300 lines
10 KiB
Python
300 lines
10 KiB
Python
"""
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15分钟K线包住形态策略（优化版本）
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- 第二根实体必须比第一根实体大 20% 以上
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- 支持续持、反手、单根反色平仓
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"""
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import datetime
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from dataclasses import dataclass
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from typing import List, Dict, Optional
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from loguru import logger
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from models.weex import Weex30 # 你的数据库模型
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# ========================= 工具函数 =========================
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def is_bullish(c):
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"""阳线"""
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return float(c['close']) > float(c['open'])
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def is_bearish(c):
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"""阴线"""
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return float(c['close']) < float(c['open'])
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def calc_body(c):
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"""计算实体大小"""
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return abs(float(c['close']) - float(c['open']))
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# ========================= 包住信号（含20%增强） =========================
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def check_signal(prev, curr):
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"""
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包住信号：
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- 多头：前跌后涨包住
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- 空头：前涨后跌包住
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增强条件：
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- 第二根（curr）K线实体大小 >= 第一根(prev) × 1.2
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"""
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p_open, p_close = float(prev['open']), float(prev['close'])
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c_open, c_close = float(curr['open']), float(curr['close'])
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prev_body = calc_body(prev)
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curr_body = calc_body(curr)
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# ====== 第二根实体必须 ≥ 第一根实体 × 1.2 ======
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if curr_body < prev_body * 1.2:
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return None, None
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# ----------- 多头包住信号（bear → bull）-----------
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if (is_bearish(prev) and is_bullish(curr)
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and c_open <= p_close
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and c_close >= p_open):
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return "long", "bear_bull_engulf"
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# ----------- 空头包住信号（bull → bear）-----------
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if (is_bullish(prev) and is_bearish(curr)
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and c_open >= p_close
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and c_close <= p_open):
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return "short", "bull_bear_engulf"
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return None, None
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# ========================= 数据获取 =========================
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def get_data_by_date(model, date_str: str):
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"""按天获取 15 分钟数据"""
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try:
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target_date = datetime.datetime.strptime(date_str, '%Y-%m-%d')
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except ValueError:
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logger.error("日期格式不正确，需为 YYYY-MM-DD")
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return []
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start_ts = int(target_date.timestamp() * 1000)
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end_ts = int((target_date + datetime.timedelta(days=1)).timestamp() * 1000) - 1
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query = model.select().where(model.id.between(start_ts, end_ts)).order_by(model.id.asc())
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return [{'id': i.id, 'open': i.open, 'high': i.high, 'low': i.low, 'close': i.close} for i in query]
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# ========================= 核心回测逻辑 =========================
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def backtest_15m_trend_optimized(dates: List[str]):
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all_data = []
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for d in dates:
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all_data.extend(get_data_by_date(Weex30, d))
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if not all_data:
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return [], {
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'bear_bull_engulf': {'count': 0, 'wins': 0, 'total_profit': 0.0, 'name': '涨包跌'},
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'bull_bear_engulf': {'count': 0, 'wins': 0, 'total_profit': 0.0, 'name': '跌包涨'},
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}
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all_data.sort(key=lambda x: x['id'])
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stats = {
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'bear_bull_engulf': {'count': 0, 'wins': 0, 'total_profit': 0.0, 'name': '涨包跌'},
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'bull_bear_engulf': {'count': 0, 'wins': 0, 'total_profit': 0.0, 'name': '跌包涨'},
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}
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trades = []
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current_position = None
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idx = 1
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while idx < len(all_data) - 1:
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prev = all_data[idx - 1]
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curr = all_data[idx]
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next_bar = all_data[idx + 1]
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direction, sig_key = check_signal(prev, curr)
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# ========== 空仓遇到信号 -> 开仓 ==========
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if current_position is None and direction:
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entry_price = float(next_bar['open'])
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current_position = {
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'direction': direction,
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'signal': stats[sig_key]['name'],
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'signal_key': sig_key,
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'entry_price': entry_price,
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'entry_time': next_bar['id']
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}
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stats[sig_key]['count'] += 1
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idx += 1
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continue
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# ========== 已持仓 ==========
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if current_position:
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pos_dir = current_position['direction']
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pos_sig_key = current_position['signal_key']
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# ======= 反向信号 -> 平仓 + 反手 =======
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if direction and direction != pos_dir:
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exit_price = float(next_bar['open'])
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diff = (exit_price - current_position['entry_price']) if pos_dir == 'long' else \
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(current_position['entry_price'] - exit_price)
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trades.append({
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'entry_time': datetime.datetime.fromtimestamp(current_position['entry_time'] / 1000),
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'exit_time': datetime.datetime.fromtimestamp(next_bar['id'] / 1000),
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'signal': current_position['signal'],
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'direction': '做多' if pos_dir == 'long' else '做空',
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'entry': current_position['entry_price'],
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'exit': exit_price,
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'diff': diff
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})
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stats[pos_sig_key]['total_profit'] += diff
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if diff > 0:
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stats[pos_sig_key]['wins'] += 1
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# === 反手开新仓 ===
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current_position = {
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'direction': direction,
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'signal': stats[sig_key]['name'],
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'signal_key': sig_key,
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'entry_price': exit_price,
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'entry_time': next_bar['id']
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}
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stats[sig_key]['count'] += 1
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idx += 1
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continue
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# ======= 同向信号 -> 继续持仓 =======
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if direction and direction == pos_dir:
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idx += 1
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continue
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# ======= 单根反色 =======
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curr_is_opposite = (pos_dir == 'long' and is_bearish(curr)) or \
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(pos_dir == 'short' and is_bullish(curr))
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if curr_is_opposite:
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# 先判断下一根是不是会形成信号
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if idx + 1 < len(all_data):
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look_dir, _ = check_signal(curr, all_data[idx + 1])
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if look_dir: # 后面还能形成信号 → 忍耐
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idx += 1
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continue
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# 否则按下一根收盘价平仓
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exit_price = float(next_bar['close'])
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diff = (exit_price - current_position['entry_price']) if pos_dir == 'long' else \
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(current_position['entry_price'] - exit_price)
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trades.append({
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'entry_time': datetime.datetime.fromtimestamp(current_position['entry_time'] / 1000),
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'exit_time': datetime.datetime.fromtimestamp(next_bar['id'] / 1000),
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'signal': current_position['signal'],
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'direction': '做多' if pos_dir == 'long' else '做空',
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'entry': current_position['entry_price'],
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'exit': exit_price,
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'diff': diff
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})
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stats[pos_sig_key]['total_profit'] += diff
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if diff > 0:
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stats[pos_sig_key]['wins'] += 1
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current_position = None
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idx += 1
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# ========== 尾仓强制平仓 ==========
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if current_position:
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last = all_data[-1]
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exit_price = float(last['close'])
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pos_dir = current_position['direction']
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diff = (exit_price - current_position['entry_price']) if pos_dir == 'long' else \
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(current_position['entry_price'] - exit_price)
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trades.append({
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'entry_time': datetime.datetime.fromtimestamp(current_position['entry_time'] / 1000),
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'exit_time': datetime.datetime.fromtimestamp(last['id'] / 1000),
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'signal': current_position['signal'],
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'direction': '做多' if pos_dir == 'long' else '做空',
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'entry': current_position['entry_price'],
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'exit': exit_price,
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'diff': diff
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})
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stats[current_position['signal_key']]['total_profit'] += diff
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if diff > 0:
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stats[current_position['signal_key']]['wins'] += 1
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return trades, stats
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# ================ 主程序（盈利计算） ================
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if __name__ == '__main__':
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dates = [f"2025-11-{i}" for i in range(1, 32)]
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trades, stats = backtest_15m_trend_optimized(dates)
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logger.info("===== 每笔交易详情 =====")
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contract_size = 10000
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open_fee_fixed = 5
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close_fee_rate = 0.0005
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total_points = 0
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total_raw_profit = 0
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total_fee = 0
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for t in trades:
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entry = t['entry']
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exit = t['exit']
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direction = t['direction']
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# 点差
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point_diff = exit - entry if direction == '做多' else entry - exit
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# 金额盈利
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money_profit = point_diff / entry * contract_size
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# 手续费
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fee = open_fee_fixed + (contract_size / entry * exit * close_fee_rate)
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net_profit = money_profit - fee
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t.update({
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'point_diff': point_diff,
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'raw_profit': money_profit,
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'fee': fee,
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'net_profit': net_profit
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})
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total_points += point_diff
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total_raw_profit += money_profit
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total_fee += fee
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logger.info(
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f"{t['entry_time']} {direction}({t['signal']}) "
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f"入={entry:.2f} 出={exit:.2f} 差价={point_diff:.2f} "
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f"原始盈利={money_profit:.2f} 手续费={fee:.2f} 净利润={net_profit:.2f} {t['exit_time']}"
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)
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# 汇总
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total_net = total_raw_profit - total_fee
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print(f"\n总交易数：{len(trades)}")
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print(f"总点差：{total_points:.2f}")
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print(f"总原始盈利：{total_raw_profit:.2f}")
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print(f"总手续费：{total_fee:.2f}")
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print(f"总净利润：{total_net:.2f}\n")
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print("===== 信号统计 =====")
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for k, v in stats.items():
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name = v['name']
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count = v['count']
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wins = v['wins']
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total_p = v['total_profit']
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win_rate = wins / count * 100 if count > 0 else 0
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avg_p = total_p / count if count > 0 else 0
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print(f"{name}: 次数={count} 胜率={win_rate:.2f}% 总价差={total_p:.2f} 平均价差={avg_p:.2f}")
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