From d7ba8a83448cf7935c21a754aad1be3068d7f49c Mon Sep 17 00:00:00 2001 From: zhoujie Date: Sat, 6 Jun 2026 16:40:15 +0800 Subject: [PATCH] =?UTF-8?q?=E4=BD=BF=E7=94=A8ctpplus=EF=BC=8C=E7=84=B6?= =?UTF-8?q?=E5=90=8E=E5=A2=9E=E5=8A=A0=E5=9B=9E=E6=B5=8B=E6=A8=A1=E5=9D=97?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../BACKTEST_INVESTOR/td.con/DialogRsp.con | Bin 0 -> 6 bytes .../BACKTEST_INVESTOR/td.con/QueryRsp.con | Bin 0 -> 6 bytes .../BACKTEST_INVESTOR/td.con/TradingDay.con | Bin 0 -> 6 bytes 1.交易策略/4.orderflow/backtest.py | 836 ++++++++++ .../backtest_results/IM2606_equity.csv | 1337 +++++++++++++++ .../backtest_results/IM2606_metrics.json | 14 + .../backtest_results/IM2606_trades.csv | 18 + 1.交易策略/4.orderflow/config.py | 42 +- .../4.orderflow/log/223828/md.con/DialogRsp.con | Bin 0 -> 6 bytes .../4.orderflow/log/223828/md.con/QueryRsp.con | Bin 0 -> 6 bytes .../4.orderflow/log/223828/md.con/TradingDay.con | Bin 0 -> 6 bytes .../4.orderflow/log/223828/td.con/DialogRsp.con | Bin 0 -> 6 bytes .../4.orderflow/log/223828/td.con/Private.con | Bin 0 -> 6 bytes .../4.orderflow/log/223828/td.con/Public.con | Bin 0 -> 6 bytes .../4.orderflow/log/223828/td.con/QueryRsp.con | Bin 0 -> 6 bytes .../4.orderflow/log/223828/td.con/TradingDay.con | Bin 0 -> 6 bytes 1.交易策略/4.orderflow/readme.md | 161 ++ 1.交易策略/4.orderflow/run.py | 122 +- .../4.orderflow/traderdata/IM2606_ofdata.json | 1442 +++++++++++++++++ .../4.orderflow/traderdata/IM2606_ofdata_2.json | 1 + .../4.orderflow/traderdata/IM2606_tick.csv | 276 ++++ 21 files changed, 4197 insertions(+), 52 deletions(-) create mode 100644 1.交易策略/4.orderflow/BACKTEST_INVESTOR/td.con/DialogRsp.con create mode 100644 1.交易策略/4.orderflow/BACKTEST_INVESTOR/td.con/QueryRsp.con create mode 100644 1.交易策略/4.orderflow/BACKTEST_INVESTOR/td.con/TradingDay.con create mode 100644 1.交易策略/4.orderflow/backtest.py create mode 100644 1.交易策略/4.orderflow/backtest_results/IM2606_equity.csv create mode 100644 1.交易策略/4.orderflow/backtest_results/IM2606_metrics.json create mode 100644 1.交易策略/4.orderflow/backtest_results/IM2606_trades.csv create mode 100644 1.交易策略/4.orderflow/log/223828/md.con/DialogRsp.con create mode 100644 1.交易策略/4.orderflow/log/223828/md.con/QueryRsp.con create mode 100644 1.交易策略/4.orderflow/log/223828/md.con/TradingDay.con create mode 100644 1.交易策略/4.orderflow/log/223828/td.con/DialogRsp.con create mode 100644 1.交易策略/4.orderflow/log/223828/td.con/Private.con create mode 100644 1.交易策略/4.orderflow/log/223828/td.con/Public.con create mode 100644 1.交易策略/4.orderflow/log/223828/td.con/QueryRsp.con create mode 100644 1.交易策略/4.orderflow/log/223828/td.con/TradingDay.con create mode 100644 1.交易策略/4.orderflow/readme.md create mode 100644 1.交易策略/4.orderflow/traderdata/IM2606_ofdata.json create mode 100644 1.交易策略/4.orderflow/traderdata/IM2606_ofdata_2.json create mode 100644 1.交易策略/4.orderflow/traderdata/IM2606_tick.csv diff --git a/1.交易策略/4.orderflow/BACKTEST_INVESTOR/td.con/DialogRsp.con b/1.交易策略/4.orderflow/BACKTEST_INVESTOR/td.con/DialogRsp.con new file mode 100644 index 0000000000000000000000000000000000000000..ab2c6846789c5681cd5544fd3e407c6648761ab9 GIT binary patch literal 6 KcmZQz009611^@v7 literal 0 HcmV?d00001 diff --git a/1.交易策略/4.orderflow/BACKTEST_INVESTOR/td.con/QueryRsp.con b/1.交易策略/4.orderflow/BACKTEST_INVESTOR/td.con/QueryRsp.con new file mode 100644 index 0000000000000000000000000000000000000000..ab2c6846789c5681cd5544fd3e407c6648761ab9 GIT binary patch literal 6 KcmZQz009611^@v7 literal 0 HcmV?d00001 diff --git a/1.交易策略/4.orderflow/BACKTEST_INVESTOR/td.con/TradingDay.con b/1.交易策略/4.orderflow/BACKTEST_INVESTOR/td.con/TradingDay.con new file mode 100644 index 0000000000000000000000000000000000000000..ab2c6846789c5681cd5544fd3e407c6648761ab9 GIT binary patch literal 6 KcmZQz009611^@v7 literal 0 HcmV?d00001 diff --git a/1.交易策略/4.orderflow/backtest.py b/1.交易策略/4.orderflow/backtest.py new file mode 100644 index 0000000..2856eb6 --- /dev/null +++ b/1.交易策略/4.orderflow/backtest.py @@ -0,0 +1,836 @@ +""" +订单流回测模块 +支持两种回测模式： +1. Mode ofdata:读取 ofdata.json 历史数据重放 +2. Mode tick: 读取原始 tick CSV 重放完整流程 +""" +import os +import json +import csv +import pandas as pd +import numpy as np +from datetime import datetime, timedelta +from dataclasses import dataclass, field +from typing import Dict, List, Optional, Tuple + +from config import SYSTEM_CONFIG, TRADING_PARAMS + + +# ============ 隔离数据存储 ============ + +class BacktestDataStore: + """回测数据存储（隔离实例，避免与实盘共享状态）""" + tickdata = {} + quote = {} + ofdata = {} + trade_dfs = {} + prev_volume = {} + last_tick = {} + + +# ============ 交易记录数据结构 ============ + +@dataclass +class TradeRecord: + """交易记录""" + trade_id: int + entry_datetime: str + entry_price: float + direction: str # "long" / "short" + exit_datetime: Optional[str] = None + exit_price: Optional[float] = None + lots: int = 1 + pnl: float = 0.0 + pnl_pct: float = 0.0 + status: str = "open" # "open" / "closed" + + +# ============ 权益跟踪器 ============ + +class EquityTracker: + """跟踪权益曲线和回撤""" + + def __init__(self, initial_equity: float = 100000.0): + self.initial_equity = initial_equity + self.current_equity = initial_equity + self.peak_equity = initial_equity + self.max_drawdown = 0.0 + self.max_drawdown_pct = 0.0 + + # 权益曲线记录 + self.equity_curve = [] # [(datetime, equity, drawdown, drawdown_pct), ...] + self.trades = [] # TradeRecord list + self.trade_id_counter = 0 + + def update_equity(self, datetime_str: str, price: float, position: int): + """更新权益曲线（每个 bar 更新一次）""" + if position != 0: + # 有持仓时不计入权益（按结算价计算 unrealized P&L） + return + + # 无持仓时权益不变 + drawdown = self.current_equity - self.peak_equity + drawdown_pct = (drawdown / self.peak_equity * 100) if self.peak_equity > 0 else 0 + + self.equity_curve.append({ + "datetime": datetime_str, + "equity": self.current_equity, + "drawdown": drawdown, + "drawdown_pct": round(drawdown_pct, 2) + }) + + def record_trade(self, trade: TradeRecord): + """记录交易""" + self.trades.append(trade) + + def close_trade(self, trade_id: int, exit_datetime: str, exit_price: float, + multiplier: float, lots: int): + """平仓并计算 P&L""" + for trade in self.trades: + if trade.trade_id == trade_id and trade.status == "open": + trade.exit_datetime = exit_datetime + trade.exit_price = exit_price + trade.status = "closed" + + if trade.direction == "long": + trade.pnl = (exit_price - trade.entry_price) * multiplier * lots + else: # short + trade.pnl = (trade.entry_price - exit_price) * multiplier * lots + + trade.pnl_pct = (trade.pnl / self.initial_equity * 100) + + # 更新权益 + self.current_equity += trade.pnl + if self.current_equity > self.peak_equity: + self.peak_equity = self.current_equity + + return trade + return None + + def get_metrics(self) -> dict: + """计算性能指标""" + closed_trades = [t for t in self.trades if t.status == "closed"] + winning_trades = [t for t in closed_trades if t.pnl > 0] + losing_trades = [t for t in closed_trades if t.pnl <= 0] + + total_return = self.current_equity - self.initial_equity + total_return_pct = (total_return / self.initial_equity * 100) + + # 计算最大回撤 + equity_df = pd.DataFrame(self.equity_curve) + if not equity_df.empty and "equity" in equity_df.columns: + rolling_max = equity_df["equity"].cummax() + drawdowns = equity_df["equity"] - rolling_max + self.max_drawdown = drawdowns.min() + self.max_drawdown_pct = (drawdowns.min() / rolling_max.max() * 100) if rolling_max.max() > 0 else 0 + + avg_win = np.mean([t.pnl for t in winning_trades]) if winning_trades else 0 + avg_loss = np.mean([t.pnl for t in losing_trades]) if losing_trades else 0 + total_win = sum([t.pnl for t in winning_trades]) + total_loss = abs(sum([t.pnl for t in losing_trades])) + + return { + "total_return": round(total_return, 2), + "total_return_pct": round(total_return_pct, 2), + "max_drawdown": round(self.max_drawdown, 2), + "max_drawdown_pct": round(self.max_drawdown_pct, 2), + "win_rate": round(len(winning_trades) / len(closed_trades), 4) if closed_trades else 0, + "total_trades": len(closed_trades), + "winning_trades": len(winning_trades), + "losing_trades": len(losing_trades), + "avg_win": round(avg_win, 2), + "avg_loss": round(avg_loss, 2), + "profit_factor": round(total_win / total_loss, 2) if total_loss > 0 else 0, + "final_equity": round(self.current_equity, 2), + } + + def save_results(self, symbol: str): + """保存回测结果到文件""" + results_dir = SYSTEM_CONFIG["backtest_results_dir"] + os.makedirs(results_dir, exist_ok=True) + + prefix = f"{results_dir}/{symbol}" + + # 保存权益曲线 CSV + if self.equity_curve: + equity_df = pd.DataFrame(self.equity_curve) + equity_df.to_csv(f"{prefix}_equity.csv", index=False) + + # 保存交易记录 CSV + if self.trades: + trades_data = [] + for t in self.trades: + trades_data.append({ + "trade_id": t.trade_id, + "entry_datetime": t.entry_datetime, + "entry_price": t.entry_price, + "direction": t.direction, + "exit_datetime": t.exit_datetime or "", + "exit_price": t.exit_price or "", + "lots": t.lots, + "pnl": round(t.pnl, 2), + "pnl_pct": round(t.pnl_pct, 2), + "status": t.status + }) + trades_df = pd.DataFrame(trades_data) + trades_df.to_csv(f"{prefix}_trades.csv", index=False) + + # 保存性能指标 JSON + metrics = self.get_metrics() + with open(f"{prefix}_metrics.json", 'w', encoding='utf-8') as f: + json.dump(metrics, f, indent=2, ensure_ascii=False) + + +# ============ 回测交易执行器 ============ + +class BacktestTrader: + """回测交易执行器（复用信号计算逻辑）""" + + def __init__(self, param_dict: dict, equity_tracker: EquityTracker): + self.param_dict = param_dict + self.equity_tracker = equity_tracker + self.current_symbol = " " + + def set_symbol(self, symbol: str): + """设置当前合约""" + self.current_symbol = symbol + + def execute_open_long(self, trade_df: pd.DataFrame, param, current_price: float): + """开多信号 — 记录待买入价格和对应的止损价（模拟实盘 pending order模式）""" + if param.position != 0: + return None + + param.pending_long_price = trade_df['dj_price_high'].iloc[-1] if 'dj_price_high' in trade_df.columns else current_price + param.pending_sl_long_price = trade_df['dj_price_low'].iloc[-1] if 'dj_price_low' in trade_df.columns else 0 + print(f"开多信号: 记录待买入价={param.pending_long_price}, datetime={trade_df['datetime'].iloc[-1]}") + + def execute_open_short(self, trade_df: pd.DataFrame, param, current_price: float): + """开空信号 — 记录待卖出价格和对应的止损价（模拟实盘 pending order 模式）""" + if param.position != 0: + return None + + param.pending_short_price = trade_df['dj_price_low'].iloc[-1] if 'dj_price_low' in trade_df.columns else current_price + param.pending_sl_short_price = trade_df['dj_price_high'].iloc[-1] if 'dj_price_high' in trade_df.columns else 0 + print(f"开空信号: 记录待卖出价={param.pending_short_price}, datetime={trade_df['datetime'].iloc[-1]}") + + def check_pending_orders(self, trade_df: pd.DataFrame, param, current_price: float): + """检查并执行待成交订单（模拟实盘 check_pending_orders）""" + # 检查待开多订单（价格回落到堆积区间高价时买入） + if param.position == 0 and param.pending_long_price > 0: + if current_price <= param.pending_long_price: + price = current_price + param.price_offset + self._do_open_long(trade_df, param, price) + param.pending_long_price = 0 + param.pending_sl_long_price = 0 + + # 检查待开空订单（价格反弹到堆积区间低价时卖出） + if param.position == 0 and param.pending_short_price > 0: + if current_price >= param.pending_short_price: + price = current_price - param.price_offset + self._do_open_short(trade_df, param, price) + param.pending_short_price = 0 + param.pending_sl_short_price = 0 + + def _do_open_long(self, trade_df: pd.DataFrame, param, price: float): + """执行开多（内部方法）""" + trade_id = self.equity_tracker.trade_id_counter + 1 + self.equity_tracker.trade_id_counter += 1 + + trade = TradeRecord( + trade_id=trade_id, + entry_datetime=trade_df["datetime"].iloc[-1], + entry_price=price, + direction="long", + lots=param.lots, + status="open" + ) + self.equity_tracker.record_trade(trade) + + param.position = 1 + param.sl_long_price = param.pending_sl_long_price if param.pending_sl_long_price > 0 else trade_df['dj_price_low'].iloc[-1] if 'dj_price_low' in trade_df.columns else 0 + print(f"执行开多: price={price}, sl={param.sl_long_price}, datetime={trade_df['datetime'].iloc[-1]}") + + return trade + + def _do_open_short(self, trade_df: pd.DataFrame, param, price: float): + """执行开空（内部方法）""" + trade_id = self.equity_tracker.trade_id_counter + 1 + self.equity_tracker.trade_id_counter += 1 + + trade = TradeRecord( + trade_id=trade_id, + entry_datetime=trade_df["datetime"].iloc[-1], + entry_price=price, + direction="short", + lots=param.lots, + status="open" + ) + self.equity_tracker.record_trade(trade) + + param.position = -1 + param.sl_short_price = param.pending_sl_short_price if param.pending_sl_short_price > 0 else trade_df['dj_price_high'].iloc[-1] if 'dj_price_high' in trade_df.columns else 0 + print(f"执行开空: price={price}, sl={param.sl_short_price}, datetime={trade_df['datetime'].iloc[-1]}") + + return trade + + def execute_close_long(self, trade_df: pd.DataFrame, param, current_price: float): + """平多""" + if param.position != 1: + return None + + #找到对应的 open trade + for trade in self.equity_tracker.trades: + if trade.direction == "long" and trade.status == "open": + trade.exit_datetime = trade_df["datetime"].iloc[-1] + trade.exit_price = current_price + trade.status = "closed" + + multiplier = SYSTEM_CONFIG["contract_multiplier"].get( + param.symbol, 1 + ) + trade.pnl = (current_price - trade.entry_price) * multiplier * param.lots + trade.pnl_pct = (trade.pnl / self.equity_tracker.initial_equity * 100) + + self.equity_tracker.current_equity += trade.pnl + if self.equity_tracker.current_equity > self.equity_tracker.peak_equity: + self.equity_tracker.peak_equity = self.equity_tracker.current_equity + + param.position = 0 + param.sl_long_price = 0 + param.pending_long_price = 0 + + return trade + return None + + def execute_close_short(self, trade_df: pd.DataFrame, param, current_price: float): + """平空""" + if param.position != -1: + return None + + for trade in self.equity_tracker.trades: + if trade.direction == "short" and trade.status == "open": + trade.exit_datetime = trade_df["datetime"].iloc[-1] + trade.exit_price = current_price + trade.status = "closed" + + multiplier = SYSTEM_CONFIG["contract_multiplier"].get( + param.symbol, 1 + ) + trade.pnl = (trade.entry_price - current_price) * multiplier * param.lots + trade.pnl_pct = (trade.pnl / self.equity_tracker.initial_equity * 100) + + self.equity_tracker.current_equity += trade.pnl + if self.equity_tracker.current_equity > self.equity_tracker.peak_equity: + self.equity_tracker.peak_equity = self.equity_tracker.current_equity + + param.position = 0 + param.sl_short_price = 0 + param.pending_short_price = 0 + + return trade + return None + + def check_stop_loss(self, trade_df: pd.DataFrame, param, current_price: float) -> bool: + """检查止损""" + if param.position > 0 and param.sl_long_price > 0: + if current_price < param.sl_long_price: + self.execute_close_long(trade_df, param, current_price) + return True + elif param.position < 0 and param.sl_short_price > 0: + if current_price > param.sl_short_price: + self.execute_close_short(trade_df, param, current_price) + return True + return False + + def calculate_signals(self, trade_df: pd.DataFrame, param) -> Tuple[bool, bool, float, float]: + """计算交易信号（复用 OrderFlowTrader 逻辑）""" + if len(trade_df) < 2: + return False, False, 0, 0 + + dj_last = trade_df["dj"].iloc[-1] + delta_last = trade_df["delta"].iloc[-1] + + bull_signal = dj_last >= param.accumulation_threshold and \ + delta_last >= param.delta_threshold + bear_signal = dj_last <= -param.accumulation_threshold and \ + delta_last <= -param.delta_threshold + + return bull_signal, bear_signal, dj_last, delta_last + + def calculate_delta_cumulative(self, trade_df: pd.DataFrame, param): + """计算 Delta 累计""" + if trade_df["delta"].dtype == object: + trade_df["delta"] = trade_df["delta"].astype(float) + + trade_df["datetime"] = pd.to_datetime(trade_df["datetime"]) + + last_dt = pd.to_datetime(trade_df["datetime"].iloc[-1]) + hour = last_dt.hour + if hour >= 21: + trading_day = (last_dt + pd.Timedelta(days=1)).date() + elif hour < 15: + trading_day = last_dt.date() + else: + trading_day = last_dt.date() + + trade_df["trading_day"] = str(trading_day) + trade_df["delta累计"] = trade_df.groupby("trading_day")["delta"].cumsum() + + trade_df["datetime"] = trade_df["datetime"].dt.strftime("%Y-%m-%d %H:%M:%S") + + +# ============ ofdata 回放器 (Mode 1) ============ + +class OfdataReplayer: + """Mode 1: 回放 ofdata.json 数据""" + + def __init__(self, backtester: 'Backtester', symbol: str): + self.backtester = backtester + self.symbol = symbol + self.param = backtester.param_dict[symbol] + self.trader = backtester.trader + self.equity_tracker = backtester.equity_tracker + self.data_store = backtester.data_store + + def replay(self): + """执行 ofdata 回放""" + data_dir = SYSTEM_CONFIG["data_dir"] + json_path = f"{data_dir}/{self.symbol}_ofdata.json" + + if not os.path.exists(json_path): + print(f"ofdata 文件不存在: {json_path}") + return + + # 加载 ofdata.json + trade_df = pd.read_json(json_path, lines=True) + if trade_df.empty: + print("ofdata 数据为空") + return + + print(f"加载 ofdata: {json_path}, 共 {len(trade_df)} 条") + + self.data_store.trade_dfs[self.symbol] = trade_df.copy() + self.trader.set_symbol(self.symbol) + + param = self.param + param.position = 0 + param.processed_rows = 0 + + # 逐行处理 + for idx in range(len(trade_df)): + # 构建单行 DataFrame + row_df = trade_df.iloc[[idx]].copy() + current_dt = row_df["datetime"].iloc[0] + current_price = row_df["close"].iloc[0] + + # 计算 delta 累计 + if idx > 0: + # 重新计算到当前行 + temp_df = trade_df.iloc[:idx+1].copy() + self.trader.calculate_delta_cumulative(temp_df, param) + signal_df = temp_df + else: + signal_df = trade_df.iloc[[idx]].copy() + + # 更新 DataStore + self.data_store.trade_dfs[self.symbol] = trade_df.iloc[[idx]].copy() + + # 检查止损（已有持仓的情况下） + self.trader.check_stop_loss(signal_df, param, current_price) + + # 检查待成交订单（价格触达 pending 则开仓） + self.trader.check_pending_orders(signal_df, param, current_price) + + # 计算信号（仅在无持仓时触发 pending order） + bull_signal, bear_signal, dj_last, delta_last = self.trader.calculate_signals(signal_df, param) + + if bull_signal or bear_signal: + # 平仓信号 + if param.position < 0 and (bear_signal or bull_signal): + self.trader.execute_close_short(row_df, param, current_price) + elif param.position > 0 and (bull_signal or bear_signal): + self.trader.execute_close_long(row_df, param, current_price) + + # 开仓信号（设置 pending price，不立即开仓） + if bull_signal and param.position == 0: + self.trader.execute_open_long(row_df, param, current_price) + if bear_signal and param.position == 0: + self.trader.execute_open_short(row_df, param, current_price) + + # 更新权益曲线（每行） + self.equity_tracker.update_equity(current_dt, current_price, param.position) + + param.processed_rows = idx + 1 + + print(f"回放完成: {len(trade_df)} 条, 最终持仓: {param.position}") + + +# ============ tick 回放器 (Mode 2) ============ + +class TickReplayer: + """Mode 2: 回放原始 tick CSV 数据""" + + def __init__(self, backtester: 'Backtester', symbol: str): + self.backtester = backtester + self.symbol = symbol + self.param = backtester.param_dict[symbol] + self.trader = backtester.trader + self.equity_tracker = backtester.equity_tracker + self.data_store = backtester.data_store + + # tick CSV 路径 + data_dir = SYSTEM_CONFIG["data_dir"] + self.tick_csv_path = f"{data_dir}/{symbol}_tick.csv" + + def replay(self): + """执行 tick 回放""" + if not os.path.exists(self.tick_csv_path): + print(f"tick CSV 不存在: {self.tick_csv_path}") + return + + # 读取 tick CSV + tick_df = pd.read_csv(self.tick_csv_path) + if tick_df.empty: + print("tick 数据为空") + return + + print(f"加载 tick: {self.tick_csv_path}, 共 {len(tick_df)} 条") + + self.trader.set_symbol(self.symbol) + param = self.param + param.position = 0 + param.processed_rows = 0 + + prev_bartime = None + + for idx, row in tick_df.iterrows(): + # 构建 tick 数据 + tick_data = { + "InstrumentID": row["InstrumentID"].encode() if isinstance(row["InstrumentID"], str) else row["InstrumentID"], + "ActionDay": str(row["ActionDay"]).encode() if isinstance(row["ActionDay"], (int, str)) else row["ActionDay"], + "UpdateTime": str(row["UpdateTime"]).encode() if isinstance(row["UpdateTime"], str) else row["UpdateTime"], + "UpdateMillisec": int(row["UpdateMillisec"]) if "UpdateMillisec" in row else 0, + "LastPrice": float(row["LastPrice"]), + "Volume": int(row["Volume"]), + "BidPrice1": float(row["BidPrice1"]), + "BidVolume1": int(row["BidVolume1"]), + "AskPrice1": float(row["AskPrice1"]), + "AskVolume1": int(row["AskVolume1"]), + "UpperLimitPrice": float(row["UpperLimitPrice"]) if "UpperLimitPrice" in row else 0, + "LowerLimitPrice": float(row["LowerLimitPrice"]) if "LowerLimitPrice" in row else 0, + "TradingDay": str(row["TradingDay"]).encode() if isinstance(row["TradingDay"], str) else row["TradingDay"], + "Turnover": float(row["Turnover"]) if "Turnover" in row else 0, + "OpenInterest": int(row["OpenInterest"]) if "OpenInterest" in row else 0, + } + + # 处理 tick + self._process_tick(tick_data, param, prev_bartime) + prev_bartime = self.data_store.tickdata.get(self.symbol, {}).get("bartime", prev_bartime) + + print(f"tick 回放完成: {len(tick_df)} 条, 最终持仓: {param.position}") + + def _process_tick(self, data: dict, param, prev_bartime: str): + """处理单个 tick（复用 run.py 的 tick 处理逻辑）""" + instrument_id = data["InstrumentID"].decode() if isinstance(data["InstrumentID"], bytes) else data["InstrumentID"] + action_day = str(data["ActionDay"].decode() if isinstance(data["ActionDay"], bytes) else data["ActionDay"]) + update_time = str(data["UpdateTime"].decode() if isinstance(data["UpdateTime"], bytes) else data["UpdateTime"]) + + action_day_fmt = f"{action_day[:4]}-{action_day[4:6]}-{action_day[6:]}" + created_at = datetime.strptime( + f"{action_day_fmt} {update_time}.{data['UpdateMillisec']}", + "%Y-%m-%d %H:%M:%S.%f" + ) + + # 计算瞬时成交量 + prev_vol = self.data_store.prev_volume.get(instrument_id, 0) + curr_vol = int(data["Volume"]) + last_vol = curr_vol - prev_vol if prev_vol != 0 else 0 + self.data_store.prev_volume[instrument_id] = curr_vol + + if last_vol <= 0: + return + + # 构建 tick + tick = { + "symbol": instrument_id, + "created_at": created_at, + "price": float(data["LastPrice"]), + "last_volume": last_vol, + "bid_p": float(data["BidPrice1"]), + "bid_v": int(data["BidVolume1"]), + "ask_p": float(data["AskPrice1"]), + "ask_v": int(data["AskVolume1"]), + "upper_limit": float(data["UpperLimitPrice"]), + "lower_limit": float(data["LowerLimitPrice"]), + "trading_day": data["TradingDay"].decode() if isinstance(data["TradingDay"], bytes) else str(data["TradingDay"]), + "cum_volume": curr_vol, + "cum_amount": float(data["Turnover"]), + "cum_position": int(data["OpenInterest"]), + } + self._on_tick(tick, param, prev_bartime) + + def _on_tick(self, tick: dict, param, prev_bartime: str): + """处理 tick（简化版）""" + tsymbol = tick["symbol"] + + # 获取上条 tick + prev_tick = self.data_store.last_tick.get(tsymbol) + if prev_tick: + bid_p = prev_tick["bid_p"] + ask_p = prev_tick["ask_p"] + bid_v = prev_tick["bid_v"] + ask_v = prev_tick["ask_v"] + else: + bid_p = tick["bid_p"] + ask_p = tick["ask_p"] + bid_v = tick["bid_v"] + ask_v = tick["ask_v"] + + self.data_store.last_tick[tsymbol] = tick + + timetick = tick["created_at"].strftime("%Y-%m-%d %H:%M:%S.%f")[:-3] + + # 构建 DataFrame + tick_dt = pd.DataFrame({ + "datetime": timetick, + "symbol": tick["symbol"], + "mainsym": tick["symbol"].rstrip("0123456789").upper(), + "lastprice": tick["price"], + "vol": tick["last_volume"], + "bid_p": bid_p, + "ask_p": ask_p, + "bid_v": bid_v, + "ask_v": ask_v, + }, index=[0]) + + self._tickdata(tick_dt, tsymbol, param, prev_bartime) + + def _tickdata(self, df: pd.DataFrame, symbol: str, param, prev_bartime: str): + """K线聚合（简化版）""" + from run import OrderFlowTrader + + tickdata = df.copy() + tickdata["bartime"] = pd.to_datetime(tickdata["datetime"]) + + rdf = self.data_store.tickdata.get(symbol) + + if rdf is not None: + rdftm = pd.to_datetime(rdf["bartime"][0]).strftime("%Y-%m-%d %H:%M:%S") + now_bartime = pd.to_datetime(tickdata["bartime"][0]).strftime("%Y-%m-%d %H:%M:%S") + + if now_bartime > rdftm: + # 新 K 线开始 + with type('Lock', (), {'__enter__': lambda s: None, '__exit__': lambda s, *a: None})(): + of = self.data_store.ofdata.pop(symbol, None) + if of is not None: + # 追加到 trade_dfs + existing = self.data_store.trade_dfs.get(symbol) + if existing is None: + self.data_store.trade_dfs[symbol] = of + else: + self.data_store.trade_dfs[symbol] = pd.concat([existing, of], ignore_index=True) + + self.data_store.quote.pop(symbol, None) + self.data_store.tickdata.pop(symbol, None) + + # 处理上一根 K 线的信号 + trade_df = self.data_store.trade_dfs.get(symbol) + if trade_df is not None and len(trade_df) > 0: + last_row = trade_df.iloc[[-1]].copy() + current_price = last_row["close"].iloc[0] + + # 计算 delta 累计 + self.trader.calculate_delta_cumulative(trade_df, param) + + # 检查止损 + self.trader.check_stop_loss(last_row, param, current_price) + + # 计算信号 + bull_signal, bear_signal, dj_last, delta_last = self.trader.calculate_signals(trade_df, param) + + if bull_signal or bear_signal: + if param.position < 0 and (bear_signal or bull_signal): + self.trader.execute_close_short(last_row, param, current_price) + elif param.position > 0 and (bull_signal or bear_signal): + self.trader.execute_close_long(last_row, param, current_price) + if bull_signal and param.position == 0: + self.trader.execute_open_long(last_row, param, current_price) + if bear_signal and param.position == 0: + self.trader.execute_open_short(last_row, param, current_price) + + # 更新权益曲线 + self.equity_tracker.update_equity( + last_row["datetime"].iloc[0], + current_price, + param.position + ) + + # 初始化新 K 线 + tickdata["open"] = tickdata["lastprice"] + tickdata["high"] = tickdata["lastprice"] + tickdata["low"] = tickdata["lastprice"] + tickdata["close"] = tickdata["lastprice"] + tickdata["starttime"] = tickdata["datetime"] + else: + # 同一 K 线 + tickdata["bartime"] = rdf["bartime"] + tickdata["open"] = rdf["open"] + lastprice_val = float(tickdata["lastprice"].values[0]) + tickdata["high"] = max(lastprice_val, float(rdf["high"].values[0])) + tickdata["low"] = min(lastprice_val, float(rdf["low"].values[0])) + tickdata["close"] = tickdata["lastprice"] + tickdata["vol"] = df["vol"].values + rdf["vol"].values + tickdata["starttime"] = rdf["starttime"] + else: + # 首条 tick + tickdata["open"] = tickdata["lastprice"] + tickdata["high"] = tickdata["lastprice"] + tickdata["low"] = tickdata["lastprice"] + tickdata["close"] = tickdata["lastprice"] + tickdata["starttime"] = tickdata["datetime"] + + self.data_store.tickdata[symbol] = tickdata + + # 生成订单流数据 + self._orderflow_df_new(tickdata, symbol, param) + + def _orderflow_df_new(self, tickdata: pd.DataFrame, symbol: str, param): + """生成订单流（简化版）""" + bar_vol = int(tickdata["vol"].values[0]) + bar_close = float(tickdata["close"].values[0]) + bar_open = float(tickdata["open"].values[0]) + bar_low = float(tickdata["low"].values[0]) + bar_high = float(tickdata["high"].values[0]) + dt = pd.to_datetime(tickdata["bartime"].values[0]).strftime("%Y-%m-%d %H:%M:%S") + + bid_p = float(tickdata["bid_p"].values[0]) + ask_p = float(tickdata["ask_p"].values[0]) + last_price = float(tickdata["lastprice"].values[0]) + + bid_dict = {} + ask_dict = {} + + if last_price >= ask_p: + ask_dict[str(last_price)] = ask_dict.get(str(last_price), 0) + bar_vol + if last_price <= bid_p: + bid_dict[str(last_price)] = bid_dict.get(str(last_price), 0) + bar_vol + + # 合并买卖盘 + bid_result, ask_result = self._process_quote(bid_dict, ask_dict, symbol) + + # 价格排序 + price_list = sorted(bid_result.keys()) + ask_list = [ask_result.get(p, 0) for p in price_list] + bid_list = [bid_result.get(p, 0) for p in price_list] + + delta = sum(ask_list) - sum(bid_list) + + # 构建 DataFrame + df = pd.DataFrame({ + "price": [price_list], + "Ask": [ask_list], + "Bid": [bid_list], + }) + df["symbol"] = symbol + df["datetime"] = dt + df["delta"] = delta + df["close"] = bar_close + df["open"] = bar_open + df["high"] = bar_high + df["low"] = bar_low + df["vol"] = bar_vol + df["dj"] = 0 + df["dj_price_high"] = 0 + df["dj_price_low"] = 0 + + self.data_store.ofdata[symbol] = df + + def _process_quote(self, bid_dict: dict, ask_dict: dict, symbol: str): + """合并买卖盘""" + dic = self.data_store.quote.get(symbol) + if dic: + bid_result = dic["bid_result"].copy() + ask_result = dic["ask_result"].copy() + else: + bid_result, ask_result = {}, {} + + price_list = sorted(set(bid_dict.keys()) | set(ask_dict.keys())) + + for price in price_list: + bid_val = int(bid_dict.get(price, 0)) + ask_val = int(ask_dict.get(price, 0)) + + if bid_val: + bid_result[price] = bid_result.get(price, 0) + bid_val + ask_result.setdefault(price, 0) + if ask_val: + ask_result[price] = ask_result.get(price, 0) + ask_val + bid_result.setdefault(price, 0) + + self.data_store.quote[symbol] = {"bid_result": bid_result, "ask_result": ask_result} + return bid_result, ask_result + + +# ============ 回测主类 ============ + +class Backtester: + """回测主协调器""" + + def __init__(self, param_dict: dict): + self.param_dict = param_dict + self.data_store = BacktestDataStore() + self.equity_tracker = EquityTracker(SYSTEM_CONFIG["initial_equity"]) + self.trader = BacktestTrader(param_dict, self.equity_tracker) + self.results = {} + + def run(self): + """执行回测""" + mode = SYSTEM_CONFIG["backtest_mode"] + + for symbol in self.param_dict.keys(): + print(f"\n{'='*50}") + print(f"回测合约: {symbol},模式: {mode}") + print(f"{'='*50}") + + # 每次重新初始化 + self.data_store = BacktestDataStore() + self.equity_tracker = EquityTracker(SYSTEM_CONFIG["initial_equity"]) + self.trader = BacktestTrader(self.param_dict, self.equity_tracker) + + if mode == "ofdata": + replayer = OfdataReplayer(self, symbol) + else: + replayer = TickReplayer(self, symbol) + + replayer.replay() + + # 保存结果 + self.equity_tracker.save_results(symbol) + + # 打印指标 + metrics = self.equity_tracker.get_metrics() + print(f"\n回测结果:") + print(f" 总收益率: {metrics['total_return_pct']}%") + print(f" 最大回撤: {metrics['max_drawdown_pct']}%") + print(f" 胜率: {metrics['win_rate']}%") + print(f" 总交易次数: {metrics['total_trades']}") + print(f" 盈利交易: {metrics['winning_trades']}, 亏损交易: {metrics['losing_trades']}") + print(f" 最终权益: {metrics['final_equity']}") + + self.results[symbol] = metrics + + return self.results + + +if __name__ == "__main__": + # 测试回测模块 + from run import TradingParam + + param_dict = {} + for symbol, config in TRADING_PARAMS.items(): + p = TradingParam.from_config(symbol, config) + p.symbol = symbol + param_dict[symbol] = p + + backtester = Backtester(param_dict) + backtester.run() \ No newline at end of file diff --git a/1.交易策略/4.orderflow/backtest_results/IM2606_equity.csv b/1.交易策略/4.orderflow/backtest_results/IM2606_equity.csv new file mode 100644 index 0000000..c7045c6 --- /dev/null +++ b/1.交易策略/4.orderflow/backtest_results/IM2606_equity.csv @@ -0,0 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14:40:00,999984.8000000002,-60.39999999990687,-0.01 +2026-06-05 14:41:00,999984.8000000002,-60.39999999990687,-0.01 +2026-06-05 14:42:00,999984.8000000002,-60.39999999990687,-0.01 +2026-06-05 14:43:00,999984.8000000002,-60.39999999990687,-0.01 +2026-06-05 14:44:00,999984.8000000002,-60.39999999990687,-0.01 +2026-06-05 14:45:00,999984.8000000002,-60.39999999990687,-0.01 +2026-06-05 14:46:00,999984.8000000002,-60.39999999990687,-0.01 +2026-06-05 14:47:00,999984.8000000002,-60.39999999990687,-0.01 +2026-06-05 14:48:00,999984.8000000002,-60.39999999990687,-0.01 +2026-06-05 14:49:00,999984.8000000002,-60.39999999990687,-0.01 +2026-06-05 14:50:00,999984.8000000002,-60.39999999990687,-0.01 +2026-06-05 14:51:00,999984.8000000002,-60.39999999990687,-0.01 +2026-06-05 14:52:00,999984.8000000002,-60.39999999990687,-0.01 +2026-06-05 14:53:00,999984.8000000002,-60.39999999990687,-0.01 +2026-06-05 14:54:00,999984.8000000002,-60.39999999990687,-0.01 +2026-06-05 14:55:00,999984.8000000002,-60.39999999990687,-0.01 +2026-06-05 14:56:00,999984.8000000002,-60.39999999990687,-0.01 +2026-06-05 14:57:00,999984.8000000002,-60.39999999990687,-0.01 +2026-06-05 14:58:00,999984.8000000002,-60.39999999990687,-0.01 +2026-06-05 14:59:00,999984.8000000002,-60.39999999990687,-0.01 +2026-06-04 16:24:00,999970.8000000002,-74.39999999990687,-0.01 diff --git a/1.交易策略/4.orderflow/backtest_results/IM2606_metrics.json b/1.交易策略/4.orderflow/backtest_results/IM2606_metrics.json new file mode 100644 index 0000000..6eb9c0d --- /dev/null +++ b/1.交易策略/4.orderflow/backtest_results/IM2606_metrics.json @@ -0,0 +1,14 @@ +{ + "total_return": -29.2, + "total_return_pct": -0.0, + "max_drawdown": -110.8, + "max_drawdown_pct": -0.01, + "win_rate": 0.1765, + "total_trades": 17, + "winning_trades": 3, + "losing_trades": 14, + "avg_win": 45.67, + "avg_loss": -11.87, + "profit_factor": 0.82, + "final_equity": 999970.8 +} \ No newline at end of file diff --git a/1.交易策略/4.orderflow/backtest_results/IM2606_trades.csv b/1.交易策略/4.orderflow/backtest_results/IM2606_trades.csv new file mode 100644 index 0000000..8f72447 --- /dev/null +++ b/1.交易策略/4.orderflow/backtest_results/IM2606_trades.csv @@ -0,0 +1,18 @@ +trade_id,entry_datetime,entry_price,direction,exit_datetime,exit_price,lots,pnl,pnl_pct,status +1,2026-05-29 10:07:00,8418.8,short,2026-05-29 10:16:00,8393.0,1,25.8,0.0,closed +2,2026-05-29 10:17:00,8397.8,short,2026-05-29 10:22:00,8409.8,1,-12.0,-0.0,closed +3,2026-05-29 13:06:00,8374.4,short,2026-05-29 13:07:00,8383.4,1,-9.0,-0.0,closed +4,2026-05-29 14:25:00,8311.2,long,2026-06-01 09:39:00,8351.6,1,40.4,0.0,closed +5,2026-06-01 09:41:00,8356.6,long,2026-06-01 09:47:00,8346.0,1,-10.6,-0.0,closed +6,2026-06-01 09:49:00,8368.0,short,2026-06-01 09:50:00,8373.2,1,-5.2,-0.0,closed +7,2026-06-01 13:16:00,8415.4,long,2026-06-01 13:17:00,8406.0,1,-9.4,-0.0,closed +8,2026-06-02 09:41:00,8309.2,long,2026-06-02 09:45:00,8271.0,1,-38.2,-0.0,closed +9,2026-06-02 10:01:00,8227.4,short,2026-06-02 10:02:00,8239.0,1,-11.6,-0.0,closed +10,2026-06-02 14:11:00,8325.4,short,2026-06-02 14:19:00,8333.4,1,-8.0,-0.0,closed +11,2026-06-03 11:15:00,8468.2,long,2026-06-03 11:16:00,8456.2,1,-12.0,-0.0,closed +12,2026-06-03 13:36:00,8421.0,short,2026-06-03 13:37:00,8436.8,1,-15.8,-0.0,closed +13,2026-06-03 14:14:00,8395.8,short,2026-06-03 14:32:00,8325.0,1,70.8,0.01,closed +14,2026-06-03 14:43:00,8339.0,short,2026-06-03 14:48:00,8348.0,1,-9.0,-0.0,closed +15,2026-06-05 09:33:00,8267.2,short,2026-06-05 09:33:00,8272.2,1,-5.0,-0.0,closed +16,2026-06-05 09:38:00,8254.8,long,2026-06-05 09:39:00,8248.4,1,-6.4,-0.0,closed +17,2026-06-04 16:21:00,8378.0,short,2026-06-04 16:24:00,8392.0,1,-14.0,-0.0,closed diff --git a/1.交易策略/4.orderflow/config.py b/1.交易策略/4.orderflow/config.py index 69a9df2..4362b7a 100644 --- a/1.交易策略/4.orderflow/config.py +++ b/1.交易策略/4.orderflow/config.py @@ -39,32 +39,32 @@ TRADING_PARAMS = { "IM2606": { "lots": 1, "price_offset": 5, - "delta_threshold": 300, + "delta_threshold": 200, "imbalance_ratio": 3, "accumulation_threshold": 3, - "period": "3min", - "min_volume": 10, + "period": "1min", + "min_volume": 20, "merge_price": 5, "mini_price": 0.2, }, - "jm2609": { - "lots": 1, - "price_offset": 1, # 黄金波动较小，价格偏移也小 - "delta_threshold": 300, - "imbalance_ratio": 3, - "accumulation_threshold": 3, - "period": "3min", - "min_volume": 5, # 黄金成交量较大，可适当调高 - "merge_price": 2, - "mini_price": 0.5, # 黄金最小变动价位 - }, + # "jm2609": { + # "lots": 1, + # "price_offset": 1, # 黄金波动较小，价格偏移也小 + # "delta_threshold": 300, + # "imbalance_ratio": 3, + # "accumulation_threshold": 3, + # "period": "1min", + # "min_volume": 10, # 黄金成交量较大，可适当调高 + # "merge_price": 2, + # "mini_price": 0.5, # 黄金最小变动价位 + # }, } # ============ SimNow模拟账户配置 ============ SIMNOW_CONFIG = { "investor_id": "223828", "password": os.getenv("SIMNOW_PASSWORD", "Zj1234!@#%"), - "server_name": "电信1", # 交易服务器(电信1、电信2、移动、TEST、N视界、TEST环境) + "server_name": "TEST", # 交易服务器(电信1、电信2、移动、TEST、N视界、TEST环境) } # ============ 实盘账户配置（注释备用） ============ @@ -88,6 +88,18 @@ SYSTEM_CONFIG = { "json_records_limit": 20, "stops_load_interval": 60, "data_dir": "traderdata", + # === 回测/录制配置 === + "mode": "backtest", # "live" | "backtest" + "backtest_mode": "ofdata", # "ofdata" | "tick" + "backtest_results_dir": "backtest_results", + "initial_equity": 1000000.0, + "contract_multiplier": { + "im2606": 300, + "jm2609": 60, # 焦煤：吨/手 + "au2608": 1000, # 黄金：克/手 + }, + "record_tick": True, # 是否录制 tick 数据 + "tick_record_interval": 1, # 录制间隔（每N个tick录一个） } # ============ 夜盘收盘时间字典 ============ diff --git a/1.交易策略/4.orderflow/log/223828/md.con/DialogRsp.con b/1.交易策略/4.orderflow/log/223828/md.con/DialogRsp.con new file mode 100644 index 0000000000000000000000000000000000000000..ab2c6846789c5681cd5544fd3e407c6648761ab9 GIT binary patch literal 6 KcmZQz009611^@v7 literal 0 HcmV?d00001 diff --git a/1.交易策略/4.orderflow/log/223828/md.con/QueryRsp.con 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LcmZ>=V*mmG0>}V? literal 0 HcmV?d00001 diff --git a/1.交易策略/4.orderflow/readme.md b/1.交易策略/4.orderflow/readme.md new file mode 100644 index 0000000..dd42990 --- /dev/null +++ b/1.交易策略/4.orderflow/readme.md @@ -0,0 +1,161 @@ +# 订单流交易系统 + +## 概述 + +订单流交易策略系统，支持实盘交易和回测。 + +## 模式切换 + +通过 `config.py` 中的 `SYSTEM_CONFIG["mode"]` 切换： + +```python +SYSTEM_CONFIG = { + "mode": "live", # "live" | "backtest" +} +``` + +## 实盘/模拟模式 (mode="live") + +运行 SimNow 模拟交易或实盘交易： + +```bash +python run.py +``` + +### Tick 数据录制 + +实盘运行时可录制 tick 数据供回测使用： + +```python +SYSTEM_CONFIG = { + "record_tick": True, # 开启录制 + "tick_record_interval": 1, # 每N个tick录一个 +} +``` + +录制的数据保存在 `traderdata/{symbol}_tick.csv`。 + +## 回测模式 (mode="backtest") + +### 配置 + +```python +SYSTEM_CONFIG = { + "mode": "backtest", + "backtest_mode": "ofdata", # "ofdata" | "tick" + "backtest_results_dir": "backtest_results", + "initial_equity": 100000.0, + "contract_multiplier": { + "jm2609": 60, # 焦煤：吨/手 + "au2608": 1000, # 黄金：克/手 + } +} +``` + +### 回测模式 1: ofdata.json 回放 + +读取已有的 `ofdata.json` 历史订单流数据进行回测。 + +数据源：`traderdata/{symbol}_ofdata.json` + +```python +"backtest_mode": "ofdata" +``` + +### 回测模式 2: 原始 tick 回放 + +读取原始 tick CSV 文件，完整重放 tick → K线 → 订单流流程。 + +数据源：`traderdata/{symbol}_tick.csv` + +```python +"backtest_mode": "tick" +``` + +### 运行回测 + +```bash +python run.py +``` + +### 输出文件 + +回测结果保存在 `backtest_results/` 目录： + +| 文件 | 说明 | +|------|------| +| `{symbol}_equity.csv` | 权益曲线 | +| `{symbol}_trades.csv` | 交易记录 | +| `{symbol}_metrics.json` | 性能指标 | + +### 性能指标 + +```json +{ + "total_return": 12500.0, + "total_return_pct": 12.5, + "max_drawdown": -3200.0, + "max_drawdown_pct": -3.2, + "win_rate": 0.62, + "total_trades": 50, + "winning_trades": 31, + "losing_trades": 19, + "avg_win": 850.0, + "avg_loss": -420.0, + "profit_factor": 2.1, + "final_equity": 112500.0 +} +``` + +## 文件结构 + +``` +4.orderflow/ +├── run.py # 实盘/模拟交易主程序 +├── config.py # 配置文件 +├── backtest.py # 回测模块 +├── traderdata/ # 实盘数据 +│ ├── jm2609_ofdata.json +│ └── jm2609_tick.csv # 录制生成 +├── backtest_results/ # 回测输出 +│ ├── jm2609_equity.csv +│ ├── jm2609_trades.csv +│ └── jm2609_metrics.json +└── readme.md +``` + +## tick CSV 格式 (Mode 2 回测数据) + +|字段 | 类型 | 说明 | +|------|------|------| +| InstrumentID | string | 合约代码 | +| ActionDay | string | YYYYMMDD | +| UpdateTime | string | HH:MM:SS | +| UpdateMillisec | int | 毫秒 | +| LastPrice | float | 最新价 | +| Volume | int | 累计成交量 | +| BidPrice1 | float | 买一价 | +| BidVolume1 | int | 买一量 | +| AskPrice1 | float | 卖一价 | +| AskVolume1 | int | 卖一量 | +| UpperLimitPrice | float | 涨停价 | +| LowerLimitPrice | float | 跌停价 | +| TradingDay | string | YYYYMMDD | +| Turnover | float | 累计成交额 | +| OpenInterest | int | 持仓量 | + +## 历史修改记录 + +### 2026-06-05: ofdata.json 保存时机改善 + +**问题**：`ofdata.json` 中价格数据相对于实时 tick 有延迟 + +**修改**：在 `tickdata` 方法中，新 K 线开始时立即保存 `ofdata.json`，移除 `cal_sig` 中的重复保存 + +### 2026-06-05: 回测模块 + +**新增功能**： +- 支持 `mode` 切换实盘/回测 +- Mode 1: ofdata.json 回放 +- Mode 2: 原始 tick CSV 回放 +- Tick 数据录制功能 \ No newline at end of file diff --git a/1.交易策略/4.orderflow/run.py b/1.交易策略/4.orderflow/run.py index 845cd01..5a10848 100644 --- a/1.交易策略/4.orderflow/run.py +++ b/1.交易策略/4.orderflow/run.py @@ -7,6 +7,7 @@ import threading # 线程模块 import os # 操作系统模块 import json # JSON模块 import re # 正则表达式模块 +import csv # CSV模块 import time as time_module # 标准库时间模块 from datetime import datetime, time as datetime_time # datetime时间对象 from multiprocessing import Process, Queue # 多进程模块 @@ -167,12 +168,23 @@ class OrderFlowTrader(TraderApiBase): # 数据存储 self._json_save_counter = {} # JSON保存计数器 self.md_queue = md_queue # 行情队列 + self._tick_record_counter = {} # tick录制计数器 {symbol: count} # ============ 行情数据处理 ============ def tickcome(self, md_queue): """接收并处理Tick行情数据""" data = md_queue # 从队列获取行情数据 + + # === tick录制（实盘模式） === + if SYSTEM_CONFIG.get("record_tick", False): + instrument_id_raw = data["InstrumentID"] + symbol = instrument_id_raw.decode() if isinstance(instrument_id_raw, bytes) else instrument_id_raw + self._tick_record_counter[symbol] = self._tick_record_counter.get(symbol, 0) + 1 + interval = SYSTEM_CONFIG.get("tick_record_interval", 1) + if self._tick_record_counter[symbol] % interval == 0: + self._record_tick_to_csv(data, symbol) + instrument_id = data["InstrumentID"].decode() # 解码合约代码 action_day = data["ActionDay"].decode() # 解码交易日期 update_time = data["UpdateTime"].decode() # 解码更新时间 @@ -215,6 +227,36 @@ class OrderFlowTrader(TraderApiBase): } self.on_tick(tick) # 调用Tick处理回调 + def _record_tick_to_csv(self, data: dict, symbol: str): + """录制 tick 数据到 CSV""" + data_dir = SYSTEM_CONFIG["data_dir"] + os.makedirs(data_dir, exist_ok=True) + csv_path = f"{data_dir}/{symbol}_tick.csv" + + # CSV 字段 + fields = [ + "InstrumentID", "ActionDay", "UpdateTime", "UpdateMillisec", + "LastPrice", "Volume", "BidPrice1", "BidVolume1", + "AskPrice1", "AskVolume1", "UpperLimitPrice", "LowerLimitPrice", + "TradingDay", "Turnover", "OpenInterest" + ] + + # 写入字段（bytes 解码） + row = {} + for field in fields: + val = data.get(field) + if isinstance(val, bytes): + row[field] = val.decode() + else: + row[field] = val + + file_exists = os.path.exists(csv_path) + with open(csv_path, 'a', newline='', encoding='utf-8') as f: + writer = csv.DictWriter(f, fieldnames=fields) + if not file_exists: + writer.writeheader() + writer.writerow(row) + def on_tick(self, tick): """处理单个Tick数据""" if tick["last_volume"] == 0: # 无成交量则返回 @@ -330,6 +372,8 @@ class OrderFlowTrader(TraderApiBase): of = DataStore.ofdata.pop(symbol, None) if of is not None: self.data_of(symbol, of) # 写入交易DataFrame + # 保存 ofdata.json（改善时间戳对齐：旧K线完成时即保存） + self.save_ofdata_json(symbol) # 清空旧K线的报价数据 with self._quote_lock: @@ -1033,9 +1077,6 @@ class OrderFlowTrader(TraderApiBase): # 计算Delta累计（必须在保存之前） self.calculate_delta_cumulative(trade_df, param) - # 保存 ofdata.json（计算 delta累计 之后） - self.save_ofdata_json(instrument_id) - # 计算交易信号 bull_signal, bear_signal, dj_last, delta_last = self.calculate_signals(trade_df, param) @@ -1146,44 +1187,51 @@ if __name__ == "__main__": for symbol, config in TRADING_PARAMS.items(): param_dict[symbol] = TradingParam.from_config(symbol, config) - # 连接SimNow模拟交易 - future_account = get_simulate_account( - investor_id=SIMNOW_CONFIG["investor_id"], - password=SIMNOW_CONFIG["password"], - server_name=SIMNOW_CONFIG["server_name"], - subscribe_list=list(param_dict.keys()), - ) + # ===模式切换：回测模式 === + if SYSTEM_CONFIG.get("mode", "live") == "backtest": + from backtest import Backtester + backtester = Backtester(param_dict) + backtester.run() + else: + # === 实盘/模拟模式 === + # 连接SimNow模拟交易 + future_account = get_simulate_account( + investor_id=SIMNOW_CONFIG["investor_id"], + password=SIMNOW_CONFIG["password"], + server_name=SIMNOW_CONFIG["server_name"], + subscribe_list=list(param_dict.keys()), + ) - # 连接实盘（备用） - # from CtpPlus.CTP.FutureAccount import FutureAccount - # future_account = FutureAccount(...) + # 连接实盘（备用） + # from CtpPlus.CTP.FutureAccount import FutureAccount + # future_account = FutureAccount(...) - print("开始", len(future_account.subscribe_list)) + print("开始", len(future_account.subscribe_list)) - # 创建共享队列 - share_queue = Queue(maxsize=SYSTEM_CONFIG["queue_share_size"]) + # 创建共享队列 + share_queue = Queue(maxsize=SYSTEM_CONFIG["queue_share_size"]) - # 启动行情进程 - md_process = Process(target=run_tick_engine, args=(future_account, [share_queue])) + # 启动行情进程 + md_process = Process(target=run_tick_engine, args=(future_account, [share_queue])) - # 启动交易进程 - trader_process = Process( - target=run_trader, - args=( - param_dict, - future_account.broker_id, - future_account.server_dict["TDServer"], - future_account.investor_id, - future_account.password, - future_account.app_id, - future_account.auth_code, - share_queue, - future_account.td_flow_path, - ), - ) + # 启动交易进程 + trader_process = Process( + target=run_trader, + args=( + param_dict, + future_account.broker_id, + future_account.server_dict["TDServer"], + future_account.investor_id, + future_account.password, + future_account.app_id, + future_account.auth_code, + share_queue, + future_account.td_flow_path, + ), + ) - md_process.start() # 启动行情进程 - trader_process.start() # 启动交易进程 + md_process.start() # 启动行情进程 + trader_process.start() # 启动交易进程 - md_process.join() # 等待行情进程结束 - trader_process.join() # 等待交易进程结束 \ No newline at end of file + md_process.join() # 等待行情进程结束 + trader_process.join() # 等待交易进程结束 \ No newline at end of file diff --git a/1.交易策略/4.orderflow/traderdata/IM2606_ofdata.json b/1.交易策略/4.orderflow/traderdata/IM2606_ofdata.json new file mode 100644 index 0000000..77a08a9 --- /dev/null +++ b/1.交易策略/4.orderflow/traderdata/IM2606_ofdata.json @@ -0,0 +1,1442 @@ 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