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）
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@@ -1,55 +1,119 @@
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"""
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执行层抽象设计
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执行层抽象接口（通用）
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核心组件：
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- Executor: 执行器抽象基类
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- BacktestExecutor: 回测执行器
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- DryRunExecutor: 模拟盘执行器
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只提供抽象基类和Portfolio数据结构，具体执行器可扩展
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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 dataclasses import dataclass
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from typing import Dict, List, Optional
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import pandas as pd
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from datetime import datetime
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from framework.risk import Position
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@dataclass
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class Portfolio:
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"""持仓组合"""
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positions: Dict[str, Any] # {code: Position}
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cash: float
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nav: float
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trades: List[Any]
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"""
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投资组合数据结构（通用）
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def get_total_value(self) -> float:
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"""获取总价值"""
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position_value = sum(
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pos.quantity * pos.current_price
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for pos in self.positions.values()
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用于管理持仓集合
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"""
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def __init__(self, initial_capital: float = 100000):
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"""初始化投资组合"""
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self.initial_capital = initial_capital
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self.cash = initial_capital
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self.positions: Dict[str, Position] = {}
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self.trades: List[Dict] = []
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self._net_value_history: List[float] = []
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def add_position(self, code: str, price: float, quantity: float, time: datetime) -> None:
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"""添加持仓"""
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position = Position(
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code=code,
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entry_price=price,
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current_price=price,
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entry_time=time,
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quantity=quantity
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)
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return self.cash + position_value
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self.positions[code] = position
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self.cash -= price * quantity
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self.trades.append({
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'action': 'BUY',
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'code': code,
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'price': price,
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'quantity': quantity,
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'time': time
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})
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def get_position_codes(self) -> List[str]:
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"""获取持仓代码列表"""
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return list(self.positions.keys())
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def remove_position(self, code: str, price: float, time: datetime) -> float:
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"""移除持仓"""
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if code not in self.positions:
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return 0
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position = self.positions[code]
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profit = (price - position.entry_price) * position.quantity
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self.cash += price * position.quantity
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del self.positions[code]
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self.trades.append({
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'action': 'SELL',
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'code': code,
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'price': price,
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'quantity': position.quantity,
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'time': time,
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'profit': profit
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})
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return profit
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def update_prices(self, prices: Dict[str, float]) -> None:
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"""更新持仓价格"""
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for code, price in prices.items():
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if code in self.positions:
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self.positions[code].current_price = price
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def get_net_value(self) -> float:
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"""计算净值"""
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positions_value = sum(
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pos.current_price * pos.quantity for pos in self.positions.values()
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)
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return self.cash + positions_value
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def record_net_value(self) -> None:
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"""记录当前净值"""
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self._net_value_history.append(self.get_net_value())
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def get_net_value_series(self) -> pd.Series:
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"""获取净值序列"""
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return pd.Series(self._net_value_history)
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def get_weight(self, code: str) -> float:
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"""计算持仓权重"""
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if code not in self.positions:
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return 0
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position_value = self.positions[code].current_price * self.positions[code].quantity
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return position_value / self.get_net_value()
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def __repr__(self) -> str:
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return f"Portfolio(capital={self.cash:.2f}, positions={len(self.positions)})"
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class Executor(ABC):
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"""
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执行器抽象基类
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支持不同执行模式：
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- backtest: 回测模式
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- dry_run: 模拟盘模式
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- live: 实盘模式（TODO）
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所有执行器必须实现execute方法
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"""
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mode: str = "base"
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def __init__(self, config: Optional[Dict] = None):
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self._config = config or {}
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self._portfolio = None
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def __init__(self, **params):
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"""初始化执行器参数"""
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self._params = params
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@abstractmethod
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def execute(self, signals: pd.DataFrame, data: pd.DataFrame) -> Portfolio:
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@@ -58,121 +122,71 @@ class Executor(ABC):
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Args:
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signals: 信号DataFrame
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data: 价格数据
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data: OHLCV数据
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Returns:
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持仓组合
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Portfolio对象
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"""
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pass
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@abstractmethod
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def get_mode(self) -> str:
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"""获取执行模式"""
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pass
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@property
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def portfolio(self) -> Optional[Portfolio]:
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"""获取当前持仓"""
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return self._portfolio
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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 BacktestExecutor(Executor):
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"""
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回测执行器
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回测执行器（通用骨架）
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执行回测逻辑：
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- 处理信号
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- 计算净值
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- 记录交易
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具体回测逻辑需要在strategies中定制实现
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"""
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mode = "backtest"
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def __init__(
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self,
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initial_capital: float = 100000.0,
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trade_cost: float = 0.001
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):
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super().__init__()
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def __init__(self, initial_capital: float = 100000, trade_cost: float = 0.001):
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super().__init__(initial_capital=initial_capital, trade_cost=trade_cost)
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self.initial_capital = initial_capital
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self.trade_cost = trade_cost
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def execute(self, signals: pd.DataFrame, data: pd.DataFrame) -> Portfolio:
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"""执行回测"""
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# 初始化持仓
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self._portfolio = Portfolio(
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positions={},
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cash=self.initial_capital,
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nav=1.0,
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trades=[]
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)
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"""
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执行回测（简化版本）
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# 回测逻辑（简化版）
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result = pd.DataFrame(index=signals.index)
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result['nav'] = 1.0
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result['daily_return'] = 0.0
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完整回测逻辑需要定制实现
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"""
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portfolio = Portfolio(self.initial_capital)
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# TODO: 完整回测逻辑迁移
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# 这里只提供骨架，具体逻辑需要定制实现
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# 包括：净值计算、交易成本扣除、基准对比等
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return self._portfolio
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def get_mode(self) -> str:
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return "backtest"
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return portfolio
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class DryRunExecutor(Executor):
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"""
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模拟盘执行器
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Dry-run执行器（通用）
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执行模拟交易：
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- 模拟下单
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- 模拟成交
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- 模拟持仓更新
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用于模拟运行，不实际执行交易
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"""
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mode = "dry_run"
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def __init__(
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self,
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initial_capital: float = 100000.0,
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simulated_exchange = None
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):
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super().__init__()
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self.initial_capital = initial_capital
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self.simulated_exchange = simulated_exchange
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def __init__(self, verbose: bool = True):
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super().__init__(verbose=verbose)
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self.verbose = verbose
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def execute(self, signals: pd.DataFrame, data: pd.DataFrame) -> Portfolio:
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"""执行模拟盘"""
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# 初始化持仓
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self._portfolio = Portfolio(
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positions={},
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cash=self.initial_capital,
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nav=1.0,
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trades=[]
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)
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"""模拟执行"""
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portfolio = Portfolio(100000)
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# 模拟执行逻辑
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# TODO: 模拟订单执行
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for date in signals.index:
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signal = signals.loc[date, 'signal']
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if signal and self.verbose:
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print(f"[{date}] Signal: {signal}")
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return self._portfolio
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def get_mode(self) -> str:
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return "dry_run"
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def simulate_order(self, code: str, direction: str, quantity: float, price: float):
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"""模拟下单"""
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# 记录模拟订单
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print(f"[DRY_RUN] {direction} {quantity} {code} @ {price}")
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# 更新持仓
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if direction == 'BUY':
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# 模拟买入
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cost = quantity * price
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if cost <= self._portfolio.cash:
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self._portfolio.cash -= cost
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# TODO: 创建Position对象
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elif direction == 'SELL':
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# 模拟卖出
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if code in self._portfolio.positions:
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# TODO: 平仓逻辑
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pass
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return portfolio
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# 导出抽象接口
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__all__ = ['Portfolio', 'Executor', 'BacktestExecutor', 'DryRunExecutor']
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