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
Reference in New Issue
Block a user