271 lines
13 KiB
Python
271 lines
13 KiB
Python
# src/execution_simulator.py (修改部分)
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from typing import Dict, List, Optional
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import pandas as pd
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from .core_data import Order, Trade, Bar, PortfolioSnapshot
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class ExecutionSimulator:
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"""
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模拟交易执行和管理账户资金、持仓。
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"""
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def __init__(self, initial_capital: float,
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slippage_rate: float = 0.0001,
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commission_rate: float = 0.0002,
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initial_positions: Optional[Dict[str, int]] = None):
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"""
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Args:
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initial_capital (float): 初始资金。
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slippage_rate (float): 滑点率（相对于成交价格的百分比）。
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commission_rate (float): 佣金率（相对于成交金额的百分比）。
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initial_positions (Optional[Dict[str, int]]): 初始持仓，格式为 {symbol: quantity}。
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"""
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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, int] = initial_positions if initial_positions is not None else {}
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# 新增：跟踪持仓的平均成本 {symbol: average_cost}
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self.average_costs: Dict[str, float] = {}
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# 如果有初始持仓，需要设置初始成本（简化为0，或在外部配置）
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if initial_positions:
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for symbol, qty in initial_positions.items():
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# 初始持仓成本，如果需要精确，应该从外部传入
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self.average_costs[symbol] = 0.0 # 简化处理，初始持仓成本为0
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self.slippage_rate = slippage_rate
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self.commission_rate = commission_rate
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self.trade_log: List[Trade] = [] # 存储所有成交记录
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self.pending_orders: Dict[str, Order] = {} # {order_id: Order_object}
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print(
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f"模拟器初始化：初始资金={self.initial_capital:.2f}, 滑点率={self.slippage_rate}, 佣金率={self.commission_rate}")
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if self.positions:
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print(f"初始持仓：{self.positions}")
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def _calculate_fill_price(self, order: Order, current_bar: Bar) -> float:
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"""
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内部方法：根据订单类型和滑点计算实际成交价格。
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简化处理：市价单以当前Bar收盘价为基准，考虑滑点。
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"""
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base_price = current_bar.close # 简化为收盘价成交
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# 考虑滑点
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if order.direction in ["BUY", "CLOSE_SHORT"]: # 买入或平空，价格向上偏离
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fill_price = base_price * (1 + self.slippage_rate)
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elif order.direction in ["SELL", "CLOSE_LONG"]: # 卖出或平多，价格向下偏离
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fill_price = base_price * (1 - self.slippage_rate)
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else: # 默认情况，无滑点
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fill_price = base_price
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# 如果是限价单且成交价格不满足条件，则可能不成交
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if order.price_type == "LIMIT" and order.limit_price is not None:
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# 对于BUY和CLOSE_SHORT，成交价必须 <= 限价
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if (order.direction == "BUY" or order.direction == "CLOSE_SHORT") and fill_price > order.limit_price:
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return -1.0 # 未触及限价
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# 对于SELL和CLOSE_LONG，成交价必须 >= 限价
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elif (order.direction == "SELL" or order.direction == "CLOSE_LONG") and fill_price < order.limit_price:
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return -1.0 # 未触及限价
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return fill_price
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def send_order(self, order: Order, current_bar: Bar) -> Optional[Trade]:
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"""
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接收策略发出的订单，并模拟执行。
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如果订单未立即成交，则加入待处理订单列表。
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特殊处理：如果 order.direction 是 "CANCEL"，则调用 cancel_order。
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Args:
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order (Order): 待执行的订单对象。
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current_bar (Bar): 当前的Bar数据，用于确定成交价格。
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Returns:
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Optional[Trade]: 如果订单成功执行则返回 Trade 对象，否则返回 None。
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"""
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# --- 处理撤单指令 ---
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if order.direction == "CANCEL":
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success = self.cancel_order(order.id)
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if success:
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# print(f"[{current_bar.datetime}] 模拟器: 收到并成功处理撤单指令 for Order ID: {order.id}")
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pass
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else:
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# print(f"[{current_bar.datetime}] 模拟器: 收到撤单指令 for Order ID: {order.id}, 但订单已成交或不存在。")
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pass
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return None # 撤单操作不返回Trade
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# --- 正常买卖订单处理 ---
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symbol = order.symbol
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volume = order.volume
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# 尝试计算成交价格
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fill_price = self._calculate_fill_price(order, current_bar)
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executed_trade: Optional[Trade] = None
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realized_pnl = 0.0 # 初始化实现盈亏
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is_open_trade = False
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is_close_trade = False
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if fill_price <= 0: # 表示未成交或不满足限价条件
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if order.price_type == "LIMIT":
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self.pending_orders[order.id] = order
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return None # 未成交，返回None
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# --- 以下是订单成功成交的逻辑 ---
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trade_value = volume * fill_price
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commission = trade_value * self.commission_rate
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current_position = self.positions.get(symbol, 0)
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current_average_cost = self.average_costs.get(symbol, 0.0)
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if order.direction == "BUY":
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# 开多仓或平空仓
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if current_position >= 0: # 当前持有多仓或无仓位 (开多)
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is_open_trade = True
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# 更新平均成本 (加权平均)
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new_total_cost = (current_average_cost * current_position) + (fill_price * volume)
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new_total_volume = current_position + volume
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self.average_costs[symbol] = new_total_cost / new_total_volume if new_total_volume > 0 else 0.0
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self.positions[symbol] = new_total_volume
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else: # 当前持有空仓 (平空)
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is_close_trade = True
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# 计算平空盈亏
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# PnL = (开仓成本 - 平仓价格) * 平仓数量 (注意空头方向)
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# 简化：假设平空时，直接使用当前的平均开仓成本来计算盈亏
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# 更精确的FIFO/LIFO需更多逻辑
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pnl_per_share = current_average_cost - fill_price # (买入平空，成本高于平仓价则盈利)
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realized_pnl = pnl_per_share * volume
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# 更新持仓和成本
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self.positions[symbol] += volume
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if self.positions[symbol] == 0:
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del self.positions[symbol]
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if symbol in self.average_costs: del self.average_costs[symbol] # 清理成本
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elif self.positions[symbol] > 0 and current_position < 0: # 部分平空转为多头，需重新设置成本
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# 这部分逻辑可以更复杂，这里简化处理，如果转为多头，成本重置为0
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# 实际应该用剩余的空头成本 + 新开多的成本
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self.average_costs[symbol] = fill_price # 简单地将剩下的多头仓位成本设为当前价格
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# 资金扣除
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if self.cash >= trade_value + commission:
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self.cash -= (trade_value + commission)
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else:
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# print(f"[{current_bar.datetime}] 资金不足，无法执行买入 {volume} {symbol}")
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return None
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elif order.direction == "SELL":
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# 开空仓或平多仓
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if current_position <= 0: # 当前持有空仓或无仓位 (开空)
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is_open_trade = True
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# 更新平均成本 (空头成本为负值)
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new_total_cost = (current_average_cost * current_position) - (fill_price * volume) # 负的持仓乘以负的卖出价
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new_total_volume = current_position - volume # 空头持仓量更负
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self.average_costs[symbol] = new_total_cost / new_total_volume if new_total_volume < 0 else 0.0
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self.positions[symbol] = new_total_volume
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else: # 当前持有多仓 (平多)
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is_close_trade = True
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# 计算平多盈亏
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# PnL = (平仓价格 - 开仓成本) * 平仓数量
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pnl_per_share = fill_price - current_average_cost # (卖出平多，平仓价高于成本则盈利)
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realized_pnl = pnl_per_share * volume
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# 更新持仓和成本
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self.positions[symbol] -= volume
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if self.positions[symbol] == 0:
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del self.positions[symbol]
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if symbol in self.average_costs: del self.average_costs[symbol] # 清理成本
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elif self.positions[symbol] < 0 and current_position > 0: # 部分平多转为空头，需重新设置成本
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self.average_costs[symbol] = fill_price # 简单地将剩下的空头仓位成本设为当前价格
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# 资金扣除 (佣金) 和增加 (卖出收入)
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if self.cash >= commission:
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self.cash -= commission
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self.cash += trade_value
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else:
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# print(f"[{current_bar.datetime}] 资金不足，无法执行卖出 {volume} {symbol}")
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return None
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# 创建 Trade 对象
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executed_trade = Trade(
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order_id=order.id, fill_time=current_bar.datetime, symbol=symbol,
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direction=order.direction, # 记录原始订单方向 (BUY/SELL)
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volume=volume, price=fill_price, commission=commission,
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cash_after_trade=self.cash, positions_after_trade=self.positions.copy(),
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realized_pnl=realized_pnl, # 填充实现盈亏
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is_open_trade=is_open_trade,
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is_close_trade=is_close_trade
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)
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self.trade_log.append(executed_trade)
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# 如果订单成交，无论它是市价单还是限价单，都从待处理订单中移除
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if order.id in self.pending_orders:
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del self.pending_orders[order.id]
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# print(f"[{current_bar.datetime}] 成交: {executed_trade.direction} {executed_trade.volume} {executed_trade.symbol} @ {executed_trade.price:.2f}, 佣金: {executed_trade.commission:.2f}, PnL: {executed_trade.realized_pnl:.2f}")
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return executed_trade
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def cancel_order(self, order_id: str) -> bool:
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"""
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尝试取消一个待处理订单。
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Args:
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order_id (str): 要取消的订单ID。
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Returns:
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bool: 如果成功取消则返回 True，否则返回 False（例如，订单不存在或已成交）。
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"""
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if order_id in self.pending_orders:
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# print(f"订单 {order_id} 已成功取消。")
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del self.pending_orders[order_id]
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return True
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# print(f"订单 {order_id} 不存在或已成交，无法取消。")
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return False
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def get_pending_orders(self) -> Dict[str, Order]:
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"""
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获取当前所有待处理订单的副本。
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"""
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return self.pending_orders.copy()
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def get_portfolio_value(self, current_bar: Bar) -> float:
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"""
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计算当前的投资组合总价值（包括现金和持仓市值）。
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Args:
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current_bar (Bar): 当前的Bar数据，用于计算持仓市值。
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Returns:
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float: 当前的投资组合总价值。
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"""
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total_value = self.cash
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# 在单品种场景下，我们假设 self.positions 最多只包含一个品种
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# 并且这个品种就是 current_bar.symbol 所代表的品种
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symbol_in_position = list(self.positions.keys())[0] if self.positions else None
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if symbol_in_position and symbol_in_position == current_bar.symbol:
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quantity = self.positions[symbol_in_position]
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# 持仓市值 = 数量 * 当前市场价格 (current_bar.close)
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# 无论多头(quantity > 0)还是空头(quantity < 0)，这个计算都是正确的
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total_value += quantity * current_bar.close
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# 您也可以选择在这里打印调试信息
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# print(f" DEBUG Portfolio Value Calculation: Cash={self.cash:.2f}, "
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# f"Position for {symbol_in_position}: {quantity} @ {current_bar.close:.2f}, "
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# f"Position Value={quantity * current_bar.close:.2f}, Total Value={total_value:.2f}")
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# 如果没有持仓，或者持仓品种与当前Bar品种不符 (理论上单品种不会发生)
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# 那么 total_value 依然是 self.cash
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return total_value
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def get_current_positions(self) -> Dict[str, int]:
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"""
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返回当前持仓字典的副本。
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"""
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return self.positions.copy()
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def get_trade_history(self) -> List[Trade]:
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"""
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返回所有成交记录的副本。
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"""
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return self.trade_log.copy()
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