NewQuant/src/execution_simulator.py

# src/execution_simulator.py

from datetime import datetime
from typing import Dict, List, Optional
import pandas as pd
from .core_data import Order, Trade, Bar, PortfolioSnapshot


class ExecutionSimulator:
    """
    模拟交易执行和管理账户资金、持仓。
    """

    def __init__(
        self,
        initial_capital: float,
        slippage_rate: float = 0.0001,
        commission_rate: float = 0.0002,
        initial_positions: Optional[Dict[str, int]] = None,
        initial_average_costs: Optional[Dict[str, float]] = None,
    ):  # 新增参数
        self.initial_capital = initial_capital
        self.cash = initial_capital
        self.positions: Dict[str, int] = (
            initial_positions if initial_positions is not None else {}
        )
        # 修正：初始平均成本应该从参数传入，而不是默认0.0
        self.average_costs: Dict[str, float] = (
            initial_average_costs if initial_average_costs is not None else {}
        )
        # 如果提供了 initial_positions 但没有提供 initial_average_costs，可以警告或默认处理
        if initial_positions and not initial_average_costs:
            print(
                f"[{datetime.now()}] 警告: 提供了初始持仓但未提供初始平均成本，这些持仓的成本默认为0.0。"
            )
            for symbol, qty in initial_positions.items():
                if symbol not in self.average_costs:
                    self.average_costs[symbol] = 0.0  # 如果没有提供，默认给0

        self.slippage_rate = slippage_rate
        self.commission_rate = commission_rate
        self.trade_log: List[Trade] = []
        self.pending_orders: Dict[str, Order] = {}
        self._current_time: Optional[datetime] = None
        self.indicator_dict = {}

        print(
            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}"
        )
        if self.positions:
            print(f"初始持仓：{self.positions}")
            print(f"初始平均成本：{self.average_costs}")  # 打印初始成本以便检查

    def update_time(self, current_time: datetime):
        self._current_time = current_time

    def get_current_time(self) -> datetime:
        if self._current_time is None:
            return None
        return self._current_time

    def _calculate_fill_price(self, order: Order, current_bar: Bar) -> float:
        """
        内部方法：根据订单类型和滑点计算实际成交价格。
        撮合逻辑：
        - 市价单：以当前K线的 **开盘价 (open)** 为基准进行撮合，并考虑滑点。
        - 限价单：判断 K 线的 **最高价 (high)** 和 **最低价 (low)** 是否触及限价。如果触及，则以 **限价 (limit_price)** 为基准计算成交价，并考虑滑点。
        """
        fill_price = -1.0  # 默认未成交

        # 对于市价单，仍然使用开盘价作为基准检查点
        base_price_for_market_order = current_bar.open

        if order.price_type == "MARKET":
            # 市价单：直接以开盘价成交，考虑滑点
            if (
                order.direction == "BUY" or order.direction == "CLOSE_SHORT"
            ):  # 买入/平空：向上偏离（多付）
                fill_price = (base_price_for_market_order + 1) * (1 + self.slippage_rate)
            elif (
                order.direction == "SELL" or order.direction == "CLOSE_LONG"
            ):  # 卖出/平多：向下偏离（少收）
                fill_price = (base_price_for_market_order - 1) * (1 - self.slippage_rate)
            else:
                fill_price = base_price_for_market_order  # 理论上不发生

        elif order.price_type == "LIMIT" and order.limit_price is not None:
            limit_price = order.limit_price

            # 限价单：判断 K 线的高低价是否触及限价
            if (
                order.direction == "BUY" or order.direction == "CLOSE_SHORT"
            ):  # 限价买入/平空
                # 如果当前K线的最低价低于或等于限价，则买入限价单有机会成交
                if current_bar.low < limit_price:
                    # 成交价以限价为基准，并考虑滑点（买入向上偏离）
                    fill_price = limit_price * (1 + self.slippage_rate)
            elif (
                order.direction == "SELL" or order.direction == "CLOSE_LONG"
            ):  # 限价卖出/平多
                # 如果当前K线的最高价高于或等于限价，则卖出限价单有机会成交
                if current_bar.high > limit_price:
                    # 成交价以限价为基准，并考虑滑点（卖出向下偏离）
                    fill_price = limit_price * (1 - self.slippage_rate)

        if fill_price <= 0:
            return -1.0
        return fill_price


    def send_order_to_pending(self, order: Order) -> Optional[Order]:
        """
        将订单添加到待处理队列。由 BacktestEngine 或 Strategy 调用。
        此方法不进行撮合，撮合由 process_pending_orders 统一处理。
        """
        if order.id in self.pending_orders:
            return None
        self.pending_orders[order.id] = order
        return order

    def process_pending_orders(self, current_bar: Bar, indicator_dict: Dict[str, float]):
        """
        处理所有待撮合的订单。在每个K线数据到来时调用。
        """
        order_ids_to_process = list(self.pending_orders.keys())

        for order_id in order_ids_to_process:
            if order_id not in self.pending_orders:
                continue

            order = self.pending_orders[order_id]

            if order.symbol != current_bar.symbol:
                continue

            trade = self._execute_single_order(order, current_bar)
            if trade:
                self.trade_log.append(trade)

                if trade.is_open_trade:
                    self.indicator_dict = indicator_dict
                elif trade.is_close_trade:
                    trade.indicator_dict = self.indicator_dict.copy()



    def _execute_single_order(self, order: Order, current_bar: Bar) -> Optional[Trade]:
        """
        内部方法：尝试执行单个订单，并处理资金和持仓变化。
        由 send_order 或 process_pending_orders 调用。
        """
        if order.direction == "CANCEL":
            success = self.cancel_order(order.id)
            if success:
                pass
            return None

        symbol = order.symbol
        volume = order.volume

        fill_price = self._calculate_fill_price(order, current_bar)
        if fill_price <= 0:
            return None

        trade_value = volume * fill_price
        commission = trade_value * self.commission_rate

        current_position = self.positions.get(symbol, 0)
        current_average_cost = self.average_costs.get(symbol, 0.0)

        realized_pnl = 0.0

        is_trade_a_close_operation = False
        is_trade_an_open_operation = False

        if order.direction in ["CLOSE_LONG", "CLOSE_SHORT"]:
            is_trade_a_close_operation = True
        elif order.direction == "BUY" and current_position < 0:
            is_trade_a_close_operation = True
        elif order.direction == "SELL" and current_position > 0:
            is_trade_a_close_operation = True

        if order.direction == "BUY":
            if current_position >= 0 or (
                current_position < 0 and (current_position + volume) > 0
            ):
                is_trade_an_open_operation = True
        elif order.direction == "SELL":
            if current_position <= 0 or (
                current_position > 0 and (current_position - volume) < 0
            ):
                is_trade_an_open_operation = True

        actual_execution_direction = ""
        if order.direction == "BUY" or order.direction == "CLOSE_SHORT":
            actual_execution_direction = "BUY"
        elif order.direction == "SELL" or order.direction == "CLOSE_LONG":
            actual_execution_direction = "SELL"
        else:
            print(
                f"[{current_bar.datetime}] 模拟器: 收到未知订单方向 {order.direction} for Order ID: {order.id}. 订单未处理。"
            )
            if order.id in self.pending_orders:
                del self.pending_orders[order.id]
            return None

        temp_cash = self.cash
        temp_positions = self.positions.copy()
        temp_average_costs = self.average_costs.copy()

        if actual_execution_direction == "BUY":
            if current_position >= 0:
                required_cash = trade_value + commission
                if temp_cash < required_cash:
                    # print(
                    #     f"[{current_bar.datetime}] 模拟器: 资金不足 (开多), 无法执行买入 {volume} {symbol} @ {fill_price:.2f}. 需要: {required_cash:.2f}, 当前: {temp_cash:.2f}"
                    # )
                    if order.id in self.pending_orders:
                        del self.pending_orders[order.id]
                    return None

                temp_cash -= required_cash
                new_total_cost = (
                    temp_average_costs.get(symbol, 0.0) * temp_positions.get(symbol, 0)
                ) + (fill_price * volume)
                new_total_volume = temp_positions.get(symbol, 0) + volume
                temp_average_costs[symbol] = (
                    new_total_cost / new_total_volume if new_total_volume > 0 else 0.0
                )
                temp_positions[symbol] = new_total_volume

            else:  # 当前持有空仓 (平空) - 平仓交易
                pnl_per_share = current_average_cost - fill_price
                realized_pnl = pnl_per_share * volume

                temp_cash -= commission
                temp_cash -= trade_value
                temp_cash += realized_pnl

                temp_positions[symbol] += volume
                if temp_positions[symbol] == 0:
                    del temp_positions[symbol]
                    if symbol in temp_average_costs:
                        del temp_average_costs[symbol]
                elif current_position < 0 and temp_positions[symbol] > 0:
                    temp_average_costs[symbol] = fill_price

        elif actual_execution_direction == "SELL":
            if current_position <= 0:  # 当前持有空仓或无仓位 (开空)
                if temp_cash < commission:
                    # print(
                    #     f"[{current_bar.datetime}] 模拟器: 资金不足 (开空佣金), 无法执行卖出 {volume} {symbol} @ {fill_price:.2f}. 佣金: {commission:.2f}, 当前: {temp_cash:.2f}"
                    # )
                    if order.id in self.pending_orders:
                        del self.pending_orders[order.id]
                    return None

                temp_cash -= commission
                temp_cash += trade_value  # 修正点：开空时将卖出资金计入现金

                existing_abs_volume = abs(temp_positions.get(symbol, 0))
                existing_abs_cost = (
                    temp_average_costs.get(symbol, 0.0) * existing_abs_volume
                )

                new_total_value = existing_abs_cost + (fill_price * volume)
                new_total_volume = existing_abs_volume + volume

                temp_average_costs[symbol] = (
                    new_total_value / new_total_volume if new_total_volume > 0 else 0.0
                )
                temp_positions[symbol] = -new_total_volume

            else:  # 当前持有多仓 (平多) - 平仓交易
                pnl_per_share = fill_price - current_average_cost
                realized_pnl = pnl_per_share * volume

                temp_cash -= commission
                temp_cash += trade_value
                temp_cash += realized_pnl

                temp_positions[symbol] -= volume
                if temp_positions[symbol] == 0:
                    del temp_positions[symbol]
                    if symbol in temp_average_costs:
                        del temp_average_costs[symbol]
                elif current_position > 0 and temp_positions[symbol] < 0:
                    temp_average_costs[symbol] = fill_price

        self.cash = temp_cash
        self.positions = temp_positions
        self.average_costs = temp_average_costs

        executed_trade = Trade(
            order_id=order.id,
            fill_time=current_bar.datetime,
            symbol=symbol,
            direction=order.direction,
            volume=volume,
            price=fill_price,
            commission=commission,
            cash_after_trade=self.cash,
            positions_after_trade=self.positions.copy(),
            realized_pnl=realized_pnl,
            is_open_trade=is_trade_an_open_operation,
            is_close_trade=is_trade_a_close_operation,
        )

        if order.id in self.pending_orders:
            del self.pending_orders[order.id]

        return executed_trade

    def cancel_order(self, order_id: str) -> bool:
        if order_id in self.pending_orders:
            del self.pending_orders[order_id]
            return True
        return False

    def force_close_all_positions_for_symbol(
        self, symbol_to_close: str, closing_bar: Bar
    ) -> List[Trade]:
        closed_trades: List[Trade] = []

        if symbol_to_close in self.positions and self.positions[symbol_to_close] != 0:
            volume_to_close = self.positions[symbol_to_close]

            direction = "CLOSE_LONG" if volume_to_close > 0 else "CLOSE_SHORT"

            rollover_order = Order(
                id=f"FORCE_CLOSE_{symbol_to_close}_{closing_bar.datetime.strftime('%Y%m%d%H%M%S%f')}",
                symbol=symbol_to_close,
                direction=direction,
                volume=abs(volume_to_close),
                price_type="MARKET",
                limit_price=None,
                submitted_time=closing_bar.datetime,
            )
            # 这里直接调用 _execute_single_order 确保强制平仓立即成交
            trade = self._execute_single_order(rollover_order, closing_bar)
            if trade:
                closed_trades.append(trade)
            else:
                print(
                    f"[{closing_bar.datetime}] 警告: 强制平仓 {symbol_to_close} 失败！"
                )

        return closed_trades

    def cancel_all_pending_orders_for_symbol(self, symbol_to_cancel: str) -> int:
        cancelled_count = 0
        order_ids_to_cancel = [
            order_id
            for order_id, order in self.pending_orders.items()
            if order.symbol == symbol_to_cancel
        ]
        for order_id in order_ids_to_cancel:
            if self.cancel_order(order_id):
                cancelled_count += 1
        return cancelled_count

    def get_pending_orders(self) -> Dict[str, Order]:
        return self.pending_orders.copy()

    def get_portfolio_value(self, current_bar: Bar) -> float:
        total_value = self.cash
        for symbol, quantity in self.positions.items():
            if symbol == current_bar.symbol:
                total_value += quantity * current_bar.open
            else:
                print(
                    f"[{current_bar.datetime}] 警告：持仓中存在非当前K线合约 {symbol}，无法准确计算其市值。"
                )
                pass
        return total_value

    def get_current_positions(self) -> Dict[str, int]:
        return self.positions.copy()

    def get_trade_history(self) -> List[Trade]:
        return self.trade_log.copy()

    def reset(
        self,
        new_initial_capital: float = None,
        new_initial_positions: Dict[str, int] = None,
        new_initial_average_costs: Dict[str, float] = None,
    ) -> None:  # 新增参数
        print("ExecutionSimulator: 重置状态。")
        self.cash = (
            new_initial_capital
            if new_initial_capital is not None
            else self.initial_capital
        )
        self.positions = (
            new_initial_positions.copy() if new_initial_positions is not None else {}
        )
        # 修正：重置时也应该考虑传入初始平均成本
        self.average_costs = (
            new_initial_average_costs.copy()
            if new_initial_average_costs is not None
            else {}
        )
        if self.positions and not new_initial_average_costs:
            print(
                f"[{datetime.now()}] 警告: 重置时提供了初始持仓但未提供初始平均成本，这些持仓的成本默认为0.0。"
            )
            for symbol, qty in self.positions.items():
                if symbol not in self.average_costs:
                    self.average_costs[symbol] = 0.0

        self.trade_log = []
        self.pending_orders = {}
        self._current_time = None

    def get_average_position_price(self, symbol: str) -> Optional[float]:
        if symbol in self.positions and self.positions[symbol] != 0:
            return self.average_costs.get(symbol)
        return None