refactor(framework): 框架只保留抽象接口，具体实现移至strategies/shared
- FactorBase/FactorRegistry/FactorCombiner: 因子抽象接口 - SignalGenerator: 信号生成抽象接口 - RiskControl/Position/CallbackHook: 风控抽象接口 - StrategyBase: 策略抽象基类 - Executor/Portfolio: 执行器抽象接口 - ConfigLoader: 配置加载器 - 删除framework/factors/momentum.py（具体实现）
This commit is contained in:
@@ -1,351 +1,188 @@
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"""
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回调钩子与风控层设计
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风控层抽象接口（通用）
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核心组件：
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- RiskControl: 风控抽象基类
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- StopLossControl: 止损控制
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- PositionLimitControl: 仓位限制控制
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- CallbackHook: 回调钩子管理
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只提供抽象基类和回调机制，具体风控组件在strategies/shared/risk/
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"""
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import pandas as pd
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from abc import ABC, abstractmethod
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from typing import Dict, Any, Optional, List
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from typing import Dict, List, Any, Callable, Optional
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from dataclasses import dataclass
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from datetime import datetime
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@dataclass
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class Position:
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"""持仓信息"""
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"""
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持仓数据结构（通用）
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用于表示单个持仓的状态
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"""
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code: str
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entry_price: float
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entry_date: datetime
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current_price: float
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current_date: datetime
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quantity: float
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weight: float
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entry_time: datetime
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quantity: float = 1.0
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weight: float = 1.0
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@property
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def profit_ratio(self) -> float:
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"""盈亏比例"""
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"""计算盈亏比例"""
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return (self.current_price - self.entry_price) / self.entry_price
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@property
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def holding_days(self) -> int:
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"""持仓天数"""
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return (self.current_date - self.entry_date).days
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def profit_amount(self) -> float:
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"""计算盈亏金额"""
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return (self.current_price - self.entry_price) * self.quantity
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@property
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def is_profit(self) -> bool:
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"""是否盈利"""
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return self.profit_ratio > 0
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@dataclass
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class Trade:
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"""交易信息"""
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code: str
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direction: str # 'entry' or 'exit'
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price: float
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date: datetime
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quantity: float
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reason: str = ""
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def holding_days(self) -> int:
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"""计算持仓天数"""
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if self.entry_time is None:
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return 0
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return (datetime.now() - self.entry_time).days
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def __repr__(self) -> str:
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return f"Position(code={self.code}, profit={self.profit_ratio:.2%}, days={self.holding_days})"
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class RiskControl(ABC):
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"""
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风控抽象基类
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风控组件抽象基类
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所有风控组件必须继承此基类。
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所有风控组件必须实现check方法
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"""
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name: str = "base"
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def __init__(self, **params):
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"""初始化风控参数"""
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self._params = params
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@abstractmethod
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def check(self, position: Optional[Position], **kwargs) -> bool:
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def check(self, position: Position, **kwargs) -> bool:
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"""
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风控检查
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检查风控条件
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Args:
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position: 持仓信息（可选）
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**kwargs: 其他参数
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position: 持仓对象
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kwargs: 额外参数（如premium、history等）
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Returns:
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是否通过检查
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True表示通过检查，False表示触发风控
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"""
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pass
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@abstractmethod
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def apply(self, position: Position) -> Optional[float]:
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def apply(self, position: Position) -> Any:
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"""
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应用风控
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应用风控规则（可选）
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Args:
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position: 持仓信息
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position: 持仓对象
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Returns:
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应用结果（如止损价格、仓位调整比例等）
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风控结果（如止损价格、建议仓位等）
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"""
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pass
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@property
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def params(self) -> Dict[str, Any]:
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return self._params
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class StopLossControl(RiskControl):
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"""
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止损控制
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参数：
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- threshold: 止损阈值（默认-0.05）
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- trailing: 是否跟踪止损（默认False）
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- trailing_percent: 跟踪止损比例（默认0.03）
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"""
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name = "stop_loss"
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def __init__(
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self,
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threshold: float = -0.05,
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trailing: bool = False,
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trailing_percent: float = 0.03
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):
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super().__init__(
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threshold=threshold,
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trailing=trailing,
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trailing_percent=trailing_percent
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)
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self.threshold = threshold
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self.trailing = trailing
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self.trailing_percent = trailing_percent
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self._highest_price = {} # 跟踪最高价
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def check(self, position: Optional[Position], **kwargs) -> bool:
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"""检查是否触发止损"""
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if position is None:
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return True
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# 更新最高价（跟踪止损）
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if self.trailing:
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if position.code not in self._highest_price:
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self._highest_price[position.code] = position.entry_price
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self._highest_price[position.code] = max(
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self._highest_price[position.code],
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position.current_price
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)
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# 检查止损
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if self.trailing:
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# 跟踪止损：从最高价回撤超过阈值
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highest = self._highest_price[position.code]
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drawdown = (position.current_price - highest) / highest
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return drawdown > -self.trailing_percent
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else:
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# 固定止损：从入场价亏损超过阈值
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return position.profit_ratio > self.threshold
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def apply(self, position: Position) -> Optional[float]:
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"""返回止损价格"""
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if self.trailing:
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highest = self._highest_price.get(position.code, position.entry_price)
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return highest * (1 - self.trailing_percent)
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else:
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return position.entry_price * (1 + self.threshold)
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class PositionLimitControl(RiskControl):
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"""
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仓位限制控制
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参数：
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- max_position: 单品种最大仓位（默认0.33）
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- max_total: 总仓位上限（默认1.0）
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"""
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name = "position_limit"
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def __init__(
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self,
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max_position: float = 0.33,
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max_total: float = 1.0
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):
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super().__init__(
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max_position=max_position,
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max_total=max_total
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)
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self.max_position = max_position
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self.max_total = max_total
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def check(self, position: Optional[Position], **kwargs) -> bool:
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"""检查仓位是否超限"""
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if position is None:
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return True
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# 检查单品种仓位
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if position.weight > self.max_position:
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return False
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return True
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def apply(self, position: Position) -> Optional[float]:
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"""返回建议仓位"""
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return min(position.weight, self.max_position)
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class PremiumControl(RiskControl):
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"""
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溢价控制
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参数：
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- threshold: 溢价阈值（默认0.10）
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- mode: 控制模式（'filter'或'penalize'）
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"""
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name = "premium"
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def __init__(
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self,
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threshold: float = 0.10,
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mode: str = 'filter'
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):
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super().__init__(
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threshold=threshold,
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mode=mode
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)
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self.threshold = threshold
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self.mode = mode
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def check(self, position: Optional[Position], **kwargs) -> bool:
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"""检查溢价是否超限"""
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premium = kwargs.get('premium', 0)
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if self.mode == 'filter':
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# 完全排除
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return premium <= self.threshold
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else:
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# 仅降权，允许通过
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return True
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def apply(self, position: Position) -> Optional[float]:
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"""返回溢价惩罚系数"""
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if self.mode == 'penalize':
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return 0.5 # 降权50%
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return None
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def __repr__(self) -> str:
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params_str = ', '.join([f"{k}={v}" for k, v in self._params.items()])
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return f"{self.__class__.__name__}({params_str})"
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class CallbackHook:
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"""
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回调钩子管理
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回调钩子管理（通用）
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支持策略生命周期回调：
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- before_entry: 入场前检查
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- after_entry: 入场后处理
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- before_exit: 出场前检查
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- after_exit: 出场后处理
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- dynamic_stoploss: 动态止损
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- custom_exit: 自定义出场
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支持在策略生命周期的关键节点注入自定义逻辑
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"""
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SUPPORTED_HOOKS = [
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'before_entry', # 入场前检查
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'after_entry', # 入场后处理
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'before_exit', # 出场前检查
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'after_exit', # 出场后处理
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'dynamic_stoploss', # 动态止损计算
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'custom_exit' # 自定义出场条件
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]
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def __init__(self):
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self._hooks = {
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'before_entry': [],
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'after_entry': [],
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'before_exit': [],
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'after_exit': [],
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'dynamic_stoploss': [],
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'custom_exit': []
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"""初始化回调钩子"""
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self._hooks: Dict[str, List[Callable]] = {
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hook: [] for hook in self.SUPPORTED_HOOKS
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}
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def register(self, hook_name: str, callback: callable) -> None:
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"""注册回调"""
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def register(self, hook_name: str, callback: Callable) -> None:
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"""注册回调函数"""
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if hook_name not in self._hooks:
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raise ValueError(f"Unknown hook: {hook_name}")
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raise ValueError(f"Unsupported hook: {hook_name}")
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self._hooks[hook_name].append(callback)
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def trigger(self, hook_name: str, *args, **kwargs) -> Any:
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"""触发回调"""
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"""
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触发回调
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Args:
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hook_name: 钩子名称
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args: 位置参数
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kwargs: 关键字参数
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Returns:
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回调结果（根据钩子类型返回不同结果）
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"""
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if hook_name not in self._hooks:
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raise ValueError(f"Unknown hook: {hook_name}")
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raise ValueError(f"Unsupported hook: {hook_name}")
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callbacks = self._hooks[hook_name]
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if not callbacks:
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# 默认行为
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if hook_name == 'dynamic_stoploss':
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return kwargs.get('default_stoploss', -0.05)
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elif hook_name in ['before_entry', 'before_exit']:
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return True
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elif hook_name == 'custom_exit':
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return False
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return None
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results = []
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for callback in self._hooks[hook_name]:
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try:
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result = callback(*args, **kwargs)
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results.append(result)
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except Exception as e:
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print(f"⚠ Callback error: {e}")
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for callback in callbacks:
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result = callback(*args, **kwargs)
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results.append(result)
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# before_entry和before_exit需要所有回调返回True
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# 根据钩子类型返回不同结果
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if hook_name in ['before_entry', 'before_exit']:
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# 所有回调返回True才允许
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return all(results)
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# dynamic_stoploss返回最小的止损值
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if hook_name == 'dynamic_stoploss':
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return min(results) if results else -0.05
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# 返回最小止损值（最严格）
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return min(results)
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# custom_exit返回是否有任一回调触发出场
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if hook_name == 'custom_exit':
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# 任一回调触发出场
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return any(results)
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return results
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# 其他钩子返回最后一个结果
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return results[-1] if results else None
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def clear(self, hook_name: str = None) -> None:
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def clear(self, hook_name: Optional[str] = None) -> None:
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"""清空回调"""
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if hook_name:
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self._hooks[hook_name] = []
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if hook_name in self._hooks:
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self._hooks[hook_name] = []
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else:
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for key in self._hooks:
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self._hooks[key] = []
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for hook in self._hooks:
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self._hooks[hook] = []
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def list_hooks(self) -> List[str]:
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"""列出支持的钩子"""
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return self.SUPPORTED_HOOKS
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def get_callbacks(self, hook_name: str) -> List[Callable]:
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"""获取钩子的所有回调"""
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return self._hooks.get(hook_name, [])
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# 便捷回调函数
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def premium_filter_callback(threshold: float = 0.10):
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"""溢价过滤回调"""
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def callback(code: str, price: float, **kwargs) -> bool:
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premium = kwargs.get('premium', 0)
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if premium > threshold:
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print(f"溢价过高，拒绝入场: {code} (溢价={premium:.2%})")
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return False
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return True
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return callback
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def crash_filter_callback(lookback: int = 3, crash_threshold: float = 0.05):
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"""崩盘过滤回调"""
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def callback(code: str, price: float, **kwargs) -> bool:
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history = kwargs.get('history', None)
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if history is None:
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return True
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# 检查最近N天是否有崩盘
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recent = history.tail(lookback)
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if len(recent) < lookback:
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return True
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returns = recent['close'].pct_change()
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min_return = returns.min()
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if min_return < -crash_threshold:
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print(f"崩盘检测，拒绝入场: {code} (最大跌幅={min_return:.2%})")
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return False
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return True
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return callback
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def holding_time_stoploss_callback(
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day_5_stoploss: float = -0.05,
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day_10_stoploss: float = -0.03
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):
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"""持仓时间动态止损回调"""
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def callback(position: Position) -> float:
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if position.holding_days >= 10:
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return day_10_stoploss # 10天后收紧止损
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elif position.holding_days >= 5:
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return day_5_stoploss
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return -0.10 # 默认止损
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return callback
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# 导出抽象接口
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__all__ = ['Position', 'RiskControl', 'CallbackHook']
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