cfdaily
377 lines
14 KiB
Python
377 lines
14 KiB
Python
"""
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纯突破策略风控模块
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功能：
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1. 单票止损：跌破突破日最低价5% → 止损卖出
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2. 单日暴跌超过7% → 强制减仓
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3. 全仓回撤控制：整体回撤超过10%降仓，超过20%清半仓
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4. 排除过滤：ST、涨跌停不能买、日均成交额<5000万排除
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Author: 关羽（云长）
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Date: 2026-03-27
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"""
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from dataclasses import dataclass
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from typing import List, Dict, Optional, Tuple
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import pandas as pd
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@dataclass
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class BreakoutStock:
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"""突破策略单票信息"""
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code: str
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name: str
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breakout_date: str # 突破日期
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breakout_low: float # 突破日最低价
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current_price: float
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daily_change: float # 当日涨跌幅（%）
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is_st: bool = False
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is_limit_up: bool = False
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is_limit_down: bool = False
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avg_daily_volume: float = 0.0 # 日均成交额（亿）
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position_size: float = 0.0 # 当前持仓市值
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@dataclass
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class PortfolioInfo:
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"""组合信息"""
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initial_capital: float
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current_capital: float
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positions: Dict[str, float] # code -> position_size
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class BreakoutSingleStopLoss:
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"""单票止损规则：跌破突破日最低价5%止损"""
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def __init__(self, trigger_pct: float = 0.05):
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"""
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初始化
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:param trigger_pct: 跌破突破日最低价多少比例触发止损，默认5%
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"""
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self.trigger_pct = trigger_pct
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def check_stop_loss(self, stock: BreakoutStock) -> Tuple[bool, float]:
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"""
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检查是否触发止损
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:return: (是否触发, 当前价格相对突破低点跌幅)
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"""
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if stock.breakout_low <= 0:
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return False, 0.0
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drop_pct = (stock.breakout_low - stock.current_price) / stock.breakout_low
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# 当前价格跌破突破日最低价超过5%，触发止损
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return drop_pct >= self.trigger_pct, drop_pct
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class SingleDayCrashReduce:
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"""单日暴跌强制减仓：单日暴跌超过7%强制减仓"""
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def __init__(self, crash_threshold: float = -7.0, reduce_ratio: float = 0.5):
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"""
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初始化
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:param crash_threshold: 暴跌阈值（%），默认-7%
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:param reduce_ratio: 减仓比例，卖出一半，默认0.5
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"""
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self.crash_threshold = crash_threshold
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self.reduce_ratio = reduce_ratio
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def check_crash(self, stock: BreakoutStock) -> Tuple[bool, float]:
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"""检查是否触发暴跌减仓"""
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# 单日跌幅超过阈值，触发减仓
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return stock.daily_change <= self.crash_threshold, stock.daily_change
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def get_target_position(self, current_position: float) -> float:
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"""计算目标持仓"""
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return current_position * (1 - self.reduce_ratio)
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class PortfolioDrawdownControl:
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"""
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全仓回撤控制
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整体回撤 > 10% → 降仓到50%
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整体回撤 > 20% → 清半仓，保留25%
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"""
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def __init__(self,
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drawdown_1: float = 0.10,
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drawdown_2: float = 0.20,
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target_ratio_1: float = 0.50,
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target_ratio_2: float = 0.25):
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"""
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初始化
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:param drawdown_1: 一级回撤阈值
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:param drawdown_2: 二级回撤阈值
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:param target_ratio_1: 一级触发后目标仓位比例
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:param target_ratio_2: 二级触发后目标仓位比例
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"""
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self.drawdown_1 = drawdown_1
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self.drawdown_2 = drawdown_2
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self.target_ratio_1 = target_ratio_1
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self.target_ratio_2 = target_ratio_2
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def calculate_drawdown(self, portfolio: PortfolioInfo) -> float:
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"""计算组合总回撤"""
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if portfolio.initial_capital <= 0:
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return 0.0
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return (portfolio.initial_capital - portfolio.current_capital) / portfolio.initial_capital
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def get_target_position_ratio(self, portfolio: PortfolioInfo) -> float:
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"""获取目标仓位比例"""
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drawdown = self.calculate_drawdown(portfolio)
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if drawdown >= self.drawdown_2:
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return self.target_ratio_2
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elif drawdown >= self.drawdown_1:
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return self.target_ratio_1
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else:
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return 1.0 # 回撤不超，保持满仓
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def need_adjust(self, portfolio: PortfolioInfo) -> Tuple[bool, float]:
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"""检查是否需要调整仓位"""
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target_ratio = self.get_target_position_ratio(portfolio)
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current_total = sum(portfolio.positions.values())
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current_ratio = current_total / portfolio.current_capital
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if current_ratio > target_ratio + 0.05: # 5%容差
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return True, target_ratio
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return False, target_ratio
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class BreakoutPreTradeFilter:
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"""突破策略开仓前过滤：排除风险票"""
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def __init__(self, min_avg_volume: float = 0.5):
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"""
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初始化
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:param min_avg_volume: 最小日均成交额（亿），默认5000万
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"""
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self.min_avg_volume = min_avg_volume
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def filter_stock(self, stock: BreakoutStock) -> Tuple[bool, str]:
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"""
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开仓前过滤
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:return: (是否可以开仓, 不通过原因)
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"""
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# 1. 排除ST
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if stock.is_st:
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return False, "ST股票，排除"
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# 2. 涨跌停都不能买
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if stock.is_limit_up:
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return False, "涨停买不进，排除"
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if stock.is_limit_down:
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return False, "跌停不能买，排除"
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# 3. 流动性不足排除
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if stock.avg_daily_volume < self.min_avg_volume and stock.avg_daily_volume > 0:
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return False, f"日均成交额{stock.avg_daily_volume:.1f}亿，不足{self.min_avg_volume}亿，排除"
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# 全部通过
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return True, ""
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def filter_universe(self, stocks: List[BreakoutStock]) -> List[BreakoutStock]:
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"""批量过滤候选池"""
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result = []
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for stock in stocks:
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ok, _ = self.filter_stock(stock)
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if ok:
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result.append(stock)
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return result
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class BreakoutRiskController:
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"""突破策略总风控控制器，整合所有风控规则"""
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def __init__(self):
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self.stop_loss_rc = BreakoutSingleStopLoss()
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self.crash_rc = SingleDayCrashReduce()
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self.portfolio_rc = PortfolioDrawdownControl()
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self.filter_rc = BreakoutPreTradeFilter()
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def pre_trade_check(self, stock: BreakoutStock, portfolio: PortfolioInfo) -> Tuple[bool, str]:
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"""
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开仓前检查
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:return: (是否允许开仓, 原因)
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"""
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# 第一步：过滤检查
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ok, reason = self.filter_rc.filter_stock(stock)
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if not ok:
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return False, reason
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# 第二步：仓位检查
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need_adjust, target_ratio = self.portfolio_rc.need_adjust(portfolio)
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current_total = sum(portfolio.positions.values())
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current_ratio = current_total / portfolio.current_capital
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if current_ratio >= target_ratio:
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return False, f"整体回撤{self.portfolio_rc.calculate_drawdown(portfolio):.1%}，目标仓位{target_ratio:.1%}，当前已满仓，不允许开新仓"
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return True, "通过"
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def post_trade_check(self, stocks: List[BreakoutStock], portfolio: PortfolioInfo) -> dict:
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"""
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收盘后检查，找出需要止损减仓的标的
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:return: 风控检查结果
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"""
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# 1. 检查突破低点止损
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stop_loss_list = []
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for stock in stocks:
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triggered, drop = self.stop_loss_rc.check_stop_loss(stock)
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if triggered:
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stop_loss_list.append({
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"code": stock.code,
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"name": stock.name,
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"breakout_low": stock.breakout_low,
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"current_price": stock.current_price,
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"drop_pct": drop
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})
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# 2. 检查单日暴跌减仓
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crash_reduce_list = []
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for stock in stocks:
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triggered, change = self.crash_rc.check_crash(stock)
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if triggered:
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crash_reduce_list.append({
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"code": stock.code,
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"name": stock.name,
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"daily_change": change,
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"current_position": stock.position_size,
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"target_position": self.crash_rc.get_target_position(stock.position_size)
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})
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# 3. 检查组合整体回撤调整
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need_portfolio_adjust, target_ratio = self.portfolio_rc.need_adjust(portfolio)
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current_drawdown = self.portfolio_rc.calculate_drawdown(portfolio)
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current_total = sum(portfolio.positions.values())
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current_ratio = current_total / portfolio.current_capital if portfolio.current_capital > 0 else 0
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return {
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# 止损结果
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"has_stop_loss": len(stop_loss_list) > 0,
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"stop_loss_stocks": stop_loss_list,
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# 暴跌减仓结果
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"has_crash_reduce": len(crash_reduce_list) > 0,
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"crash_reduce_stocks": crash_reduce_list,
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# 组合调整结果
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"need_portfolio_adjust": need_portfolio_adjust,
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"current_drawdown": current_drawdown,
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"current_position_ratio": current_ratio,
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"target_position_ratio": target_ratio
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}
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def get_risk_report(self, stocks: List[BreakoutStock], portfolio: PortfolioInfo) -> str:
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"""生成风控日报"""
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result = self.post_trade_check(stocks, portfolio)
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lines = []
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lines.append("=" * 50)
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lines.append("纯突破策略 风控日报")
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lines.append("=" * 50)
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lines.append(f"初始资金: {portfolio.initial_capital:.0f}")
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lines.append(f"当前资金: {portfolio.current_capital:.0f}")
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lines.append(f"组合总回撤: {result['current_drawdown']:.2%}")
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lines.append(f"当前仓位比例: {result['current_position_ratio']:.2%}")
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lines.append(f"目标仓位比例: {result['target_position_ratio']:.2%}")
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lines.append("")
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if result['has_stop_loss']:
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lines.append("⚠️ 需要止损个股（跌破突破低点5%）:")
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for item in result['stop_loss_stocks']:
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lines.append(f" {item['code']} {item['name']} 突破低点:{item['breakout_low']:.2f} 当前:{item['current_price']:.2f} 跌幅:{item['drop_pct']:.2%}")
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else:
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lines.append("✅ 无个股触发跌破突破低点止损")
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lines.append("")
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if result['has_crash_reduce']:
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lines.append("⚠️ 需要减仓个股（单日暴跌超7%）:")
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for item in result['crash_reduce_stocks']:
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lines.append(f" {item['code']} {item['name']} 日跌幅:{item['daily_change']:.1f}% 当前持仓:{item['current_position']:.0f} → 目标:{item['target_position']:.0f}")
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else:
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lines.append("✅ 无个股触发单日暴跌减仓")
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lines.append("")
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if result['need_portfolio_adjust']:
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lines.append(f"⚠️ 组合需要降仓调整，当前仓位高于目标")
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else:
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lines.append("✅ 组合仓位符合风控要求")
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lines.append("=" * 50)
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return "\n".join(lines)
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if __name__ == "__main__":
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# 测试用例
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print("=== 测试纯突破风控模块 ===")
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# 测试1: 跌破突破低点止损
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stock1 = BreakoutStock(
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code="002123",
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name="梦网集团",
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breakout_date="2026-03-20",
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breakout_low=20.0,
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current_price=18.8,
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daily_change=-3.2
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)
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sl = BreakoutSingleStopLoss()
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triggered, drop = sl.check_stop_loss(stock1)
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print(f"\n[测试1] 跌破突破低点止损: 突破低点20，当前18.8，跌幅{(drop*100):.1f}% → 触发={triggered}")
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# 跌幅6%，应该触发5%止损 → True
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# 测试2: 单日暴跌减仓
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stock2 = BreakoutStock(
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code="600123",
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name="兰花科创",
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breakout_date="2026-03-20",
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breakout_low=15.0,
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current_price=13.5,
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daily_change=-7.8,
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position_size=100000
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)
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crash = SingleDayCrashReduce()
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triggered, change = crash.check_crash(stock2)
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print(f"\n[测试2] 单日暴跌减仓: 日跌幅{change:.1f}% → 触发={triggered}")
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print(f" 当前仓位100000 → 目标仓位{crash.get_target_position(100000)}")
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# 测试3: 组合回撤控制
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portfolio = PortfolioInfo(
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initial_capital=1000000,
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current_capital=880000,
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positions={"002123": 200000, "600123": 150000}
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)
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pd_ctrl = PortfolioDrawdownControl()
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dd = pd_ctrl.calculate_drawdown(portfolio)
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need_adj, target = pd_ctrl.need_adjust(portfolio)
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print(f"\n[测试3] 组合回撤控制: 初始100万，当前88万 → 回撤{dd:.1%}")
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print(f" 需要调整={need_adj}, 目标仓位比例={target:.1%}")
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# 测试4: 开仓过滤
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filter_ = BreakoutPreTradeFilter()
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st_stock = BreakoutStock(
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code="000003",
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name="ST基蛋",
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breakout_date="2026-03-20",
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breakout_low=10.0,
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current_price=10.5,
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daily_change=2.0,
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is_st=True
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)
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ok, reason = filter_.filter_stock(st_stock)
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print(f"\n[测试4] ST过滤: ok={ok}, reason={reason}")
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liq_stock = BreakoutStock(
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code="603xxx",
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name="小票",
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breakout_date="2026-03-20",
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breakout_low=10.0,
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current_price=10.5,
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daily_change=1.5,
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avg_daily_volume=0.3
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)
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ok, reason = filter_.filter_stock(liq_stock)
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print(f"流动性过滤(日均0.3亿): ok={ok}, reason={reason}")
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# 测试5: 整合风控报告
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rc = BreakoutRiskController()
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print("\n[测试5] 风控报告:")
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print(rc.get_risk_report([stock1, stock2], portfolio))
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