._is_volume_window_full: bool = False
|
||||
|
||||
def reset(self):
|
||||
"""重置所有状态"""
|
||||
self._last_hawkes_unscaled = 0.0
|
||||
self._hawkes_window = np.array([], dtype=np.float64)
|
||||
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
|
||||
|
||||
def initialize_state(self, initial_volumes: np.ndarray):
|
||||
"""用历史数据批量初始化状态"""
|
||||
normalized_volumes = []
|
||||
for vol in initial_volumes:
|
||||
self._update_volume_stats_incrementally(vol)
|
||||
mean, std = self._get_current_volume_stats()
|
||||
z_score = 0.0 if std <= 1e-9 else (vol - mean) / std
|
||||
normalized_volumes.append(z_score)
|
||||
|
||||
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] * self._hawkes_alpha + normalized_volumes[i]
|
||||
|
||||
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:]
|
||||
|
||||
def update_state_incrementally(self, latest_volume: float):
|
||||
"""在每个bar上增量更新状态"""
|
||||
self._update_volume_stats_incrementally(latest_volume)
|
||||
mean, std = self._get_current_volume_stats()
|
||||
normalized_volume = 0.0 if std <= 1e-9 else (latest_volume - mean) / std
|
||||
|
||||
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
|
||||
|
||||
def _update_volume_stats_incrementally(self, latest_volume: float):
|
||||
oldest_volume = self._volume_window[self._volume_pointer]
|
||||
self._volume_sum += latest_volume - oldest_volume
|
||||
self._volume_sum_sq += latest_volume ** 2 - oldest_volume ** 2
|
||||
self._volume_window[self._volume_pointer] = latest_volume
|
||||
self._volume_pointer = (self._volume_pointer + 1) % self.volume_norm_n
|
||||
if not self._is_volume_window_full and self._volume_pointer == 0:
|
||||
self._is_volume_window_full = True
|
||||
|
||||
def _get_current_volume_stats(self) -> (float, float):
|
||||
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
|
||||
variance = max(0, (self._volume_sum_sq / n) - mean ** 2)
|
||||
std = np.sqrt(variance)
|
||||
return mean, std
|
||||
|
||||
def get_latest_hawkes_value(self) -> Optional[float]:
|
||||
return self._hawkes_window[-1] if self._hawkes_window.size > 0 else None
|
||||
|
||||
def get_hawkes_quantile(self, percentile: float) -> Optional[float]:
|
||||
return np.quantile(self._hawkes_window, percentile) if self._hawkes_window.size > 0 else None
|
||||
|
||||
|
||||
class DualModeTrendlineHawkesStrategy(Strategy):
|
||||
"""
|
||||
趋势线与霍克斯过程双重确认策略 (V11 - 完全独立信号版):
|
||||
- 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。
|
||||
- 每个策略使用各自的 trendline_n, hawkes_kappa, hawkes_lookback, volume_norm_n 参数。
|
||||
- 信号生成完全分离，确保逻辑独立性。
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
context: Any,
|
||||
main_symbol: str,
|
||||
trend_enabled: bool = True,
|
||||
reversion_enabled: bool = True,
|
||||
conflict_resolution_mode: str = 'trend_priority',
|
||||
trend_params: Dict[str, Any] = None,
|
||||
reversion_params: Dict[str, Any] = None,
|
||||
enable_log: bool = True,
|
||||
indicators: Union[Indicator, List[Indicator]] = None,
|
||||
):
|
||||
super().__init__(context, main_symbol, enable_log)
|
||||
self.main_symbol = main_symbol
|
||||
self.trend_enabled = trend_enabled
|
||||
self.reversion_enabled = reversion_enabled
|
||||
if conflict_resolution_mode not in ['trend_priority', 'reversion_priority', 'none']:
|
||||
raise ValueError("conflict_resolution_mode 必须是 'trend_priority', 'reversion_priority', 或 'none'")
|
||||
self.conflict_resolution_mode = conflict_resolution_mode
|
||||
|
||||
default_params = {
|
||||
"trade_volume": 1,
|
||||
"order_direction": ["BUY", "SELL"],
|
||||
"hawkes_entry_percent": 0.95,
|
||||
"hawkes_exit_percent": 0.50,
|
||||
"enable_atr_stop_loss": True,
|
||||
"atr_period": 14,
|
||||
"atr_multiplier": 2.0,
|
||||
"trendline_n": 50,
|
||||
"hawkes_kappa": 0.1,
|
||||
"hawkes_lookback": 50,
|
||||
"volume_norm_n": 50,
|
||||
}
|
||||
self.trend_params = default_params.copy()
|
||||
if trend_params: self.trend_params.update(trend_params)
|
||||
|
||||
self.reversion_params = default_params.copy()
|
||||
if reversion_params: self.reversion_params.update(reversion_params)
|
||||
|
||||
# --- 【核心修改】创建两个独立的信号生成器实例 ---
|
||||
self.trend_generator = _SignalGenerator(
|
||||
hawkes_kappa=self.trend_params['hawkes_kappa'],
|
||||
hawkes_lookback=self.trend_params['hawkes_lookback'],
|
||||
volume_norm_n=self.trend_params['volume_norm_n']
|
||||
)
|
||||
self.reversion_generator = _SignalGenerator(
|
||||
hawkes_kappa=self.reversion_params['hawkes_kappa'],
|
||||
hawkes_lookback=self.reversion_params['hawkes_lookback'],
|
||||
volume_norm_n=self.reversion_params['volume_norm_n']
|
||||
)
|
||||
|
||||
self.pos_meta: Dict[str, Dict[str, Any]] = {}
|
||||
self.indicators = indicators or [Empty(), Empty()]
|
||||
self._is_initialized = False
|
||||
|
||||
def on_init(self):
|
||||
super().on_init()
|
||||
self.pos_meta.clear()
|
||||
self.trend_generator.reset()
|
||||
self.reversion_generator.reset()
|
||||
self._is_initialized = False
|
||||
|
||||
def on_open_bar(self, open_price: float, symbol: str):
|
||||
bar_history = self.get_bar_history()
|
||||
min_bars_required = max(
|
||||
self.trend_params['trendline_n'] + 2, self.reversion_params['trendline_n'] + 2,
|
||||
self.trend_params['hawkes_lookback'] + 2, self.reversion_params['hawkes_lookback'] + 2,
|
||||
self.trend_params['volume_norm_n'] + 2, self.reversion_params['volume_norm_n'] + 2,
|
||||
self.trend_params['atr_period'] + 2, self.reversion_params['atr_period'] + 2
|
||||
)
|
||||
if len(bar_history) < min_bars_required:
|
||||
return
|
||||
|
||||
latest_volume = float(bar_history[-1].volume)
|
||||
# --- 【核心修改】初始化或更新两个独立的生成器 ---
|
||||
if not self._is_initialized:
|
||||
initial_volumes = np.array([b.volume for b in bar_history[:-1]], dtype=float)
|
||||
self.log("首次运行，正在初始化趋势信号生成器...")
|
||||
self.trend_generator.initialize_state(initial_volumes)
|
||||
self.log("正在初始化回归信号生成器...")
|
||||
self.reversion_generator.initialize_state(initial_volumes)
|
||||
self._is_initialized = True
|
||||
|
||||
self.trend_generator.update_state_incrementally(latest_volume)
|
||||
self.reversion_generator.update_state_incrementally(latest_volume)
|
||||
|
||||
self.cancel_all_pending_orders(symbol)
|
||||
pos = self.get_current_positions().get(symbol, 0)
|
||||
|
||||
# --- 平仓逻辑 ---
|
||||
meta = self.pos_meta.get(symbol)
|
||||
if meta and pos != 0:
|
||||
strategy_type = meta.get('strategy_type', 'trend')
|
||||
# 根据开仓类型选择正确的参数和生成器
|
||||
params, generator = (self.trend_params, self.trend_generator) if strategy_type == 'trend' \
|
||||
else (self.reversion_params, self.reversion_generator)
|
||||
|
||||
latest_hawkes_value = generator.get_latest_hawkes_value()
|
||||
latest_hawkes_lower = generator.get_hawkes_quantile(params['hawkes_exit_percent'])
|
||||
|
||||
close_reason = None
|
||||
if latest_hawkes_value is not None and latest_hawkes_lower is not None and latest_hawkes_value < latest_hawkes_lower:
|
||||
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})"
|
||||
|
||||
if params['enable_atr_stop_loss'] and 'stop_loss_price' in meta and meta['stop_loss_price'] is not None:
|
||||
if (meta['direction'] == "BUY" and bar_history[-1].close < meta['stop_loss_price']) or \
|
||||
(meta['direction'] == "SELL" and bar_history[-1].close > meta['stop_loss_price']):
|
||||
close_reason = f"[{strategy_type.upper()}] ATR止损触发"
|
||||
|
||||
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
|
||||
|
||||
# --- 开仓逻辑 ---
|
||||
if pos == 0:
|
||||
trend_signal, reversion_signal = None, None
|
||||
close_prices = np.array([b.close for b in bar_history])
|
||||
prev_close, last_close = bar_history[-2].close, bar_history[-1].close
|
||||
|
||||
# 1. 检查趋势策略信号
|
||||
if self.trend_enabled:
|
||||
prices_for_trendline = close_prices[-self.trend_params['trendline_n'] - 1:-1]
|
||||
trend_upper, trend_lower = calculate_latest_trendline_values(prices_for_trendline)
|
||||
if trend_upper is not None:
|
||||
upper_break = last_close > trend_upper and prev_close < trend_upper
|
||||
lower_break = last_close < trend_lower and prev_close > trend_lower
|
||||
|
||||
hawkes_val = self.trend_generator.get_latest_hawkes_value()
|
||||
hawkes_thresh = self.trend_generator.get_hawkes_quantile(self.trend_params['hawkes_entry_percent'])
|
||||
|
||||
if hawkes_val is not None and hawkes_thresh is not None and hawkes_val > hawkes_thresh and (
|
||||
upper_break or lower_break):
|
||||
direction = "BUY" if upper_break else "SELL"
|
||||
if direction in self.trend_params['order_direction']:
|
||||
trend_signal = direction
|
||||
|
||||
# 2. 检查均值回归策略信号
|
||||
if self.reversion_enabled:
|
||||
prices_for_trendline = close_prices[-self.reversion_params['trendline_n'] - 1:-1]
|
||||
trend_upper, trend_lower = calculate_latest_trendline_values(prices_for_trendline)
|
||||
if trend_upper is not None:
|
||||
upper_break = last_close > trend_upper and prev_close < trend_upper
|
||||
lower_break = last_close < trend_lower and prev_close > trend_lower
|
||||
|
||||
hawkes_val = self.reversion_generator.get_latest_hawkes_value()
|
||||
hawkes_thresh = self.reversion_generator.get_hawkes_quantile(
|
||||
self.reversion_params['hawkes_entry_percent'])
|
||||
|
||||
if hawkes_val is not None and hawkes_thresh is not None and hawkes_val > hawkes_thresh and (
|
||||
upper_break or lower_break):
|
||||
direction = "SELL" if upper_break else "BUY" # 方向相反
|
||||
if direction in self.reversion_params['order_direction']:
|
||||
reversion_signal = direction
|
||||
|
||||
# 3. 解决信号冲突和下单
|
||||
final_direction, final_params, strategy_type, generator = None, None, None, None
|
||||
if trend_signal and not reversion_signal:
|
||||
final_direction, final_params, strategy_type, generator = trend_signal, self.trend_params, 'trend', self.trend_generator
|
||||
elif not trend_signal and reversion_signal:
|
||||
final_direction, final_params, strategy_type, generator = reversion_signal, self.reversion_params, 'reversion', self.reversion_generator
|
||||
elif trend_signal and reversion_signal:
|
||||
self.log(
|
||||
f"开仓信号冲突: 趋势={trend_signal}, 回归={reversion_signal}. 模式: {self.conflict_resolution_mode}")
|
||||
if self.conflict_resolution_mode == 'trend_priority':
|
||||
final_direction, final_params, strategy_type, generator = trend_signal, self.trend_params, 'trend', self.trend_generator
|
||||
elif self.conflict_resolution_mode == 'reversion_priority':
|
||||
final_direction, final_params, strategy_type, generator = reversion_signal, self.reversion_params, 'reversion', self.reversion_generator
|
||||
|
||||
if final_direction:
|
||||
sl_price = None
|
||||
if final_params['enable_atr_stop_loss']:
|
||||
atr_val = self._calculate_atr(bar_history[:-1], final_params['atr_period'])
|
||||
if atr_val is not None:
|
||||
sl_price = open_price - atr_val * final_params[
|
||||
'atr_multiplier'] if final_direction == "BUY" else open_price + atr_val * final_params[
|
||||
'atr_multiplier']
|
||||
|
||||
self.log(
|
||||
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})")
|
||||
self.send_open_order(final_direction, open_price, final_params['trade_volume'], sl_price, strategy_type)
|
||||
|
||||
# --- 辅助函数 (与之前版本相同) ---
|
||||
def _calculate_atr(self, bar_history: List[Bar], period: int) -> Optional[float]:
|
||||
# ... (代码不变)
|
||||
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)
|
||||
return atr_values[-1] if not np.isnan(atr_values[-1]) else None
|
||||
|
||||
def send_open_order(self, direction: str, entry_price: float, volume: int, stop_loss_price: Optional[float],
|
||||
strategy_type: str):
|
||||
# ... (代码不变)
|
||||
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="BUY" if direction == "BUY" else "SELL", 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, "strategy_type": strategy_type}
|
||||
self.log(f"[{strategy_type.upper()}] 发送开仓订单: {direction} {volume}手")
|
||||
|
||||
def send_market_order(self, direction: str, volume: int):
|
||||
# ... (代码不变)
|
||||
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")
|
||||
|
||||
def on_rollover(self, old_symbol: str, new_symbol: str):
|
||||
# ... (代码不变)
|
||||
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
@@ -0,0 +1,284 @@
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
from typing import Optional, Dict, Any, List, Union
|
||||
import talib # <-- 【新增】导入talib库
|
||||
|
||||
|
||||
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
|
||||
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
from typing import Optional, Dict, Any, List, Union
|
||||
import talib
|
||||
|
||||
|
||||
class TrendlineHawkesStrategy(Strategy):
|
||||
"""
|
||||
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):
|
||||
- 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
File diff suppressed because one or more lines are too long
@@ -0,0 +1,279 @@
|
||||
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_v2
|
||||
|
||||
|
||||
class DualModeTrendlineHawkesStrategy(Strategy):
|
||||
"""
|
||||
趋势线与霍克斯过程双模式策略 (V5 - 趋势/回归自适应版):
|
||||
- 支持两套独立的参数配置，分别对应趋势跟踪和均值回归逻辑。
|
||||
- 开平仓条件共享，但交易方向相反。
|
||||
- 内置冲突解决机制，用于处理两种模式同时发出开仓信号的情况。
|
||||
- 保持了V4版本高效的增量计算特性。
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
context: Any,
|
||||
main_symbol: str,
|
||||
trade_volume: int = 1,
|
||||
# 【核心修改】使用字典来配置两种模式
|
||||
trend_params: Dict[str, Any] = None,
|
||||
reversion_params: Dict[str, Any] = None,
|
||||
# 【新增】模式启用开关
|
||||
enabled_modes: Optional[List[str]] = None,
|
||||
# 【新增】信号冲突解决方案: 'TREND_PRIORITY', 'REVERSION_PRIORITY', 'NONE'
|
||||
conflict_resolution: str = 'TREND_PRIORITY',
|
||||
enable_log: bool = True,
|
||||
):
|
||||
super().__init__(context, main_symbol, enable_log)
|
||||
self.main_symbol = main_symbol
|
||||
self.trade_volume = trade_volume
|
||||
|
||||
# --- 【核心修改】参数结构化 ---
|
||||
# 提供默认参数，防止用户未提供
|
||||
default_params = {
|
||||
"order_direction": ["BUY", "SELL"],
|
||||
"trendline_n": 50,
|
||||
"hawkes_kappa": 0.1,
|
||||
"hawkes_lookback": 50,
|
||||
"hawkes_entry_percent": 0.95,
|
||||
"hawkes_exit_percent": 0.50,
|
||||
}
|
||||
self.trend_params = default_params.copy()
|
||||
if trend_params:
|
||||
self.trend_params.update(trend_params)
|
||||
|
||||
self.reversion_params = default_params.copy()
|
||||
if reversion_params:
|
||||
self.reversion_params.update(reversion_params)
|
||||
|
||||
self.enabled_modes = enabled_modes or ['TREND', 'REVERSION']
|
||||
self.conflict_resolution = conflict_resolution
|
||||
|
||||
self.pos_meta: Dict[str, Dict[str, Any]] = {}
|
||||
|
||||
# --- 【核心修改】为每个模式维护独立的状态 ---
|
||||
# 趋势模式状态
|
||||
self._trend_last_hawkes_unscaled: float = 0.0
|
||||
self._trend_hawkes_window: np.ndarray = np.array([], dtype=np.float64)
|
||||
self._trend_hawkes_alpha = np.exp(-self.trend_params['hawkes_kappa'])
|
||||
|
||||
# 回归模式状态
|
||||
self._reversion_last_hawkes_unscaled: float = 0.0
|
||||
self._reversion_hawkes_window: np.ndarray = np.array([], dtype=np.float64)
|
||||
self._reversion_hawkes_alpha = np.exp(-self.reversion_params['hawkes_kappa'])
|
||||
|
||||
print("DualModeTrendlineHawkesStrategy initialized.")
|
||||
print(f"Enabled modes: {self.enabled_modes}")
|
||||
print(f"Conflict resolution: {self.conflict_resolution}")
|
||||
|
||||
# --- 辅助函数，用于状态管理 (可复用) ---
|
||||
def _initialize_hawkes_state(self, params: Dict, initial_volumes: np.ndarray) -> (float, np.ndarray):
|
||||
"""根据给定参数和历史成交量，初始化霍克斯状态。"""
|
||||
print(f"Initializing Hawkes state with lookback {params['hawkes_lookback']}...")
|
||||
alpha = np.exp(-params['hawkes_kappa'])
|
||||
kappa = params['hawkes_kappa']
|
||||
|
||||
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)
|
||||
|
||||
last_hawkes_unscaled = temp_hawkes_history[-1] if len(temp_hawkes_history) > 0 else 0.0
|
||||
hawkes_window = (temp_hawkes_history * kappa)[-params['hawkes_lookback']:]
|
||||
return last_hawkes_unscaled, hawkes_window
|
||||
|
||||
def _update_hawkes_state_incrementally(self, params: Dict, latest_volume: float, last_unscaled: float,
|
||||
window: np.ndarray) -> (float, np.ndarray):
|
||||
"""根据给定参数，增量更新霍克斯状态。"""
|
||||
alpha = np.exp(-params['hawkes_kappa'])
|
||||
kappa = params['hawkes_kappa']
|
||||
|
||||
new_hawkes_unscaled = last_unscaled * alpha + (latest_volume if not np.isnan(latest_volume) else 0.0)
|
||||
new_hawkes_scaled = new_hawkes_unscaled * kappa
|
||||
|
||||
new_window = np.roll(window, -1)
|
||||
new_window[-1] = new_hawkes_scaled
|
||||
|
||||
return new_hawkes_unscaled, new_window
|
||||
|
||||
def on_init(self):
|
||||
super().on_init()
|
||||
self.pos_meta.clear()
|
||||
# 重置所有状态
|
||||
self._trend_last_hawkes_unscaled = 0.0
|
||||
self._trend_hawkes_window = np.array([], dtype=np.float64)
|
||||
self._reversion_last_hawkes_unscaled = 0.0
|
||||
self._reversion_hawkes_window = np.array([], dtype=np.float64)
|
||||
|
||||
def on_open_bar(self, open_price: float, symbol: str):
|
||||
bar_history = self.get_bar_history()
|
||||
|
||||
# 确保有足够的数据来初始化两个模式
|
||||
min_bars_required = max(
|
||||
self.trend_params['trendline_n'] + 2, self.trend_params['hawkes_lookback'] + 2,
|
||||
self.reversion_params['trendline_n'] + 2, self.reversion_params['hawkes_lookback'] + 2
|
||||
)
|
||||
if len(bar_history) < min_bars_required:
|
||||
return
|
||||
|
||||
# --- 状态初始化与更新 ---
|
||||
# 首次运行时，为两个启用的模式初始化状态
|
||||
if self._trend_hawkes_window.size == 0 and 'TREND' in self.enabled_modes:
|
||||
initial_volumes = np.array([b.volume for b in bar_history], dtype=float)
|
||||
self._trend_last_hawkes_unscaled, self._trend_hawkes_window = self._initialize_hawkes_state(
|
||||
self.trend_params, initial_volumes[:-1]
|
||||
)
|
||||
if self._reversion_hawkes_window.size == 0 and 'REVERSION' in self.enabled_modes:
|
||||
initial_volumes = np.array([b.volume for b in bar_history], dtype=float)
|
||||
self._reversion_last_hawkes_unscaled, self._reversion_hawkes_window = self._initialize_hawkes_state(
|
||||
self.reversion_params, initial_volumes[:-1]
|
||||
)
|
||||
|
||||
# 增量更新两个模式的状态
|
||||
latest_volume = float(bar_history[-1].volume)
|
||||
if 'TREND' in self.enabled_modes:
|
||||
self._trend_last_hawkes_unscaled, self._trend_hawkes_window = self._update_hawkes_state_incrementally(
|
||||
self.trend_params, latest_volume, self._trend_last_hawkes_unscaled, self._trend_hawkes_window
|
||||
)
|
||||
if 'REVERSION' in self.enabled_modes:
|
||||
self._reversion_last_hawkes_unscaled, self._reversion_hawkes_window = self._update_hawkes_state_incrementally(
|
||||
self.reversion_params, latest_volume, self._reversion_last_hawkes_unscaled,
|
||||
self._reversion_hawkes_window
|
||||
)
|
||||
|
||||
self.cancel_all_pending_orders(symbol)
|
||||
pos = self.get_current_positions().get(symbol, 0)
|
||||
|
||||
# --- 1. 平仓逻辑 ---
|
||||
meta = self.pos_meta.get(symbol)
|
||||
if meta and pos != 0:
|
||||
strategy_mode = meta.get('strategy_mode')
|
||||
params_to_use = self.trend_params if strategy_mode == 'TREND' else self.reversion_params
|
||||
window_to_use = self._trend_hawkes_window if strategy_mode == 'TREND' else self._reversion_hawkes_window
|
||||
|
||||
if window_to_use.size > 0:
|
||||
latest_hawkes_value = window_to_use[-1]
|
||||
latest_hawkes_lower = np.quantile(window_to_use, params_to_use['hawkes_exit_percent'])
|
||||
|
||||
if latest_hawkes_value < latest_hawkes_lower:
|
||||
self.log(f"[{strategy_mode}模式] 霍克斯出场信号触发，平仓。")
|
||||
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 ---
|
||||
if pos == 0:
|
||||
trend_signal = None
|
||||
reversion_signal = None
|
||||
|
||||
# 分别计算两个模式的信号
|
||||
if 'TREND' in self.enabled_modes:
|
||||
trend_signal = self._calculate_entry_signal(
|
||||
'TREND', bar_history, self.trend_params, self._trend_hawkes_window
|
||||
)
|
||||
if 'REVERSION' in self.enabled_modes:
|
||||
reversion_signal = self._calculate_entry_signal(
|
||||
'REVERSION', bar_history, self.reversion_params, self._reversion_hawkes_window
|
||||
)
|
||||
|
||||
final_direction = None
|
||||
winning_mode = None
|
||||
|
||||
# --- 信号冲突解决 ---
|
||||
if trend_signal and reversion_signal:
|
||||
self.log(f"信号冲突：趋势模式 ({trend_signal}) vs 回归模式 ({reversion_signal})")
|
||||
if self.conflict_resolution == 'TREND_PRIORITY':
|
||||
final_direction = trend_signal
|
||||
winning_mode = 'TREND'
|
||||
elif self.conflict_resolution == 'REVERSION_PRIORITY':
|
||||
final_direction = reversion_signal
|
||||
winning_mode = 'REVERSION'
|
||||
else: # 'NONE'
|
||||
self.log("冲突解决策略为'NONE'，本次不开仓。")
|
||||
elif trend_signal:
|
||||
final_direction = trend_signal
|
||||
winning_mode = 'TREND'
|
||||
elif reversion_signal:
|
||||
final_direction = reversion_signal
|
||||
winning_mode = 'REVERSION'
|
||||
|
||||
# 执行最终决策
|
||||
if final_direction and winning_mode:
|
||||
params_to_use = self.trend_params if winning_mode == 'TREND' else self.reversion_params
|
||||
if final_direction in params_to_use['order_direction']:
|
||||
self.log(f"[{winning_mode}模式] 开仓信号确认: {final_direction}")
|
||||
self.send_open_order(final_direction, open_price, self.trade_volume, winning_mode)
|
||||
|
||||
def _calculate_entry_signal(self, mode: str, bar_history: List[Bar], params: Dict, hawkes_window: np.ndarray) -> \
|
||||
Optional[str]:
|
||||
"""计算单个模式的入场信号，返回 'BUY', 'SELL' 或 None。"""
|
||||
if hawkes_window.size == 0:
|
||||
return None
|
||||
|
||||
# 霍克斯确认
|
||||
latest_hawkes_value = hawkes_window[-1]
|
||||
latest_hawkes_upper = np.quantile(hawkes_window, params['hawkes_entry_percent'])
|
||||
hawkes_confirmation = latest_hawkes_value > latest_hawkes_upper
|
||||
|
||||
if not hawkes_confirmation:
|
||||
return None
|
||||
|
||||
# 趋势线突破事件
|
||||
close_prices = np.array([b.close for b in bar_history])
|
||||
prices_for_trendline = close_prices[-params['trendline_n'] - 1:-1]
|
||||
trend_upper, trend_lower = calculate_latest_trendline_values_v2(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
|
||||
lower_break_event = last_close < trend_lower and prev_close > trend_lower
|
||||
|
||||
if upper_break_event:
|
||||
# 趋势模式：向上突破 -> 买入
|
||||
# 回归模式：向上突破 -> 卖出 (认为是假突破，价格将回归)
|
||||
return "BUY" if mode == 'TREND' else "SELL"
|
||||
elif lower_break_event:
|
||||
# 趋势模式：向下突破 -> 卖出
|
||||
# 回归模式：向下突破 -> 买入 (认为是超卖，价格将反弹)
|
||||
return "SELL" if mode == 'TREND' else "BUY"
|
||||
|
||||
return None
|
||||
|
||||
def send_open_order(self, direction: str, entry_price: float, volume: int, strategy_mode: str):
|
||||
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)
|
||||
# 【核心修改】记录仓位属于哪个模式
|
||||
self.pos_meta[self.symbol] = {
|
||||
"direction": direction,
|
||||
"volume": volume,
|
||||
"entry_price": entry_price,
|
||||
"strategy_mode": strategy_mode
|
||||
}
|
||||
self.log(f"发送开仓订单 ({strategy_mode}): {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
@@ -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 +1,188 @@
|
||||
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, calculate_latest_trendline_values_v2
|
||||
|
||||
|
||||
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,
|
||||
):
|
||||
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]] = {}
|
||||
|
||||
# --- 【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_v2(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
|
||||
lower_break_event = last_close < trend_lower and prev_close > trend_lower
|
||||
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
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 +1,188 @@
|
||||
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
|
||||
|
||||
|
||||
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,
|
||||
):
|
||||
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]] = {}
|
||||
|
||||
# --- 【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
|
||||
lower_break_event = last_close < trend_lower and prev_close > trend_lower
|
||||
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()
|
||||
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Reference in New Issue
Block a user