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diff --git a/weex/长期持有信号/30分钟优化实体超过版本.py b/weex/长期持有信号/30分钟优化实体超过版本.py
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+++ b/weex/长期持有信号/30分钟优化实体超过版本.py
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+"""
+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 * 1.2:
+        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 = [f"2025-11-{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("===== 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}")