312 lines
12 KiB
Python
312 lines
12 KiB
Python
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import numpy as np
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import talib
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from scipy.signal import stft
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from datetime import timedelta
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from typing import Optional, Any, List
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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 SpectralTrendStrategy(Strategy):
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"""
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频域能量相变策略 - 塔勒布宽幅结构版 (Chandelier Exit)
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修改重点：
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1. 移除 Slope 离场，避免噪音干扰。
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2. 引入状态变量记录持仓期间的极值 (pos_highest/pos_lowest)。
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3. 实施“吊灯止损”：以持仓期间极值为锚点，回撤 N * ATR 离场。
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4. 止损系数建议：4.0 - 6.0 (给予极大的呼吸空间，仅防范趋势崩溃)。
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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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# --- 市场参数 ---
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bars_per_day: int = 23,
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# --- STFT 策略参数 ---
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spectral_window_days: float = 2.0,
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low_freq_days: float = 2.0,
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high_freq_days: float = 1.0,
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trend_strength_threshold: float = 0.2, # 入场能量阈值
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exit_threshold: float = 0.1, # 自然能量衰竭离场阈值
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slope_threshold: float = 0.0, # 仅用于判断方向，不用于离场
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# --- 关键风控参数 (Chandelier Exit) ---
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stop_loss_atr_multiplier: float = 5.0, # 塔勒布式宽止损，建议 4.0 ~ 6.0
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stop_loss_atr_period: int = 14,
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# --- 其他 ---
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order_direction: Optional[List[str]] = None,
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indicators: Indicator = None,
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model_indicator: Indicator = None,
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reverse: bool = False,
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):
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super().__init__(context, main_symbol, enable_log)
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if order_direction is None:
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order_direction = ['BUY', 'SELL']
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self.trade_volume = trade_volume
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self.bars_per_day = bars_per_day
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# 信号参数
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self.spectral_window_days = spectral_window_days
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self.low_freq_days = low_freq_days
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self.high_freq_days = high_freq_days
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self.trend_strength_threshold = trend_strength_threshold
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self.exit_threshold = exit_threshold
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self.slope_threshold = slope_threshold
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# 风控参数
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self.sl_atr_multiplier = stop_loss_atr_multiplier
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self.sl_atr_period = stop_loss_atr_period
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self.order_direction = order_direction
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self.model_indicator = model_indicator or Empty()
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self.indicators = indicators or Empty()
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self.reverse = reverse
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# 计算 STFT 窗口大小
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self.spectral_window = int(self.spectral_window_days * self.bars_per_day)
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if self.spectral_window % 2 != 0:
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self.spectral_window += 1
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self.low_freq_bound = 1.0 / self.low_freq_days if self.low_freq_days > 0 else float('inf')
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self.high_freq_bound = 1.0 / self.high_freq_days if self.high_freq_days > 0 else 0.0
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self.order_id_counter = 0
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# --- 持仓状态追踪变量 ---
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self.entry_price = 0.0
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self.pos_highest = 0.0 # 持有多单期间的最高价
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self.pos_lowest = 0.0 # 持有空单期间的最低价
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self.log(
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f"SpectralTrend Strategy Initialized. Window: {self.spectral_window}, "
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f"Chandelier Stop: {self.sl_atr_multiplier}x ATR"
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)
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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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self.cancel_all_pending_orders(self.main_symbol)
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# 1. 数据长度检查
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required_len = max(self.spectral_window, self.sl_atr_period + 5)
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if len(bar_history) < required_len:
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return
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# 2. 计算 ATR (用于止损)
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atr_window = self.sl_atr_period + 10
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highs = np.array([b.high for b in bar_history[-atr_window:]], dtype=float)
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lows = np.array([b.low for b in bar_history[-atr_window:]], dtype=float)
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closes = np.array([b.close for b in bar_history[-atr_window:]], dtype=float)
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try:
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atr_values = talib.ATR(highs, lows, closes, timeperiod=self.sl_atr_period)
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current_atr = atr_values[-1]
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if np.isnan(current_atr): current_atr = 0.0
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except Exception as e:
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self.log(f"ATR Calc Error: {e}")
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current_atr = 0.0
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# 3. 计算 STFT 核心指标
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stft_closes = np.array([b.close for b in bar_history[-self.spectral_window:]], dtype=float)
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trend_strength, trend_slope = self.calculate_market_state(stft_closes)
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# 4. 交易逻辑
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position_volume = self.get_current_positions().get(self.symbol, 0)
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# 获取当前Bar的最高/最低价用于更新极值（如果使用Bar内更新，更加灵敏）
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# 这里为了稳健，使用上一根Bar的High/Low来更新，或者使用开盘价近似
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current_high = bar_history[-1].high
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current_low = bar_history[-1].low
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if self.trading:
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if position_volume == 0:
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# 重置状态
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self.pos_highest = 0.0
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self.pos_lowest = 0.0
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self.entry_price = 0.0
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self.evaluate_entry_signal(open_price, trend_strength, trend_slope)
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else:
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# 传入 current_high/low 用于更新追踪止损的锚点
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self.manage_open_position(
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position_volume,
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trend_strength,
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open_price,
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current_atr,
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current_high,
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current_low
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)
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def calculate_market_state(self, prices: np.array) -> (float, float):
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"""
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计算频域能量占比和线性回归斜率(仅用于方向)
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"""
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if len(prices) < self.spectral_window:
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return 0.0, 0.0
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# 标准化处理，消除绝对价格影响
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window_data = prices[-self.spectral_window:]
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mean_val = np.mean(window_data)
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std_val = np.std(window_data)
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if std_val == 0: std_val = 1.0
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normalized = (window_data - mean_val) / (std_val + 1e-8)
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# STFT 计算
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try:
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f, t, Zxx = stft(
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normalized,
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fs=self.bars_per_day,
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nperseg=self.spectral_window,
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noverlap=max(0, self.spectral_window // 2),
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boundary=None,
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padded=False
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)
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except Exception:
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return 0.0, 0.0
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# 提取有效频率
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valid_mask = (f >= 0) & (f <= self.bars_per_day / 2)
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f = f[valid_mask]
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Zxx = Zxx[valid_mask, :]
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if Zxx.size == 0: return 0.0, 0.0
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# 计算能量
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current_energy = np.abs(Zxx[:, -1]) ** 2
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low_mask = f < self.low_freq_bound
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high_mask = f > self.high_freq_bound
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low_energy = np.sum(current_energy[low_mask]) if np.any(low_mask) else 0.0
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high_energy = np.sum(current_energy[high_mask]) if np.any(high_mask) else 0.0
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total_energy = low_energy + high_energy + 1e-8
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trend_strength = low_energy / total_energy
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# 计算简单线性斜率用于判断方向
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x = np.arange(len(normalized))
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slope, _ = np.polyfit(x, normalized, 1)
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return trend_strength, slope
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def evaluate_entry_signal(self, open_price: float, trend_strength: float, trend_slope: float):
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"""
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入场逻辑：高低频能量比 > 阈值 + 斜率确认方向
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"""
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# 必须有足够的趋势强度
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if trend_strength > self.trend_strength_threshold:
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direction = None
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# 仅使用 slope 的正负号和基本阈值来决定方向，不作为离场依据
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if "BUY" in self.order_direction and trend_slope > self.slope_threshold:
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direction = "BUY"
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elif "SELL" in self.order_direction and trend_slope < -self.slope_threshold:
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direction = "SELL"
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if direction:
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# 外部过滤条件
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if not self.indicators.is_condition_met(*self.get_indicator_tuple()):
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return
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if not self.model_indicator.is_condition_met(*self.get_indicator_tuple()):
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direction = "SELL" if direction == "BUY" else "BUY"
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if self.reverse:
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direction = "SELL" if direction == "BUY" else "BUY"
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self.log(f"Entry: {direction} | Strength={trend_strength:.2f} | DirSlope={trend_slope:.4f}")
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self.send_limit_order(direction, open_price, self.trade_volume, "OPEN")
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# 初始化持仓状态
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self.entry_price = open_price
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# 初始极值设为当前价格
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self.pos_highest = open_price
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self.pos_lowest = open_price
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def manage_open_position(self, volume: int, trend_strength: float, current_price: float,
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current_atr: float, high_price: float, low_price: float):
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"""
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离场逻辑核心：
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1. 信号离场：能量自然衰竭 (Trend Strength < Threshold)
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2. 结构离场：Chandelier Exit (吊灯止损) - 宽幅 ATR 追踪
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"""
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exit_dir = "CLOSE_LONG" if volume > 0 else "CLOSE_SHORT"
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# --- 更新持仓期间的极值 ---
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if volume > 0: # 多头
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if high_price > self.pos_highest or self.pos_highest == 0:
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self.pos_highest = high_price
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else: # 空头
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if (low_price < self.pos_lowest or self.pos_lowest == 0) and low_price > 0:
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self.pos_lowest = low_price
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# --- 1. 计算宽幅吊灯止损 (Structural Stop) ---
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is_stop_triggered = False
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stop_line = 0.0
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# 如果 ATR 无效，暂时不触发止损，或者使用百分比兜底（此处略）
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if current_atr > 0:
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stop_distance = current_atr * self.sl_atr_multiplier
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if volume > 0:
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# 多头止损线 = 最高价 - N * ATR
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# 随着价格创新高，止损线不断上移；价格下跌，止损线不变
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stop_line = self.pos_highest - stop_distance
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if current_price <= stop_line:
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is_stop_triggered = True
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self.log(
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f"STOP (Long): Price {current_price} <= Highest {self.pos_highest} - {self.sl_atr_multiplier}xATR")
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else:
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# 空头止损线 = 最低价 + N * ATR
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stop_line = self.pos_lowest + stop_distance
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if current_price >= stop_line:
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is_stop_triggered = True
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self.log(
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f"STOP (Short): Price {current_price} >= Lowest {self.pos_lowest} + {self.sl_atr_multiplier}xATR")
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if is_stop_triggered:
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self.close_position(exit_dir, abs(volume))
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return # 止损优先
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# --- 2. 信号自然离场 (Signal Exit) ---
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# 当 STFT 检测到低频能量消散，说明市场进入混沌或震荡，此时平仓
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# 这是一个 "慢" 离场，通常在趋势走完后
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if trend_strength < self.exit_threshold:
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self.log(f"Exit (Signal): Strength {trend_strength:.2f} < {self.exit_threshold}")
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self.close_position(exit_dir, abs(volume))
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return
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# --- 交易执行辅助函数 ---
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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}_MKT_{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, symbol=self.symbol, direction=direction, volume=volume,
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price_type="MARKET", submitted_time=self.get_current_time(), 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}_LMT_{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, symbol=self.symbol, direction=direction, volume=volume,
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price_type="LIMIT", submitted_time=self.get_current_time(), offset=offset,
|
|||
|
|
limit_price=limit_price
|
|||
|
|
)
|
|||
|
|
self.send_order(order)
|