lm_code/weex/长期持有信号/30分钟优化实体超过版本.py

"""
15分钟K线包住形态策略（优化版本）
- 第二根实体必须比第一根实体大 20% 以上
- 支持续持、反手、单根反色平仓
"""

import datetime
from dataclasses import dataclass
from typing import List, Dict, Optional
from loguru import logger
from models.weex import Weex30  # 你的数据库模型


# ========================= 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 calc_body(c):
    """计算实体大小"""
    return abs(float(c['close']) - float(c['open']))


# ========================= 包住信号（含20%增强） =========================

def check_signal(prev, curr):
    """
    包住信号：
    - 多头：前跌后涨包住
    - 空头：前涨后跌包住

    增强条件：
    - 第二根（curr）K线实体大小 >= 第一根(prev) × 1.2
    """

    p_open, p_close = float(prev['open']), float(prev['close'])
    c_open, c_close = float(curr['open']), float(curr['close'])

    prev_body = calc_body(prev)
    curr_body = calc_body(curr)

    # ====== 第二根实体必须 ≥ 第一根实体 × 1.2 ======
    if curr_body < prev_body + (curr_body * 0.4):
        return None, None

    # ----------- 多头包住信号（bear → bull）-----------
    if (is_bearish(prev) and is_bullish(curr)
            and c_open <= p_close
            and c_close >= p_open):
        return "long", "bear_bull_engulf"

    # ----------- 空头包住信号（bull → bear）-----------
    if (is_bullish(prev) and is_bearish(curr)
            and c_open >= p_close
            and c_close <= p_open):
        return "short", "bull_bear_engulf"

    return None, None


# ========================= 数据获取 =========================

def get_data_by_date(model, date_str: str):
    """按天获取 15 分钟数据"""
    try:
        target_date = datetime.datetime.strptime(date_str, '%Y-%m-%d')
    except ValueError:
        logger.error("日期格式不正确，需为 YYYY-MM-DD")
        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]


# ========================= 核心回测逻辑 =========================

def backtest_15m_trend_optimized(dates: List[str]):
    all_data = []
    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 = []
    current_position = None
    idx = 1

    while idx < len(all_data) - 1:
        prev = all_data[idx - 1]
        curr = all_data[idx]
        next_bar = all_data[idx + 1]

        direction, sig_key = check_signal(prev, curr)

        # ========== 空仓遇到信号 -> 开仓 ==========
        if current_position is None and direction:
            entry_price = float(next_bar['open'])
            current_position = {
                'direction': direction,
                'signal': stats[sig_key]['name'],
                'signal_key': sig_key,
                'entry_price': entry_price,
                'entry_time': next_bar['id']
            }
            stats[sig_key]['count'] += 1
            idx += 1
            continue

        # ========== 已持仓 ==========
        if current_position:
            pos_dir = current_position['direction']
            pos_sig_key = current_position['signal_key']

            # ======= 反向信号 -> 平仓 + 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

                # === 反手开新仓 ===
                current_position = {
                    'direction': direction,
                    'signal': stats[sig_key]['name'],
                    'signal_key': sig_key,
                    'entry_price': exit_price,
                    'entry_time': next_bar['id']
                }
                stats[sig_key]['count'] += 1

                idx += 1
                continue

            # ======= 同向信号 -> 继续持仓 =======
            if direction and direction == pos_dir:
                idx += 1
                continue

            # ======= 单根反色 =======
            curr_is_opposite = (pos_dir == 'long' and is_bearish(curr)) or \
                               (pos_dir == 'short' and is_bullish(curr))

            if curr_is_opposite:
                # 先判断下一根是不是会形成信号
                if idx + 1 < len(all_data):
                    look_dir, _ = check_signal(curr, all_data[idx + 1])
                    if look_dir:  # 后面还能形成信号 → 忍耐
                        idx += 1
                        continue

                # 否则按下一根收盘价平仓
                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(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 = None

        idx += 1

    # ========== 尾仓强制平仓 ==========
    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


# ================ 主程序（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 =====")

    contract_size = 10000
    open_fee_fixed = 5
    close_fee_rate = 0.0005

    total_points = 0
    total_raw_profit = 0
    total_fee = 0

    for t in trades:
        entry = t['entry']
        exit = t['exit']
        direction = t['direction']

        # 点差
        point_diff = exit - entry if direction == '做多' else entry - exit

        # 金额盈利
        money_profit = point_diff / entry * contract_size

        # 手续费
        fee = open_fee_fixed + (contract_size / entry * exit * close_fee_rate)

        net_profit = money_profit - fee

        t.update({
            'point_diff': point_diff,
            'raw_profit': money_profit,
            'fee': fee,
            'net_profit': net_profit
        })

        total_points += point_diff
        total_raw_profit += money_profit
        total_fee += fee

        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
    total_net = total_raw_profit - total_fee
    print(f"\n总交易数：{len(trades)}")
    print(f"总点差：{total_points:.2f}")
    print(f"总原始盈利：{total_raw_profit:.2f}")
    print(f"总手续费：{total_fee:.2f}")
    print(f"总净利润：{total_net:.2f}\n")

    print(total_raw_profit - total_fee * 0.1)

    print("===== 信号统计 =====")
    for k, v in stats.items():
        name = v['name']
        count = v['count']
        wins = v['wins']
        total_p = v['total_profit']
        win_rate = wins / count * 100 if count > 0 else 0
        avg_p = total_p / count if count > 0 else 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}")