200 lines
7.7 KiB
Python
200 lines
7.7 KiB
Python
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from typing import Any
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import numpy as np
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import pywt
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from src.core_data import Order
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from src.strategies.base_strategy import Strategy
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# =============================================================================
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# 策略实现 (WaveletDynamicsStrategy - 全新动态分析策略)
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# =============================================================================
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class WaveletSignalNoiseStrategy(Strategy):
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"""
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小波信噪比策略 (最终版)
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核心哲学:
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1. 信任小波: 策略完全基于小波变换最独特的“信号/噪音”分离能力。
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2. 简洁因子: 使用一个核心因子——趋势信噪比(TNR)，衡量趋势的质量。
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3. 可靠逻辑:
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- 当信噪比高（趋势清晰）时入场。
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- 当信噪比低（噪音过大）时出场。
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"""
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def __init__(
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self,
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context: Any,
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main_symbol: str,
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enable_log: bool,
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trade_volume: int,
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# --- 【核心参数】 ---
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bars_per_day: int = 23,
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analysis_window_days: float = 2.0, # 窗口长度适中即可
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wavelet_family: str = 'db4',
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# --- 【信噪比交易阈值】 ---
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tnr_entry_threshold: float = 5, # 入场阈值：信号强度至少是噪音的2倍
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tnr_exit_threshold: float = 5, # 离场阈值：信号强度不再显著高于噪音
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# --- 【持仓管理】 ---
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max_hold_days: int = 10,
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):
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super().__init__(context, main_symbol, enable_log)
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# ... (参数赋值) ...
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self.bars_per_day = bars_per_day
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self.analysis_window_days = analysis_window_days
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self.wavelet = wavelet_family
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self.tnr_entry_threshold = tnr_entry_threshold
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self.tnr_exit_threshold = tnr_exit_threshold
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self.trade_volume = trade_volume
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self.max_hold_days = max_hold_days
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self.analysis_window = int(self.analysis_window_days * self.bars_per_day)
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self.decomposition_level = pywt.dwt_max_level(self.analysis_window, self.wavelet)
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self.entry_time = None
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self.order_id_counter = 0
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self.log("WaveletSignalNoiseStrategy Initialized.")
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def calculate_trend_noise_ratio(self, prices: np.array) -> (float, np.array):
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"""
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【最终核心】计算趋势信噪比(TNR)和内在趋势线
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返回: (tnr_factor, trend_signal)
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"""
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if len(prices) < self.analysis_window:
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return 0.0, None
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window_data = prices[-self.analysis_window:]
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try:
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coeffs = pywt.wavedec(window_data, self.wavelet, level=self.decomposition_level)
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# 1. 重构内在趋势信号 (Signal)
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trend_coeffs = [coeffs[0]] + [np.zeros_like(d) for d in coeffs[1:]]
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trend_signal = pywt.waverec(trend_coeffs, self.wavelet)
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trend_signal = trend_signal[:len(window_data)]
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# 2. 重构噪音信号 (Noise)
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noise_coeffs = [np.zeros_like(coeffs[0])] + coeffs[1:]
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noise_signal = pywt.waverec(noise_coeffs, self.wavelet)
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noise_signal = noise_signal[:len(window_data)]
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# 3. 计算各自的强度 (标准差)
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strength_trend = np.std(trend_signal)
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strength_noise = np.std(noise_signal)
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# 4. 计算信噪比因子
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if strength_noise < 1e-9: # 避免除以零
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tnr_factor = np.inf
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else:
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tnr_factor = strength_trend / strength_noise
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return tnr_factor, trend_signal
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except Exception as e:
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self.log(f"TNR calculation error: {e}", "ERROR")
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return 0.0, None
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def on_open_bar(self, open_price: float, symbol: str):
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self.symbol = symbol
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bar_history = self.get_bar_history()
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position_volume = self.get_current_positions().get(self.symbol, 0)
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self.cancel_all_pending_orders(self.main_symbol)
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if len(bar_history) < self.analysis_window:
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return
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closes = np.array([b.close for b in bar_history], dtype=float)
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tnr_factor, trend_signal = self.calculate_trend_noise_ratio(closes)
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if trend_signal is None: return
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if position_volume == 0:
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self.evaluate_entry_signal(open_price, tnr_factor, trend_signal)
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else:
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self.manage_open_position(position_volume, tnr_factor)
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def evaluate_entry_signal(self, open_price: float, tnr_factor: float, trend_signal: np.array):
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"""入场逻辑：信噪比达标 + 方向确认"""
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if tnr_factor < self.tnr_entry_threshold:
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return
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direction = None
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# 方向判断：内在趋势线的斜率
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# if len(trend_signal) < 5: return
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if trend_signal[-1] > trend_signal[-5]:
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direction = "SELL"
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elif trend_signal[-1] < trend_signal[-5]:
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direction = "BUY"
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if direction:
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self.log(f"Entry Signal: {direction} | Trend-Noise Ratio={tnr_factor:.2f}")
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self.entry_time = self.get_current_time()
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self.send_limit_order(direction, open_price, self.trade_volume, "OPEN")
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def manage_open_position(self, volume: int, tnr_factor: float):
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"""出场逻辑：信噪比低于退出阈值"""
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if tnr_factor < self.tnr_exit_threshold:
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direction_str = "CLOSE_LONG" if volume > 0 else "CLOSE_SHORT"
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self.log(f"Exit Signal: TNR ({tnr_factor:.2f}) < Threshold ({self.tnr_exit_threshold})")
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self.close_position(direction_str, abs(volume))
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self.entry_time = None
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# --- 辅助函数区 (与之前版本相同) ---
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# (此处省略，以保持简洁)
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# --- 辅助函数区 (与之前版本相同) ---
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# --- 辅助函数区 ---
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def close_all_positions(self):
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"""强制平仓所有头寸"""
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positions = self.get_current_positions()
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if self.symbol in positions and positions[self.symbol] != 0:
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direction = "CLOSE_LONG" if positions[self.symbol] > 0 else "CLOSE_SHORT"
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self.close_position(direction, abs(positions[self.symbol]))
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self.log(f"Forced exit of {abs(positions[self.symbol])} contracts")
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def close_position(self, direction: str, volume: int):
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self.send_market_order(direction, volume, offset="CLOSE")
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def send_market_order(self, direction: str, volume: int, offset: str):
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order_id = f"{self.symbol}_{direction}_MARKET_{self.order_id_counter}"
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self.order_id_counter += 1
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order = Order(
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id=order_id,
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symbol=self.symbol,
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direction=direction,
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volume=volume,
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price_type="MARKET",
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submitted_time=self.get_current_time(),
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offset=offset
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)
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self.send_order(order)
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def send_limit_order(self, direction: str, limit_price: float, volume: int, offset: str):
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order_id = f"{self.symbol}_{direction}_MARKET_{self.order_id_counter}"
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self.order_id_counter += 1
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order = Order(
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id=order_id,
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symbol=self.symbol,
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direction=direction,
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volume=volume,
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price_type="LIMIT",
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submitted_time=self.get_current_time(),
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offset=offset,
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limit_price=limit_price
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)
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self.send_order(order)
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def on_init(self):
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super().on_init()
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self.cancel_all_pending_orders(self.main_symbol)
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self.log("Strategy initialized. Waiting for phase transition signals...")
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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.log(f"Rollover from {old_symbol} to {new_symbol}. Resetting position state.")
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self.entry_time = None
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self.position_direction = None
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self.last_trend_strength = 0.0
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