""" 量化交易回测系统 - 仅15分钟K线 & 信号续持/反手/单根反色平仓逻辑（完整版） """ import datetime from dataclasses import dataclass from typing import List, Dict, Optional from loguru import logger from models.weex import Weex30 # 替换为你的15分钟K线模型 # ========================= 工具函数 ========================= def is_bullish(c): # 阳线 return float(c['close']) > float(c['open']) def is_bearish(c): # 阴线 return float(c['close']) < float(c['open']) def check_signal(prev, curr): """ 包住形态信号判定（仅15分钟K线）： - 前跌后涨包住 -> 做多 - 前涨后跌包住 -> 做空 """ p_open, p_close = float(prev['open']), float(prev['close']) c_open, c_close = float(curr['open']), float(curr['close']) # 前跌后涨包住 -> 做多 if is_bullish(curr) and is_bearish(prev) and c_open <= p_close and c_close >= p_open: return "long", "bear_bull_engulf" # 前涨后跌包住 -> 做空 if is_bearish(curr) and is_bullish(prev) and c_open >= p_close and c_close <= p_open: return "short", "bull_bear_engulf" return None, None def get_data_by_date(model, date_str: str): """按天获取指定表的数据（15分钟）""" try: target_date = datetime.datetime.strptime(date_str, '%Y-%m-%d') except ValueError: logger.error("日期格式不正确，请使用 YYYY-MM-DD 格式。") return [] start_ts = int(target_date.timestamp() * 1000) end_ts = int((target_date + datetime.timedelta(days=1)).timestamp() * 1000) - 1 query = model.select().where(model.id.between(start_ts, end_ts)).order_by(model.id.asc()) return [{'id': i.id, 'open': i.open, 'high': i.high, 'low': i.low, 'close': i.close} for i in query] # ========================= 回测逻辑 ========================= def backtest_15m_trend_optimized(dates: List[str]): all_data: List[Dict] = [] for d in dates: all_data.extend(get_data_by_date(Weex30, d)) if not all_data: return [], { 'bear_bull_engulf': {'count': 0, 'wins': 0, 'total_profit': 0.0, 'name': '涨包跌'}, 'bull_bear_engulf': {'count': 0, 'wins': 0, 'total_profit': 0.0, 'name': '跌包涨'}, } all_data.sort(key=lambda x: x['id']) stats = { 'bear_bull_engulf': {'count': 0, 'wins': 0, 'total_profit': 0.0, 'name': '涨包跌'}, 'bull_bear_engulf': {'count': 0, 'wins': 0, 'total_profit': 0.0, 'name': '跌包涨'}, } trades: List[Dict] = [] current_position: Optional[Dict] = None # 开仓信息 idx = 1 while idx < len(all_data) - 1: prev, curr, next_bar = all_data[idx - 1], all_data[idx], all_data[idx + 1] direction, signal_key = check_signal(prev, curr) # 空仓 -> 碰到信号则开仓 if current_position is None and direction: entry_price = float(next_bar['open']) current_position = { 'direction': direction, 'signal': stats[signal_key]['name'], 'signal_key': signal_key, 'entry_price': entry_price, 'entry_time': next_bar['id'] } stats[signal_key]['count'] += 1 idx += 1 continue if current_position: pos_dir = current_position['direction'] pos_sig_key = current_position['signal_key'] # 反向信号 -> 下一根开盘平仓 + 同价反手 if direction and direction != pos_dir: exit_price = float(next_bar['open']) diff = (exit_price - current_position['entry_price']) if pos_dir == 'long' else ( current_position['entry_price'] - exit_price) trades.append({ 'entry_time': datetime.datetime.fromtimestamp(current_position['entry_time'] / 1000), 'exit_time': datetime.datetime.fromtimestamp(next_bar['id'] / 1000), 'signal': current_position['signal'], 'direction': '做多' if pos_dir == 'long' else '做空', 'entry': current_position['entry_price'], 'exit': exit_price, 'diff': diff }) stats[pos_sig_key]['total_profit'] += diff if diff > 0: stats[pos_sig_key]['wins'] += 1 current_position = { 'direction': direction, 'signal': stats[signal_key]['name'], 'signal_key': signal_key, 'entry_price': exit_price, 'entry_time': next_bar['id'] } stats[signal_key]['count'] += 1 idx += 1 continue # 同向信号 -> 续持 if direction and direction == pos_dir: idx += 1 continue # 单根反色K线 -> 判断后续是否能组成信号 curr_is_opposite = (pos_dir == 'long' and is_bearish(curr)) or (pos_dir == 'short' and is_bullish(curr)) if curr_is_opposite: can_peek = idx + 1 < len(all_data) if can_peek: lookahead_dir, _ = check_signal(curr, all_data[idx + 1]) if lookahead_dir is not None: idx += 1 continue # 后续可组成信号，等待信号处理 # 否则按收盘价平仓 exit_price = float(next_bar['close']) diff = (exit_price - current_position['entry_price']) if pos_dir == 'long' else ( current_position['entry_price'] - exit_price) trades.append({ 'entry_time': datetime.datetime.fromtimestamp(current_position['entry_time'] / 1000), 'exit_time': datetime.datetime.fromtimestamp(all_data[idx + 1]['id'] / 1000), 'signal': current_position['signal'], 'direction': '做多' if pos_dir == 'long' else '做空', 'entry': current_position['entry_price'], 'exit': exit_price, 'diff': diff }) stats[pos_sig_key]['total_profit'] += diff if diff > 0: stats[pos_sig_key]['wins'] += 1 current_position = None idx += 1 # 尾仓：最后一根收盘价平仓 if current_position: last = all_data[-1] exit_price = float(last['close']) pos_dir = current_position['direction'] diff = (exit_price - current_position['entry_price']) if pos_dir == 'long' else ( current_position['entry_price'] - exit_price) trades.append({ 'entry_time': datetime.datetime.fromtimestamp(current_position['entry_time'] / 1000), 'exit_time': datetime.datetime.fromtimestamp(last['id'] / 1000), 'signal': current_position['signal'], 'direction': '做多' if pos_dir == 'long' else '做空', 'entry': current_position['entry_price'], 'exit': exit_price, 'diff': diff }) stats[current_position['signal_key']]['total_profit'] += diff if diff > 0: stats[current_position['signal_key']]['wins'] += 1 return trades, stats # ========================= 运行示例（优化版盈利计算） ========================= if __name__ == '__main__': dates = [] for i in range(1, 11): for i1 in range(1, 31): dates.append(f"2025-{f'0{i}' if len(str(i)) < 2 else i}-{i1}") print(dates) # dates = [f"2025-09-{i}" for i in range(1, 32)] trades, stats = backtest_15m_trend_optimized(dates) logger.info("===== 每笔交易详情 =====") # === 参数设定 === contract_size = 10000 # 合约规模（1手对应多少基础货币） open_fee_fixed = 5 # 固定开仓手续费 close_fee_rate = 0.0005 # 按成交额比例的平仓手续费率 total_points_profit = 0 # 累计点差 total_money_profit = 0 # 累计金额盈利 total_fee = 0 # 累计手续费 for t in trades: entry = t['entry'] exit = t['exit'] direction = t['direction'] # === 1️⃣ 原始价差（点差） === point_diff = (exit - entry) if direction == '做多' else (entry - exit) # === 2️⃣ 金额盈利（考虑合约规模） === money_profit = point_diff / entry * contract_size # 利润以基础货币计（例如USD） # === 3️⃣ 手续费计算 === # 开仓 + 平仓手续费（按比例计算 + 固定） fee = open_fee_fixed + (contract_size / entry * exit * close_fee_rate) # === 4️⃣ 净利润 === net_profit = money_profit - fee # 保存计算结果 t.update({ 'point_diff': point_diff, 'raw_profit': money_profit, 'fee': fee, 'net_profit': net_profit }) total_points_profit += point_diff total_money_profit += money_profit total_fee += fee # if net_profit < -400: logger.info( f"{t['entry_time']} {direction}({t['signal']}) " f"入={entry:.2f} 出={exit:.2f} 差价={point_diff:.2f} " f"原始盈利={money_profit:.2f} 手续费={fee:.2f} 净利润={net_profit:.2f} {t['exit_time']}" ) # === 汇总统计 === total_net_profit = total_money_profit - total_fee print(f"\n一共交易笔数：{len(trades)}") print(f"总点差：{total_points_profit:.2f}") print(f"总原始盈利（未扣费）：{total_money_profit:.2f}") print(f"总手续费：{total_fee:.2f}") print(f"总净利润：{total_net_profit:.2f}\n") print(total_money_profit - total_fee * 0.1 ) print("===== 信号统计 =====") for k, v in stats.items(): name, count, wins, total_p = v['name'], v['count'], v['wins'], v['total_profit'] win_rate = (wins / count * 100) if count > 0 else 0.0 avg_p = (total_p / count) if count > 0 else 0.0 print(f"{name}: 次数={count} 胜率={win_rate:.2f}% 总价差={total_p:.2f} 平均价差={avg_p:.2f}")