242 lines
11 KiB
Python
242 lines
11 KiB
Python
import numpy as np
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import math
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import talib
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from collections import deque
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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.strategies.base_strategy import Strategy
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class PragmaticCyberneticStrategy(Strategy):
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"""
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【务实回归版·控制论策略】(TA-Lib 提速 + 换月支持)
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哲学坚守：
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1. 捍卫原版出场逻辑：坚决使用基于 entry_price 的固定硬止损。脱离成本区后，给予价格无限宽容度，实现长线死拿。
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2. 动能极值止盈：恢复 FB > 1.6 且拐头时的精准落袋为安。
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3. 拒绝画蛇添足：没有任何 _target_state，不堆砌 Trick，底层数据即真理。
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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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min_tick: float = 1.0,
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# --- 核心周期 ---
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trend_period: int = 26,
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fisher_period: int = 20,
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atr_period: int = 23,
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# --- 经过验证的优秀参数 ---
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fisher_exit_level: float = 1.6, # 配合 1.98 修复后的 FB，1.6 是一个非常好的极值止盈点
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fb_entry_threshold: float = 0.1, # 0.1 确保在顺大势的前提下，动能稍有配合即可入场
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# --- 风险控制 ---
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stop_mult: float = 2.0, # 原始的硬止损乘数
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limit_offset_mult: float = 0.,
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order_direction: Optional[List[str]] = None,
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indicator: Indicator = None,
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):
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super().__init__(context, main_symbol, enable_log)
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self.trade_volume = trade_volume
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self.min_tick = min_tick
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self.t_len = trend_period
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self.f_len = fisher_period
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self.atr_len = atr_period
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self.fisher_exit_level = fisher_exit_level
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self.fb_entry_threshold = fb_entry_threshold
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self.stop_mult = stop_mult
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self.limit_offset_mult = limit_offset_mult
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self.order_direction = order_direction or ['BUY', 'SELL']
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self.indicator = indicator
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# 为 talib.ATR 预留充足的数据预热空间
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self._buf_len = max(self.t_len, self.f_len, self.atr_len * 2) + 100
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self._highs = deque(maxlen=self._buf_len)
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self._lows = deque(maxlen=self._buf_len)
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self._closes = deque(maxlen=self._buf_len)
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# 使用 deque 记录 FB，相比单独的 _prev_fb 变量更安全，不会因为初始 0 导致误判
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self._fbs = deque(maxlen=2)
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self.order_id_counter = 0
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def round_to_tick(self, price: float) -> float:
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if self.min_tick <= 0: return price
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return round(price / self.min_tick) * self.min_tick
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def _calculate_indicators(self):
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"""完全无状态的纯数学指标计算 (基于 TA-Lib)"""
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if len(self._closes) < self._buf_len:
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return None, None, None, None
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np_highs = np.array(self._highs, dtype=np.float64)
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np_lows = np.array(self._lows, dtype=np.float64)
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np_closes = np.array(self._closes, dtype=np.float64)
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# 1. T轴 (大势过滤)
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t_max_h = talib.MAX(np_highs, timeperiod=self.t_len)[-1]
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t_min_l = talib.MIN(np_lows, timeperiod=self.t_len)[-1]
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T = (t_max_h + t_min_l) / 2.0
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# 2. FV (公允价值挂单基准)
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FV = (np_closes[-1] + 2 * np_closes[-2] + 2 * np_closes[-3] + np_closes[-4]) / 6.0
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# 3. Fisher Transform (1.98 数学修复版)
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f_max_h = talib.MAX(np_highs, timeperiod=self.f_len)[-1]
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f_min_l = talib.MIN(np_lows, timeperiod=self.f_len)[-1]
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denom = f_max_h - f_min_l if f_max_h != f_min_l else self.min_tick
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stoc = (np_closes[-1] - f_min_l) / denom
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value = max(-0.999, min(0.999, 1.98 * (stoc - 0.5)))
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FB = 0.5 * math.log((1.0 + value) / (1.0 - value))
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# 4. ATR
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atr_array = talib.ATR(np_highs, np_lows, np_closes, timeperiod=self.atr_len)
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ATR = atr_array[-1]
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return T, FV, FB, ATR
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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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self.cancel_all_pending_orders(self.symbol)
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bars = self.get_bar_history()
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if len(bars) < 1: return
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prev_bar = bars[-1]
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self._highs.append(prev_bar.high)
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self._lows.append(prev_bar.low)
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self._closes.append(prev_bar.close)
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T, FV, FB, ATR = self._calculate_indicators()
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self.log(f'T: {T} FV: {FV} FB: {FB} ATR: {ATR}')
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if T is None or math.isnan(ATR): return
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self._fbs.append(FB)
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# 必须凑齐两根 FB 才能判断拐点，否则跳过
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if len(self._fbs) < 2: return
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current_fb = self._fbs[-1]
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prev_fb = self._fbs[-2]
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# 绝对无状态：从账户物理数据获取真实持仓和开仓均价
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pos = self.get_current_positions().get(self.symbol, 0)
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entry_price = self.get_average_position_price(self.symbol)
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is_met = self.indicator is None or self.indicator.is_condition_met(*self.get_indicator_tuple())
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self.log(f'is_met: {is_met}, pos: {pos}, current_fb: {current_fb}, prev_fb: {prev_fb}')
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# ==========================================
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# 核心一：经典出场逻辑 (你的原版设计)
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# ==========================================
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if pos != 0:
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stop_dist = max(self.stop_mult * ATR, self.min_tick * 20)
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# --- 预判：是否存在反向入场信号？ ---
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# 反向做多信号：大势已多 (C > T)，且动能回调 (FB < -0.1)
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is_long_signal = (prev_bar.close > T) and (current_fb < -self.fb_entry_threshold)
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# 反向做空信号：大势已空 (C < T)，且动能反弹 (FB > 0.1)
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is_short_signal = (prev_bar.close < T) and (current_fb > self.fb_entry_threshold)
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if pos > 0:
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# A. 动能极值止盈
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if current_fb > self.fisher_exit_level and current_fb < prev_fb:
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self.log(f"TAKE PROFIT (Long): FB {current_fb} Peak Reached")
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self.send_market_order("CLOSE_LONG", abs(pos), "CLOSE")
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return
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# B. 原版硬止损 (最后的底线)
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if prev_bar.close < entry_price - stop_dist:
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self.log(f"HARD STOP (Long): Close {prev_bar.close} < Limit {entry_price - stop_dist}")
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self.send_market_order("CLOSE_LONG", abs(pos), "CLOSE")
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return
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# C. 解决冲突：反向信号强制平仓
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# 如果我们持有多单，但盘面竟然发出了“做空”信号，说明大势已去，逻辑矛盾，必须平仓！
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if is_short_signal and is_met:
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self.log(f"REVERSAL SIGNAL EXIT (Long): Trend Down & Short Signal Triggered.")
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self.send_market_order("CLOSE_LONG", abs(pos), "CLOSE")
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return
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elif pos < 0:
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# A. 动能极值止盈
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if current_fb < -self.fisher_exit_level and current_fb > prev_fb:
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self.log(f"TAKE PROFIT (Short): FB {current_fb} Bottom Reached")
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self.send_market_order("CLOSE_SHORT", abs(pos), "CLOSE")
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return
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# B. 原版硬止损
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if prev_bar.close > entry_price + stop_dist:
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self.log(f"HARD STOP (Short): Close {prev_bar.close} > Limit {entry_price + stop_dist}")
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self.send_market_order("CLOSE_SHORT", abs(pos), "CLOSE")
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return
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# C. 解决冲突：反向信号强制平仓
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# 如果我们持有空单，但盘面发出了“做多”信号，平空！
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if is_long_signal and is_met:
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self.log(f"REVERSAL SIGNAL EXIT (Short): Trend Up & Long Signal Triggered.")
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self.send_market_order("CLOSE_SHORT", abs(pos), "CLOSE")
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return
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# ==========================================
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# 核心二：经典入场逻辑 (完全不变)
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# ==========================================
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elif pos == 0 and is_met:
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if prev_bar.close > T and current_fb < -self.fb_entry_threshold:
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if "BUY" in self.order_direction:
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long_limit = self.round_to_tick(FV - (self.limit_offset_mult * ATR))
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self.send_limit_order(long_limit, "BUY", self.trade_volume, "OPEN")
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elif prev_bar.close < T and current_fb > self.fb_entry_threshold:
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if "SELL" in self.order_direction:
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short_limit = self.round_to_tick(FV + (self.limit_offset_mult * ATR))
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self.send_limit_order(short_limit, "SELL", self.trade_volume, "OPEN")
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# ==========================================
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# 彻底隔离历史噪音：原生换月机制
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# ==========================================
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def on_contract_rollover(self, old_symbol: str, new_symbol: str):
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self.log(f"ROLLOVER TRIGGERED: {old_symbol} -> {new_symbol}")
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# 撤销老合约全部残留动作
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self.cancel_all_pending_orders(old_symbol)
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# 市价清空老合约，因为换月会导致 entry_price 和盘面断层，强制物理归零最安全
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pos = self.get_current_positions().get(old_symbol, 0)
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if pos > 0:
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self.send_order(Order(id=f"ROLLOVER_CLOSE_L_{old_symbol}", symbol=old_symbol, direction="CLOSE_LONG",
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volume=abs(pos), price_type="MARKET", submitted_time=self.get_current_time(),
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offset="CLOSE"))
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elif pos < 0:
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self.send_order(Order(id=f"ROLLOVER_CLOSE_S_{old_symbol}", symbol=old_symbol, direction="CLOSE_SHORT",
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volume=abs(pos), price_type="MARKET", submitted_time=self.get_current_time(),
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offset="CLOSE"))
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# 切换主交易标的
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self.main_symbol = new_symbol
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self.symbol = new_symbol
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# --- 下单系统 ---
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def send_market_order(self, direction, volume, offset):
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ts = self.get_current_time().strftime('%H%M%S')
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oid = f"{self.symbol}_{direction}_MKT_{ts}_{self.order_id_counter}"
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self.order_id_counter += 1
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self.send_order(Order(id=oid, symbol=self.symbol, direction=direction, volume=volume, price_type="MARKET",
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submitted_time=self.get_current_time(), offset=offset))
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def send_limit_order(self, price, direction, volume, offset):
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ts = self.get_current_time().strftime('%H%M%S')
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oid = f"{self.symbol}_{direction}_LMT_{ts}_{self.order_id_counter}"
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self.order_id_counter += 1
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self.send_order(Order(id=oid, symbol=self.symbol, direction=direction, volume=volume, price_type="LIMIT",
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submitted_time=self.get_current_time(), offset=offset, limit_price=price)) |