优化交易代码

1111

@@ -21,9 +21,27 @@ db2e87093c120766bca60d2282y72760688
 yx20250715@gmail.com
 Abc12345678
 
-yx20250715@gmail.com
+
+248.23
+2611
+
+
+
+基于前一根有效 K 线（实体 ≥ 0.1）：
+做多触发价 = 当前 k 线开盘价 + 实体 / 5（收盘价向上 1/5 实体）
+做空触发价 = 当前 k 线开盘价 - 实体 / 5（收盘价向下 1/5 实体）
+
+若已有持仓，在 3 分钟 K 线的第一分钟可单独检测反手：
+持空反手做多：价格涨到 开仓价 + 前一根实体 / 5
+持多反手做空：价格跌到 开仓价 - 前一根实体 / 5
+
+
+
+
+
+
+
+
 
 
 
-555.73
-2278

bitmart/回测-三分之一策略-精准版.py

@@ -215,15 +215,128 @@ def determine_trigger_order_by_1m(
     return None
 
 
+def check_reverse_signal_in_first_minute(
+    bars_1m: List[Dict],
+    long_trigger: float,
+    short_trigger: float,
+    current_direction: str
+) -> bool:
+    """
+    检查反手信号是否在第一分钟触发
+    
+    :param bars_1m: 3根1分钟K线数据
+    :param long_trigger: 做多触发价格
+    :param short_trigger: 做空触发价格
+    :param current_direction: 当前持仓方向 ('long' 或 'short')
+    :return: True 表示反手信号在第一分钟触发，False 表示不是
+    """
+    if not bars_1m:
+        return False
+    
+    # 只检查第一分钟K线
+    first_bar = bars_1m[0]
+    high = float(first_bar['high'])
+    low = float(first_bar['low'])
+    
+    # 如果当前是多仓，检查空信号是否在第一分钟触发
+    if current_direction == 'long':
+        return low <= short_trigger
+    
+    # 如果当前是空仓，检查多信号是否在第一分钟触发
+    if current_direction == 'short':
+        return high >= long_trigger
+    
+    return False
+
+
+def get_body_percent(candle) -> float:
+    """
+    计算K线实体占价格的百分比
+    :param candle: K线数据
+    :return: 实体百分比（如0.1表示0.1%）
+    """
+    body = abs(float(candle['open']) - float(candle['close']))
+    price = (float(candle['open']) + float(candle['close'])) / 2
+    if price == 0:
+        return 0
+    return (body / price) * 100
+
+
+def check_breakout_reverse_signal(
+    all_data_3m: List[Dict],
+    current_idx: int,
+    current_position_direction: str,
+    min_body_percent: float = 0.1
+) -> tuple:
+    """
+    检查"突破上一根K线高低点"的反手信号
+    
+    规则：
+    - 持多单时：当前K线跌破上一根K线最低点 → 反手开空
+      条件：上一根K线是阴线且实体>0.1%波动
+    - 持空单时：当前K线涨破上一根K线最高点 → 反手开多
+      条件：上一根K线是阳线且实体>0.1%波动
+    
+    :param all_data_3m: 3分钟K线数据
+    :param current_idx: 当前K线索引
+    :param current_position_direction: 当前持仓方向 ('long' 或 'short')
+    :param min_body_percent: 最小实体百分比（默认0.1%）
+    :return: (方向, 触发价格, 信号类型) 或 (None, None, None)
+    """
+    if current_idx <= 0 or current_position_direction is None:
+        return None, None, None
+    
+    curr = all_data_3m[current_idx]
+    prev = all_data_3m[current_idx - 1]
+    
+    c_high = float(curr['high'])
+    c_low = float(curr['low'])
+    prev_high = float(prev['high'])
+    prev_low = float(prev['low'])
+    
+    # 计算上一根K线的实体百分比
+    body_percent = get_body_percent(prev)
+    
+    # 持多单时：检查是否跌破上一根K线最低点
+    if current_position_direction == 'long':
+        # 条件：上一根K线是阴线且实体>min_body_percent%
+        if is_bearish(prev) and body_percent >= min_body_percent:
+            if c_low < prev_low:
+                # 触发反手开空信号
+                logger.debug(f"突破反手信号：持多单，当前K线低点{c_low:.2f}跌破上一根阴线低点{prev_low:.2f}，实体{body_percent:.3f}%")
+                return 'short', prev_low, 'breakout'
+    
+    # 持空单时：检查是否涨破上一根K线最高点
+    elif current_position_direction == 'short':
+        # 条件：上一根K线是阳线且实体>min_body_percent%
+        if is_bullish(prev) and body_percent >= min_body_percent:
+            if c_high > prev_high:
+                # 触发反手开多信号
+                logger.debug(f"突破反手信号：持空单，当前K线高点{c_high:.2f}涨破上一根阳线高点{prev_high:.2f}，实体{body_percent:.3f}%")
+                return 'long', prev_high, 'breakout'
+    
+    return None, None, None
+
+
 def check_trigger_with_1m(
     all_data_3m: List[Dict], 
     current_idx: int, 
-    min_body_size: float = 0.1
+    min_body_size: float = 0.1,
+    current_position_direction: str = None,
+    first_minute_only: bool = True
 ) -> tuple:
     """
     检查当前3分钟K线是否触发了交易信号
     如果同时触发两个方向，使用1分钟K线精确判断顺序
     
+    新增逻辑：如果有持仓且 first_minute_only=True，反手信号必须在第一分钟触发才有效
+    
+    :param all_data_3m: 3分钟K线数据
+    :param current_idx: 当前K线索引
+    :param min_body_size: 最小实体大小
+    :param current_position_direction: 当前持仓方向 ('long', 'short', 或 None)
+    :param first_minute_only: 是否只在第一分钟触发反手信号才有效
+    
     返回：(方向, 触发价格, 有效前一根K线索引, 1分钟数据是否使用)
     """
     if current_idx <= 0:
@@ -257,6 +370,15 @@ def check_trigger_with_1m(
             direction = determine_trigger_order_by_1m(bars_1m, long_trigger, short_trigger)
             if direction:
                 trigger_price = long_trigger if direction == 'long' else short_trigger
+                
+                # 检查反手信号是否需要在第一分钟触发
+                if first_minute_only and current_position_direction and direction != current_position_direction:
+                    # 这是一个反手信号，检查是否在第一分钟触发
+                    if not check_reverse_signal_in_first_minute(bars_1m, long_trigger, short_trigger, current_position_direction):
+                        # 反手信号不是在第一分钟触发，忽略
+                        logger.debug(f"反手信号 {direction} 不在第一分钟触发，忽略")
+                        return None, None, None, False
+                
                 return direction, trigger_price, valid_prev_idx, True
         
         # 如果没有1分钟数据，使用开盘价距离判断
@@ -269,9 +391,21 @@ def check_trigger_with_1m(
             return 'long', long_trigger, valid_prev_idx, False
 
     if short_triggered:
+        # 检查是否是反手信号且需要第一分钟触发
+        if first_minute_only and current_position_direction == 'long':
+            bars_1m = get_1m_data_for_3m_bar(curr)
+            if bars_1m and not check_reverse_signal_in_first_minute(bars_1m, long_trigger, short_trigger, 'long'):
+                logger.debug(f"空信号不在第一分钟触发，忽略（当前持多仓）")
+                return None, None, None, False
         return 'short', short_trigger, valid_prev_idx, False
 
     if long_triggered:
+        # 检查是否是反手信号且需要第一分钟触发
+        if first_minute_only and current_position_direction == 'short':
+            bars_1m = get_1m_data_for_3m_bar(curr)
+            if bars_1m and not check_reverse_signal_in_first_minute(bars_1m, long_trigger, short_trigger, 'short'):
+                logger.debug(f"多信号不在第一分钟触发，忽略（当前持空仓）")
+                return None, None, None, False
         return 'long', long_trigger, valid_prev_idx, False
 
     return None, None, None, False
@@ -279,12 +413,21 @@ def check_trigger_with_1m(
 
 # ========================= 回测逻辑 =========================
 
-def backtest_one_third_strategy(dates: List[str], min_body_size: float = 0.1):
+def backtest_one_third_strategy(
+    dates: List[str], 
+    min_body_size: float = 0.1, 
+    first_minute_only: bool = True,
+    enable_breakout_reverse: bool = True,
+    breakout_min_body_percent: float = 0.1
+):
     """
     三分之一策略回测（精准版）
     
     :param dates: 日期列表
-    :param min_body_size: 最小实体大小
+    :param min_body_size: 最小实体大小（绝对值）
+    :param first_minute_only: 是否只在第一分钟触发反手信号才有效（默认True）
+    :param enable_breakout_reverse: 是否启用"突破上一根K线高低点"反手信号（默认True）
+    :param breakout_min_body_percent: 突破反手信号的最小实体百分比（默认0.1%）
     :return: (trades, stats)
     """
     # 获取所有3分钟K线数据
@@ -297,6 +440,8 @@ def backtest_one_third_strategy(dates: List[str], min_body_size: float = 0.1):
             total_queried += len(day_data)
     
     logger.info(f"总共查询了 {len(dates)} 天，获取到 {total_queried} 条3分钟K线数据")
+    logger.info(f"反手信号仅第一分钟有效: {first_minute_only}")
+    logger.info(f"突破反手信号启用: {enable_breakout_reverse}，最小实体百分比: {breakout_min_body_percent}%")
     
     if not all_data:
         logger.warning("未获取到任何数据，请检查数据库")
@@ -325,24 +470,47 @@ def backtest_one_third_strategy(dates: List[str], min_body_size: float = 0.1):
     # 统计使用1分钟数据精准判断的次数
     precise_count = 0
     fallback_count = 0
+    # 统计突破反手信号触发次数
+    breakout_reverse_count = 0
+    # 记录每根K线是否已经执行过突破反手（当前K线只执行一次）
+    last_breakout_bar_id = None
     
     idx = 1
     while idx < len(all_data):
         curr = all_data[idx]
+        curr_bar_id = curr['id']
         
-        # 检测信号（使用1分钟K线精准判断）
+        # 获取当前持仓方向（用于判断反手信号是否在第一分钟触发）
+        current_pos_dir = current_position['direction'] if current_position else None
+        
+        # 检测信号（使用1分钟K线精准判断，并考虑反手信号第一分钟限制）
         direction, trigger_price, valid_prev_idx, used_1m = check_trigger_with_1m(
-            all_data, idx, min_body_size
+            all_data, idx, min_body_size,
+            current_position_direction=current_pos_dir,
+            first_minute_only=first_minute_only
         )
         
+        # 如果没有五分之一信号，且有持仓，检查突破反手信号
+        signal_type = 'one_fifth'  # 信号类型：one_fifth（五分之一）或 breakout（突破）
+        if direction is None and current_position is not None and enable_breakout_reverse:
+            # 检查当前K线是否已经执行过突破反手
+            if last_breakout_bar_id != curr_bar_id:
+                breakout_dir, breakout_price, breakout_type = check_breakout_reverse_signal(
+                    all_data, idx, current_pos_dir, breakout_min_body_percent
+                )
+                if breakout_dir:
+                    direction = breakout_dir
+                    trigger_price = breakout_price
+                    signal_type = 'breakout'
+        
         if used_1m:
             precise_count += 1
-        elif direction:
+        elif direction and signal_type == 'one_fifth':
             fallback_count += 1
         
-        # 无持仓 -> 开仓
+        # 无持仓 -> 开仓（只用五分之一信号开仓，突破信号不用于开仓）
         if current_position is None:
-            if direction:
+            if direction and signal_type == 'one_fifth':
                 current_position = {
                     'direction': direction,
                     'entry_price': trigger_price,
@@ -369,19 +537,28 @@ def backtest_one_third_strategy(dates: List[str], min_body_size: float = 0.1):
             else:
                 diff = current_position['entry_price'] - exit_price
             
+            # 记录信号类型
+            signal_type_str = '突破' if signal_type == 'breakout' else '五分之一'
+            
             trades.append({
                 'entry_time': datetime.datetime.fromtimestamp(current_position['entry_time'] / 1000),
                 'exit_time': datetime.datetime.fromtimestamp(curr['id'] / 1000),
                 'direction': '做多' if pos_dir == 'long' else '做空',
                 'entry': current_position['entry_price'],
                 'exit': exit_price,
-                'diff': diff
+                'diff': diff,
+                'signal_type': signal_type_str
             })
             
             stats[pos_dir]['total_profit'] += diff
             if diff > 0:
                 stats[pos_dir]['wins'] += 1
             
+            # 如果是突破反手信号，记录当前K线ID，防止重复执行
+            if signal_type == 'breakout':
+                last_breakout_bar_id = curr_bar_id
+                breakout_reverse_count += 1
+            
             # 反手开仓
             current_position = {
                 'direction': direction,
@@ -392,7 +569,7 @@ def backtest_one_third_strategy(dates: List[str], min_body_size: float = 0.1):
             stats[direction]['count'] += 1
             
             time_str = datetime.datetime.fromtimestamp(curr['id'] / 1000).strftime('%Y-%m-%d %H:%M')
-            logger.debug(f"[{time_str}] 平{pos_dir}反手{direction} @ {trigger_price:.2f} 盈亏={diff:.2f}")
+            logger.debug(f"[{time_str}] 平{pos_dir}反手{direction}({signal_type_str}) @ {trigger_price:.2f} 盈亏={diff:.2f}")
         
         idx += 1
     
@@ -420,7 +597,7 @@ def backtest_one_third_strategy(dates: List[str], min_body_size: float = 0.1):
         if diff > 0:
             stats[pos_dir]['wins'] += 1
     
-    logger.info(f"回测完成：使用1分钟精准判断 {precise_count} 次，使用开盘价距离判断 {fallback_count} 次")
+    logger.info(f"回测完成：使用1分钟精准判断 {precise_count} 次，使用开盘价距离判断 {fallback_count} 次，突破反手信号 {breakout_reverse_count} 次")
     
     return trades, stats
 
@@ -431,7 +608,12 @@ if __name__ == '__main__':
     # ==================== 配置参数 ====================
     START_DATE = "2025-01-01"
     END_DATE = "2025-12-31"
-    MIN_BODY_SIZE = 0.1  # 最小实体大小
+    MIN_BODY_SIZE = 0.1  # 最小实体大小（绝对值）
+    FIRST_MINUTE_ONLY = True  # 反手信号仅在3分钟K线的第一分钟触发才有效
+    
+    # 突破反手信号配置
+    ENABLE_BREAKOUT_REVERSE = True  # 是否启用"突破上一根K线高低点"反手信号
+    BREAKOUT_MIN_BODY_PERCENT = 0.1  # 突破反手信号的最小实体百分比（0.1表示0.1%）
     
     # ==================== 生成查询日期列表 ====================
     dates = []
@@ -455,7 +637,13 @@ if __name__ == '__main__':
         exit(1)
     
     # ==================== 执行回测 ====================
-    trades, stats = backtest_one_third_strategy(dates, MIN_BODY_SIZE)
+    trades, stats = backtest_one_third_strategy(
+        dates, 
+        MIN_BODY_SIZE, 
+        FIRST_MINUTE_ONLY,
+        ENABLE_BREAKOUT_REVERSE,
+        BREAKOUT_MIN_BODY_PERCENT
+    )
     
     # ==================== 输出交易详情 ====================
     logger.info("===== 每笔交易详情 =====")
@@ -511,6 +699,8 @@ if __name__ == '__main__':
     print(f"{'='*60}")
     print(f"回测周期：{START_DATE} 到 {END_DATE}")
     print(f"最小实体要求：{MIN_BODY_SIZE}")
+    print(f"反手信号仅第一分钟有效：{'是' if FIRST_MINUTE_ONLY else '否'}")
+    print(f"突破反手信号：{'启用' if ENABLE_BREAKOUT_REVERSE else '禁用'}（最小实体{BREAKOUT_MIN_BODY_PERCENT}%）")
     print(f"{'='*60}")
     print(f"总交易笔数：{len(trades)}")
     print(f"总点差：{total_points_profit:.2f}")
@@ -536,7 +726,7 @@ if __name__ == '__main__':
         with open(csv_path, 'w', newline='', encoding='utf-8') as f:
             writer = csv.DictWriter(f, fieldnames=[
                 'entry_time', 'exit_time', 'direction', 'entry', 'exit', 
-                'point_diff', 'raw_profit', 'fee', 'net_profit'
+                'point_diff', 'raw_profit', 'fee', 'net_profit', 'signal_type'
             ])
             writer.writeheader()
             for t in trades:
@@ -549,6 +739,7 @@ if __name__ == '__main__':
                     'point_diff': t['point_diff'],
                     'raw_profit': t['raw_profit'],
                     'fee': t['fee'],
-                    'net_profit': t['net_profit']
+                    'net_profit': t['net_profit'],
+                    'signal_type': t.get('signal_type', '五分之一')
                 })
         print(f"\n交易记录已保存到：{csv_path}")

me/bitmart-三分之一策略交易111111111.py

@@ -0,0 +1,715 @@
+"""
+BitMart 三分之一回归策略交易（双向触发版）
+使用5分钟K线周期，实时监测
+
+策略规则：
+1. 触发价格计算（基于有效的前一根K线，实体>=0.1）：
+   - 做多触发价格 = 收盘价 + 实体/3（从收盘价往上涨1/3）
+   - 做空触发价格 = 收盘价 - 实体/3（从收盘价往下跌1/3）
+   
+2. 信号触发条件：
+   - 当前K线最高价 >= 做多触发价格 → 做多信号
+   - 当前K线最低价 <= 做空触发价格 → 做空信号
+
+3. 执行逻辑：
+   - 做多时遇到做空信号 -> 平多并反手开空
+   - 做空时遇到做多信号 -> 平空并反手开多
+   - 同一根K线内只交易一次，防止频繁反手
+
+示例1（阳线）：
+   前一根K线：开盘3000，收盘3100（阳线，实体=100）
+   - 做多触发价格 = 3100 + 33 = 3133（继续上涨做多）
+   - 做空触发价格 = 3100 - 33 = 3067（回调做空）←当前跌到这里就做空
+
+示例2（阴线）：
+   前一根K线：开盘3100，收盘3000（阴线，实体=100）
+   - 做多触发价格 = 3000 + 33 = 3033（反弹做多）
+   - 做空触发价格 = 3000 - 33 = 2967（继续下跌做空）
+"""
+
+import time
+import datetime
+
+from tqdm import tqdm
+from loguru import logger
+from bit_tools import openBrowser
+from DrissionPage import ChromiumPage
+from DrissionPage import ChromiumOptions
+
+from bitmart.api_contract import APIContract
+from 交易.tools import send_dingtalk_message
+
+
+class BitmartOneThirdStrategy:
+    def __init__(self, bit_id):
+
+        self.page: ChromiumPage | None = None
+
+        self.api_key = "6104088c65a68d7e53df5d9395b67d78e555293a"
+        self.secret_key = "a8b14312330d8e6b9b09acfd972b34e32022fdfa9f2b06f0a0a31723b873fd01"
+        self.memo = "me"
+
+        self.contract_symbol = "ETHUSDT"
+
+        self.contractAPI = APIContract(self.api_key, self.secret_key, self.memo, timeout=(5, 15))
+
+        self.start = 0  # 持仓状态: -1 空, 0 无, 1 多
+        self.direction = None
+
+        self.pbar = tqdm(total=5, desc="等待K线", ncols=80)  # 5分钟周期
+
+        self.last_kline_time = None
+
+        self.leverage = "40"  # 高杠杆（全仓模式下可开更大仓位）
+        self.open_type = "cross"  # 全仓模式
+        self.risk_percent = 0.01  # 每次开仓使用可用余额的 1%
+
+        self.open_avg_price = None  # 开仓价格
+        self.current_amount = None  # 持仓量
+
+        self.bit_id = bit_id
+
+        # 三分之一策略参数
+        self.min_body_size = 0.1  # 最小实体大小
+        self.kline_step = 5  # K线周期（5分钟）
+        self.kline_count = 20  # 获取的K线数量，用于向前查找有效K线
+
+        # 实时监测参数
+        self.check_interval = 3  # 检测间隔（秒）
+        self.last_trigger_kline_id = None  # 记录上次触发信号的K线ID，避免同一K线重复触发
+        self.last_trigger_direction = None  # 记录上次触发的方向
+        self.last_trade_kline_id = None  # 记录上次实际交易的K线ID，防止同一K线内频繁反手
+
+    # ========================= 三分之一策略核心函数 =========================
+
+    def is_bullish(self, c):
+        """判断阳线"""
+        return float(c['close']) > float(c['open'])
+
+    def is_bearish(self, c):
+        """判断阴线"""
+        return float(c['close']) < float(c['open'])
+
+    def get_body_size(self, candle):
+        """计算K线实体大小（绝对值）"""
+        return abs(float(candle['open']) - float(candle['close']))
+
+    def find_valid_prev_bar(self, all_data, current_idx, min_body_size=0.1):
+        """
+        从当前索引往前查找，直到找到实体>=min_body_size的K线
+        返回：(有效K线的索引, K线数据) 或 (None, None)
+        """
+        if current_idx <= 0:
+            return None, None
+
+        for i in range(current_idx - 1, -1, -1):
+            prev = all_data[i]
+            body_size = self.get_body_size(prev)
+            if body_size >= min_body_size:
+                return i, prev
+
+        return None, None
+
+    def get_one_third_levels(self, prev):
+        """
+        计算前一根K线实体的 1/3 双向触发价格
+        返回：(做多触发价格, 做空触发价格)
+
+        基于收盘价计算（无论阴线阳线）：
+        - 做多触发价格 = 收盘价 + 实体/3（从收盘价往上涨1/3实体）
+        - 做空触发价格 = 收盘价 - 实体/3（从收盘价往下跌1/3实体）
+
+        示例：
+        阳线 open=3000, close=3100, 实体=100
+        - 做多触发 = 3100 + 33 = 3133（继续涨）
+        - 做空触发 = 3100 - 33 = 3067（回调）
+
+        阴线 open=3100, close=3000, 实体=100
+        - 做多触发 = 3000 + 33 = 3033（反弹）
+        - 做空触发 = 3000 - 33 = 2967（继续跌）
+        """
+        p_open = float(prev['open'])
+        p_close = float(prev['close'])
+
+        body = abs(p_open - p_close)
+
+        if body < 0.001:  # 十字星，忽略
+            return None, None
+
+        # 基于收盘价的双向触发价格
+        long_trigger = p_close + body / 3  # 从收盘价往上涨1/3触发做多
+        short_trigger = p_close - body / 3  # 从收盘价往下跌1/3触发做空
+
+        return long_trigger, short_trigger
+
+    def check_trigger(self, all_data, current_idx):
+        """
+        检查当前K线是否触发了交易信号（双向检测）
+        返回：(方向, 触发价格, 有效前一根K线索引) 或 (None, None, None)
+
+        规则：
+        - 当前K线高点 >= 做多触发价格 → 做多信号
+        - 当前K线低点 <= 做空触发价格 → 做空信号
+        """
+        if current_idx <= 0:
+            return None, None, None
+
+        curr = all_data[current_idx]
+
+        # 查找实体>=min_body_size的前一根K线
+        valid_prev_idx, prev = self.find_valid_prev_bar(all_data, current_idx, self.min_body_size)
+
+        if prev is None:
+            return None, None, None
+
+        long_trigger, short_trigger = self.get_one_third_levels(prev)
+
+        if long_trigger is None:
+            return None, None, None
+
+        # 使用影线部分（high/low）来判断
+        c_high = float(curr['high'])
+        c_low = float(curr['low'])
+
+        # 检测是否触发
+        long_triggered = c_high >= long_trigger
+        short_triggered = c_low <= short_trigger
+
+        # 如果两个方向都触发，判断哪个先触发
+        if long_triggered and short_triggered:
+            c_open = float(curr['open'])
+            dist_to_long = abs(long_trigger - c_open)
+            dist_to_short = abs(short_trigger - c_open)
+            if dist_to_short <= dist_to_long:
+                return 'short', short_trigger, valid_prev_idx
+            else:
+                return 'long', long_trigger, valid_prev_idx
+
+        if short_triggered:
+            return 'short', short_trigger, valid_prev_idx
+
+        if long_triggered:
+            return 'long', long_trigger, valid_prev_idx
+
+        return None, None, None
+
+    def check_realtime_trigger(self, kline_data):
+        """
+        实时检测当前K线是否触发信号（双向检测）
+        基于已收盘的K线计算触发价格，用当前正在形成的K线判断
+        返回：(方向, 触发价格, 有效前一根K线, 当前K线) 或 (None, None, None, None)
+        """
+        if len(kline_data) < 2:
+            return None, None, None, None
+
+        # 当前正在形成的K线（最后一根，未收盘）
+        curr = kline_data[-1]
+        curr_kline_id = curr['id']
+
+        # 从倒数第二根开始往前找有效K线（已收盘的K线）
+        valid_prev_idx, prev = self.find_valid_prev_bar(kline_data, len(kline_data) - 1, self.min_body_size)
+
+        if prev is None:
+            return None, None, None, None
+
+        long_trigger, short_trigger = self.get_one_third_levels(prev)
+
+        if long_trigger is None:
+            return None, None, None, None
+
+        # 使用当前K线的实时高低点来判断
+        c_high = float(curr['high'])
+        c_low = float(curr['low'])
+
+        # 检测是否触发
+        long_triggered = c_high >= long_trigger
+        short_triggered = c_low <= short_trigger
+
+        # 确定触发方向
+        direction = None
+        trigger_price = None
+
+        if long_triggered and short_triggered:
+            # 两个方向都触发，判断哪个先（距离开盘价更近的先触发）
+            c_open = float(curr['open'])
+            dist_to_long = abs(long_trigger - c_open)
+            dist_to_short = abs(short_trigger - c_open)
+            if dist_to_short <= dist_to_long:
+                direction = 'short'
+                trigger_price = short_trigger
+            else:
+                direction = 'long'
+                trigger_price = long_trigger
+        elif short_triggered:
+            direction = 'short'
+            trigger_price = short_trigger
+        elif long_triggered:
+            direction = 'long'
+            trigger_price = long_trigger
+
+        if direction is None:
+            return None, None, None, None
+
+        # 检查是否在同一根K线内已经触发过相同方向
+        if self.last_trigger_kline_id == curr_kline_id and self.last_trigger_direction == direction:
+            return None, None, None, None
+
+        return direction, trigger_price, prev, curr
+
+    # ========================= BitMart API 函数 =========================
+
+    def get_klines(self):
+        """获取最近N根5分钟K线"""
+        try:
+            end_time = int(time.time())
+            # 获取足够多的K线用于向前查找有效K线
+            response = self.contractAPI.get_kline(
+                contract_symbol=self.contract_symbol,
+                step=self.kline_step,  # 5分钟
+                start_time=end_time - 3600 * 3,  # 取最近3小时
+                end_time=end_time
+            )[0]["data"]
+
+            # 每根: [timestamp, open, high, low, close, volume]
+            formatted = []
+            for k in response:
+                formatted.append({
+                    'id': int(k["timestamp"]),
+                    'open': float(k["open_price"]),
+                    'high': float(k["high_price"]),
+                    'low': float(k["low_price"]),
+                    'close': float(k["close_price"])
+                })
+            formatted.sort(key=lambda x: x['id'])
+            return formatted
+        except Exception as e:
+            error_msg = str(e)
+            # 检查是否是429限流错误
+            if "429" in error_msg or "too many requests" in error_msg.lower():
+                logger.warning(f"API限流，等待60秒后重试: {e}")
+                time.sleep(60)
+            else:
+                logger.error(f"获取K线异常: {e}")
+                self.ding(msg="获取K线异常", error=True)
+            return None
+
+    def get_current_price(self):
+        """获取当前最新价格"""
+        try:
+            end_time = int(time.time())
+            response = self.contractAPI.get_kline(
+                contract_symbol=self.contract_symbol,
+                step=1,  # 1分钟
+                start_time=end_time - 3600 * 3,
+                end_time=end_time
+            )[0]
+            if response['code'] == 1000:
+                return float(response['data'][-1]["close_price"])
+            return None
+        except Exception as e:
+            logger.error(f"获取价格异常: {e}")
+            return None
+
+    def get_available_balance(self):
+        """获取合约账户可用USDT余额"""
+        try:
+            response = self.contractAPI.get_assets_detail()[0]
+            if response['code'] == 1000:
+                data = response['data']
+                if isinstance(data, dict):
+                    return float(data.get('available_balance', 0))
+                elif isinstance(data, list):
+                    for asset in data:
+                        if asset.get('currency') == 'USDT':
+                            return float(asset.get('available_balance', 0))
+            return None
+        except Exception as e:
+            logger.error(f"余额查询异常: {e}")
+            return None
+
+    def get_position_status(self):
+        """获取当前持仓方向"""
+        try:
+            response = self.contractAPI.get_position(contract_symbol=self.contract_symbol)[0]
+            if response['code'] == 1000:
+                positions = response['data']
+                if not positions:
+                    self.start = 0
+                    self.open_avg_price = None
+                    self.current_amount = None
+                    self.position_cross = None
+                    return True
+                self.start = 1 if positions[0]['position_type'] == 1 else -1
+                self.open_avg_price = positions[0]['open_avg_price']
+                self.current_amount = positions[0]['current_amount']
+                self.position_cross = positions[0]["position_cross"]
+                return True
+            else:
+                return False
+        except Exception as e:
+            logger.error(f"持仓查询异常: {e}")
+            return False
+
+    def set_leverage(self):
+        """程序启动时设置全仓 + 高杠杆"""
+        try:
+            response = self.contractAPI.post_submit_leverage(
+                contract_symbol=self.contract_symbol,
+                leverage=self.leverage,
+                open_type=self.open_type
+            )[0]
+            if response['code'] == 1000:
+                logger.success(f"全仓模式 + {self.leverage}x 杠杆设置成功")
+                return True
+            else:
+                logger.error(f"杠杆设置失败: {response}")
+                return False
+        except Exception as e:
+            logger.error(f"设置杠杆异常: {e}")
+            return False
+
+    # ========================= 浏览器自动化函数 =========================
+
+    def openBrowser(self):
+        """打开 TGE 对应浏览器实例"""
+        try:
+            bit_port = openBrowser(id=self.bit_id)
+            co = ChromiumOptions()
+            co.set_local_port(port=bit_port)
+            self.page = ChromiumPage(addr_or_opts=co)
+            return True
+        except:
+            return False
+
+    def close_extra_tabs_in_browser(self):
+        """关闭多余 tab"""
+        try:
+            for idx, tab in enumerate(self.page.get_tabs()):
+                if idx > 0:
+                    tab.close()
+            return True
+        except:
+            return False
+
+    def click_safe(self, xpath, sleep=0.5):
+        """安全点击"""
+        try:
+            ele = self.page.ele(xpath)
+            if not ele:
+                return False
+            ele.scroll.to_see(center=True)
+            time.sleep(sleep)
+            ele.click(by_js=True)
+            return True
+        except:
+            return False
+
+    def 平仓(self):
+        """市价平仓"""
+        logger.info("执行平仓操作...")
+        self.click_safe('x://span[normalize-space(text()) ="市价"]')
+        time.sleep(0.5)
+        self.ding(msg="执行平仓操作")
+
+    def 开单(self, marketPriceLongOrder=0, size=None):
+        """
+        市价开单
+        marketPriceLongOrder: 1 做多, -1 做空
+        """
+        if size is None or size <= 0:
+            logger.warning("开单金额无效")
+            return False
+
+        direction_str = "做多" if marketPriceLongOrder == 1 else "做空"
+        logger.info(f"执行{direction_str}操作，金额: {size}")
+
+        size = 50
+        try:
+            if marketPriceLongOrder == -1:
+                self.click_safe('x://button[normalize-space(text()) ="市价"]')
+                self.page.ele('x://*[@id="size_0"]').input(size)
+                self.click_safe('x://span[normalize-space(text()) ="卖出/做空"]')
+            elif marketPriceLongOrder == 1:
+                self.click_safe('x://button[normalize-space(text()) ="市价"]')
+                self.page.ele('x://*[@id="size_0"]').input(size)
+                self.click_safe('x://span[normalize-space(text()) ="买入/做多"]')
+
+            self.ding(msg=f"执行{direction_str}操作，金额: {size}")
+            return True
+        except Exception as e:
+            logger.error(f"开单异常: {e}")
+            return False
+
+    def ding(self, msg, error=False):
+        """统一消息格式"""
+        prefix = "❌三分之一策略：" if error else "🔔三分之一策略："
+        if error:
+            logger.error(msg)
+            for i in range(10):
+                send_dingtalk_message(f"{prefix}{msg}")
+        else:
+            logger.info(msg)
+            send_dingtalk_message(f"{prefix}{msg}")
+
+    # ========================= 时间计算函数 =========================
+
+    def get_now_time(self):
+        """获取当前5分钟整点时间戳"""
+        current_timestamp = time.time()
+        current_datetime = datetime.datetime.fromtimestamp(current_timestamp)
+
+        # 计算距离当前时间最近的5分钟整点
+        minute = current_datetime.minute
+        target_minute = (minute // 5) * 5  # 向下取整到5分钟
+        target_datetime = current_datetime.replace(minute=target_minute, second=0, microsecond=0)
+
+        return int(target_datetime.timestamp())
+
+    def get_time_to_next_5min(self):
+        """获取距离下一个5分钟的秒数"""
+        current_timestamp = time.time()
+        current_datetime = datetime.datetime.fromtimestamp(current_timestamp)
+
+        minute = current_datetime.minute
+        next_5min = ((minute // 5) + 1) * 5
+        if next_5min >= 60:
+            next_datetime = current_datetime.replace(minute=0, second=0, microsecond=0) + datetime.timedelta(hours=1)
+        else:
+            next_datetime = current_datetime.replace(minute=next_5min, second=0, microsecond=0)
+
+        return (next_datetime - current_datetime).total_seconds()
+
+    # ========================= 主运行函数 =========================
+
+    def action(self):
+        """主运行逻辑 - 实时监测版本"""
+        # 启动时设置全仓高杠杆
+        if not self.set_leverage():
+            logger.error("杠杆设置失败，程序继续运行但可能下单失败")
+            return
+
+        # 1. 打开浏览器
+        if not self.openBrowser():
+            self.ding("打开浏览器失败！", error=True)
+            return
+        logger.info("浏览器打开成功")
+
+        if self.close_extra_tabs_in_browser():
+            logger.info('关闭多余标签页成功')
+        else:
+            logger.info('关闭多余标签页失败')
+
+        self.page.get("https://derivatives.bitmart.com/zh-CN/futures/ETHUSDT")
+        time.sleep(2)
+
+        self.click_safe('x://button[normalize-space(text()) ="市价"]')
+
+        logger.info(f"开始实时监测，检测间隔: {self.check_interval}秒")
+
+        # 用于定时发送持仓信息（每5分钟发一次）
+        last_report_time = 0
+        report_interval = 300  # 5分钟报告一次持仓
+
+        while True:
+            # 1. 打开浏览器
+            for i in range(5):
+                if self.openBrowser():
+                    break
+
+                time.sleep(5)
+            else:
+                self.ding("打开浏览器失败！", error=True)
+                return
+            logger.info("浏览器打开成功")
+
+            if self.close_extra_tabs_in_browser():
+                logger.info('关闭多余标签页成功')
+            else:
+                logger.info('关闭多余标签页失败')
+
+            self.page.get("https://derivatives.bitmart.com/zh-CN/futures/ETHUSDT")
+            time.sleep(2)
+
+            self.click_safe('x://button[normalize-space(text()) ="市价"]')
+
+            try:
+                # 获取K线数据
+                kline_data = self.get_klines()
+                if not kline_data:
+                    logger.warning("获取K线数据失败，等待重试...")
+                    time.sleep(self.check_interval)
+                    continue
+
+                if len(kline_data) < 3:
+                    logger.warning("K线数据不足")
+                    time.sleep(self.check_interval)
+                    continue
+
+                # 获取当前K线信息用于日志
+                curr = kline_data[-1]
+                curr_time_str = datetime.datetime.fromtimestamp(curr['id']).strftime('%H:%M:%S')
+
+                # ========== 实时信号检测 ==========
+                direction, trigger_price, valid_prev, curr_kline = self.check_realtime_trigger(kline_data)
+
+                if direction:
+                    curr_kline_id = curr_kline['id']
+
+                    # 检查是否在同一K线内已经交易过（防止频繁反手）
+                    if self.last_trade_kline_id == curr_kline_id:
+                        logger.debug(f"同一K线内已交易，跳过本次{direction}信号")
+                        # 更新触发记录，避免重复日志
+                        self.last_trigger_kline_id = curr_kline_id
+                        self.last_trigger_direction = direction
+                        time.sleep(self.check_interval)
+                        continue
+
+                    # 获取持仓状态
+                    if not self.get_position_status():
+                        logger.warning("获取仓位信息失败")
+                        time.sleep(self.check_interval)
+                        continue
+
+                    prev_time = datetime.datetime.fromtimestamp(valid_prev['id']).strftime('%H:%M')
+                    prev_type = "阳线" if self.is_bullish(valid_prev) else "阴线"
+                    prev_body = self.get_body_size(valid_prev)
+
+                    # 检查信号与持仓是否同向（避免重复日志）
+                    if (direction == "long" and self.start == 1) or (direction == "short" and self.start == -1):
+                        # 信号与持仓同向，静默忽略
+                        self.last_trigger_kline_id = curr_kline_id
+                        self.last_trigger_direction = direction
+                        time.sleep(self.check_interval)
+                        continue
+
+                    logger.info(f"{'=' * 50}")
+                    logger.info(f"🚨 检测到{direction}信号！触发价格: {trigger_price:.2f}")
+                    logger.info(
+                        f"  有效前一根[{prev_time}]: {prev_type} 实体={prev_body:.2f} O={valid_prev['open']:.2f} C={valid_prev['close']:.2f}")
+                    logger.info(
+                        f"  当前K线: H={curr_kline['high']:.2f} L={curr_kline['low']:.2f} C={curr_kline['close']:.2f}")
+                    logger.info(f"  当前持仓: {self.start} (1=多, -1=空, 0=无)")
+
+                    # ========== 执行交易逻辑 ==========
+                    balance = self.get_available_balance()
+                    if balance is None:
+                        balance = 0
+                    trade_size = balance * self.risk_percent
+
+                    executed = False
+                    if direction == "long":
+                        if self.start == -1:  # 当前空仓，平空开多
+                            logger.info("📈 平空仓，反手开多")
+                            self.平仓()
+                            time.sleep(1)
+                            self.开单(marketPriceLongOrder=1, size=trade_size)
+                            executed = True
+                        elif self.start == 0:  # 当前无仓，直接开多
+                            logger.info("📈 无仓位，开多")
+                            self.开单(marketPriceLongOrder=1, size=trade_size)
+                            executed = True
+
+                    elif direction == "short":
+                        if self.start == 1:  # 当前多仓，平多开空
+                            logger.info("📉 平多仓，反手开空")
+                            self.平仓()
+                            time.sleep(1)
+                            self.开单(marketPriceLongOrder=-1, size=trade_size)
+                            executed = True
+                        elif self.start == 0:  # 当前无仓，直接开空
+                            logger.info("📉 无仓位，开空")
+                            self.开单(marketPriceLongOrder=-1, size=trade_size)
+                            executed = True
+
+                    # 记录本次触发
+                    self.last_trigger_kline_id = curr_kline_id
+                    self.last_trigger_direction = direction
+
+                    if executed:
+                        # 记录交易K线，防止同一K线内频繁反手
+                        self.last_trade_kline_id = curr_kline_id
+                        # 交易后立即发送持仓信息
+                        self.get_position_status()
+                        self._send_position_message(curr_kline)
+                        last_report_time = time.time()
+
+                    logger.info(f"{'=' * 50}")
+
+                else:
+                    # 没有信号时，显示实时价格
+                    logger.debug(
+                        f"[{curr_time_str}] 现价: {curr['close']:.2f} H={curr['high']:.2f} L={curr['low']:.2f}")
+
+                # ========== 定时发送持仓信息 ==========
+                current_time = time.time()
+                if current_time - last_report_time >= report_interval:
+                    if self.get_position_status():
+                        self._send_position_message(kline_data[-1])
+                    last_report_time = current_time
+
+                # 等待下次检测
+                time.sleep(self.check_interval)
+
+            except Exception as e:
+                logger.error(f"主循环异常: {e}")
+                time.sleep(self.check_interval)
+
+            time.sleep(15)
+            self.page.close()
+            time.sleep(15)
+
+    def _send_position_message(self, latest_kline):
+        """发送持仓信息到钉钉"""
+        current_price = float(latest_kline["close"])
+        balance = self.get_available_balance()
+        self.balance = balance if balance is not None else 0.0
+
+        if self.start != 0:
+            open_avg_price = float(self.open_avg_price) if self.open_avg_price else 0.0
+            current_amount = float(self.current_amount) if self.current_amount else 0.0
+            position_cross = float(self.position_cross) if hasattr(self,
+                                                                   'position_cross') and self.position_cross else 0.0
+
+            # 计算浮动盈亏
+            if self.start == 1:  # 多头
+                unrealized_pnl = current_amount * 0.001 * (current_price - open_avg_price)
+            else:  # 空头
+                unrealized_pnl = current_amount * 0.001 * (open_avg_price - current_price)
+
+            # 计算收益率
+            if open_avg_price > 0:
+                if self.start == 1:
+                    pnl_rate = (current_price - open_avg_price) / open_avg_price * 10000
+                else:
+                    pnl_rate = (open_avg_price - current_price) / open_avg_price * 10000
+                rate_str = f" ({pnl_rate:+.2f}%)"
+            else:
+                rate_str = ""
+
+            direction_str = "空" if self.start == -1 else "多"
+            pnl_str = f"{unrealized_pnl:+.2f} USDT"
+
+            msg = (
+                f"【三分之一策略 {self.contract_symbol} 5分钟】\n"
+                f"当前方向：{direction_str}\n"
+                f"当前现价：{current_price:.2f} USDT\n"
+                f"开仓均价：{open_avg_price:.2f} USDT\n"
+                f"持仓量(eth)：{float(current_amount) / 1000} eth\n"
+                f"持仓量(usdt)：{position_cross} usdt\n"
+                f"浮动盈亏：{pnl_str}{rate_str}\n"
+                f"账户可用余额：{self.balance:.2f} usdt"
+            )
+        else:
+            msg = (
+                f"【三分之一策略 {self.contract_symbol} 5分钟】\n"
+                f"当前方向：无\n"
+                f"当前现价：{current_price:.2f} USDT\n"
+                f"账户可用余额：{self.balance:.2f} usdt"
+            )
+
+        self.ding(msg=msg)
+
+
+if __name__ == '__main__':
+    # 启动三分之一策略交易
+    BitmartOneThirdStrategy(bit_id="62f9107d0c674925972084e282df55b3").action()

open_fifth_strategy/README.md

@@ -0,0 +1,25 @@
+# 基于开盘价的五分之一策略
+
+策略规则（1111）：
+
+- **做多触发价** = 当前K线开盘价 + 前一根实体/5
+- **做空触发价** = 当前K线开盘价 - 前一根实体/5
+- **前一根有效K线**：实体 ≥ 0.1
+
+## 执行逻辑
+
+- 当前K线最高价 ≥ 做多触发价 → 做多信号
+- 当前K线最低价 ≤ 做空触发价 → 做空信号
+- 同根K线多空都触及时，用1分钟K线判断先后
+- 触及信号则开仓或反手，同根3分钟K线只交易一次
+
+## 运行
+
+```bash
+cd /path/to/lm_code
+python open_fifth_strategy/main.py
+```
+
+## 配置
+
+在 `config.py` 中修改 API、合约、杠杆等参数。

open_fifth_strategy/__init__.py

@@ -0,0 +1,2 @@
+# -*- coding: utf-8 -*-
+"""基于开盘价的五分之一策略"""

open_fifth_strategy/config.py

@@ -0,0 +1,26 @@
+# -*- coding: utf-8 -*-
+"""
+基于开盘价的五分之一策略 - 配置文件
+
+策略规则（1111）：
+- 做多触发价 = 当前K线开盘价 + 前一根实体/5
+- 做空触发价 = 当前K线开盘价 - 前一根实体/5
+- 前一根有效K线：实体 >= 0.1
+"""
+
+# BitMart API（请勿提交敏感信息到版本库）
+API_KEY = "a0fb7b98464fd9bcce67e7c519d58ec10d0c38a8"
+SECRET_KEY = "4eaeba78e77aeaab1c2027f846a276d164f264a44c2c1bb1c5f3be50c8de1ca5"
+MEMO = "合约交易"
+
+# 交易参数
+CONTRACT_SYMBOL = "ETHUSDT"
+KLINE_STEP = 3  # 3分钟K线
+MIN_BODY_SIZE = 0.1  # 有效K线最小实体
+CHECK_INTERVAL = 3  # 检测间隔（秒）
+LEVERAGE = "100"
+OPEN_TYPE = "cross"  # 全仓
+RISK_PERCENT = 0.01  # 每次开仓占用可用余额的比例
+
+# 比特浏览器ID（用于网页下单）
+BIT_ID = "f2320f57e24c45529a009e1541e25961"

open_fifth_strategy/main.py

@@ -0,0 +1,536 @@
+# -*- coding: utf-8 -*-
+"""
+BitMart 基于开盘价的五分之一策略交易
+
+策略规则（1111）：
+- 做多触发价 = 当前K线开盘价 + 实体/5
+- 做空触发价 = 当前K线开盘价 - 实体/5
+- 基于前一根有效K线（实体 >= 0.1）
+
+执行：触及做多/做空触发价则开仓或反手，同根K线只交易一次
+
+运行：python open_fifth_strategy/main.py（在项目根目录 lm_code 下）
+"""
+import sys
+from pathlib import Path
+
+_root = Path(__file__).resolve().parent.parent
+if str(_root) not in sys.path:
+    sys.path.insert(0, str(_root))
+
+import random
+import time
+from concurrent.futures import ThreadPoolExecutor
+
+from loguru import logger
+from bit_tools import openBrowser
+from DrissionPage import ChromiumPage
+from DrissionPage import ChromiumOptions
+
+from bitmart.api_contract import APIContract
+from 交易.tools import send_dingtalk_message
+
+from open_fifth_strategy.config import (
+    API_KEY,
+    SECRET_KEY,
+    MEMO,
+    CONTRACT_SYMBOL,
+    KLINE_STEP,
+    MIN_BODY_SIZE,
+    CHECK_INTERVAL,
+    LEVERAGE,
+    OPEN_TYPE,
+    RISK_PERCENT,
+    BIT_ID,
+)
+
+ding_executor = ThreadPoolExecutor(max_workers=2, thread_name_prefix="dingtalk")
+
+
+class OpenBasedFifthStrategy:
+    """基于开盘价的五分之一策略"""
+
+    def __init__(self, bit_id=None):
+        self.page = None
+        self.api_key = API_KEY
+        self.secret_key = SECRET_KEY
+        self.memo = MEMO
+        self.contract_symbol = CONTRACT_SYMBOL
+        self.contractAPI = APIContract(
+            self.api_key, self.secret_key, self.memo, timeout=(5, 15)
+        )
+
+        self.start = 0  # 持仓: -1空, 0无, 1多
+        self.open_avg_price = None
+        self.current_amount = None
+        self.position_cross = None
+        self.bit_id = bit_id or BIT_ID
+
+        self.min_body_size = MIN_BODY_SIZE
+        self.kline_step = KLINE_STEP
+        self.check_interval = CHECK_INTERVAL
+        self.leverage = LEVERAGE
+        self.open_type = OPEN_TYPE
+        self.risk_percent = RISK_PERCENT
+
+        self.last_trigger_kline_id = None
+        self.last_trigger_direction = None
+        self.last_trade_kline_id = None
+
+    # ==================== 策略核心 ====================
+
+    def get_body_size(self, candle):
+        return abs(float(candle["open"]) - float(candle["close"]))
+
+    def find_valid_prev_bar(self, all_data, current_idx):
+        """找前一根有效K线（实体>=min_body_size）"""
+        if current_idx <= 0:
+            return None, None
+        for i in range(current_idx - 1, -1, -1):
+            prev = all_data[i]
+            if self.get_body_size(prev) >= self.min_body_size:
+                return i, prev
+        return None, None
+
+    def get_trigger_levels(self, prev, curr_open):
+        """
+        基于当前K线开盘价计算触发价（1111）
+        做多触发 = 当前K线开盘价 + 实体/5
+        做空触发 = 当前K线开盘价 - 实体/5
+        """
+        body = self.get_body_size(prev)
+        if body < 0.001:
+            return None, None
+        curr_o = float(curr_open)
+        return curr_o + body / 5, curr_o - body / 5
+
+    def get_1m_bars_for_3m_bar(self, bar_3m):
+        """获取当前3分钟K线对应的3根1分钟K线"""
+        try:
+            start_ts = int(bar_3m["id"])
+            end_ts = start_ts + 3 * 60
+            response = self.contractAPI.get_kline(
+                contract_symbol=self.contract_symbol,
+                step=1,
+                start_time=start_ts,
+                end_time=end_ts,
+            )[0]
+            if response.get("code") != 1000:
+                return []
+            data = response.get("data", [])
+            out = []
+            for k in data:
+                out.append(
+                    {
+                        "id": int(k["timestamp"]),
+                        "open": float(k["open_price"]),
+                        "high": float(k["high_price"]),
+                        "low": float(k["low_price"]),
+                        "close": float(k["close_price"]),
+                    }
+                )
+            out.sort(key=lambda x: x["id"])
+            return out
+        except Exception as e:
+            logger.warning(f"获取1分钟K线失败: {e}")
+            return []
+
+    def determine_trigger_order_by_1m(self, bars_1m, long_trigger, short_trigger):
+        """同根K线多空都触及时，用1分钟K线判断先后"""
+        if not bars_1m:
+            return None
+        for bar in bars_1m:
+            high = float(bar["high"])
+            low = float(bar["low"])
+            open_price = float(bar["open"])
+            long_ok = high >= long_trigger
+            short_ok = low <= short_trigger
+            if long_ok and not short_ok:
+                return "long"
+            if short_ok and not long_ok:
+                return "short"
+            if long_ok and short_ok:
+                d_long = abs(long_trigger - open_price)
+                d_short = abs(short_trigger - open_price)
+                return "short" if d_short < d_long else "long"
+        return None
+
+    def check_trigger(self, kline_data):
+        """
+        检测当前K线是否触发信号（1111：当前开盘价±实体/5）
+        返回：(方向, 触发价, 有效前一根, 当前K线) 或 (None,...)
+        """
+        if len(kline_data) < 2:
+            return None, None, None, None
+
+        curr = kline_data[-1]
+        curr_kline_id = curr["id"]
+        curr_open = curr["open"]
+        _, prev = self.find_valid_prev_bar(kline_data, len(kline_data) - 1)
+        if prev is None:
+            return None, None, None, None
+
+        long_trigger, short_trigger = self.get_trigger_levels(prev, curr_open)
+        if long_trigger is None:
+            return None, None, None, None
+
+        c_high = float(curr["high"])
+        c_low = float(curr["low"])
+        long_triggered = c_high >= long_trigger
+        short_triggered = c_low <= short_trigger
+
+        direction = None
+        trigger_price = None
+
+        if long_triggered and short_triggered:
+            bars_1m = self.get_1m_bars_for_3m_bar(curr)
+            if bars_1m:
+                direction = self.determine_trigger_order_by_1m(
+                    bars_1m, long_trigger, short_trigger
+                )
+                trigger_price = long_trigger if direction == "long" else short_trigger
+            if direction is None:
+                c_open_f = float(curr["open"])
+                d_long = abs(long_trigger - c_open_f)
+                d_short = abs(short_trigger - c_open_f)
+                direction = "short" if d_short <= d_long else "long"
+                trigger_price = long_trigger if direction == "long" else short_trigger
+        elif short_triggered:
+            direction = "short"
+            trigger_price = short_trigger
+        elif long_triggered:
+            direction = "long"
+            trigger_price = long_trigger
+
+        if direction is None:
+            return None, None, None, None
+        if (
+            self.last_trigger_kline_id == curr_kline_id
+            and self.last_trigger_direction == direction
+        ):
+            return None, None, None, None
+
+        return direction, trigger_price, prev, curr
+
+    # ==================== BitMart API ====================
+
+    def get_klines(self):
+        try:
+            end_time = int(time.time())
+            response = self.contractAPI.get_kline(
+                contract_symbol=self.contract_symbol,
+                step=self.kline_step,
+                start_time=end_time - 3600 * 3,
+                end_time=end_time,
+            )[0]["data"]
+            formatted = []
+            for k in response:
+                formatted.append(
+                    {
+                        "id": int(k["timestamp"]),
+                        "open": float(k["open_price"]),
+                        "high": float(k["high_price"]),
+                        "low": float(k["low_price"]),
+                        "close": float(k["close_price"]),
+                    }
+                )
+            formatted.sort(key=lambda x: x["id"])
+            return formatted
+        except Exception as e:
+            if "429" in str(e) or "too many requests" in str(e).lower():
+                logger.warning(f"API限流，等待60秒: {e}")
+                time.sleep(60)
+            else:
+                logger.error(f"获取K线异常: {e}")
+                self.ding("获取K线异常", error=True)
+            return None
+
+    def get_available_balance(self):
+        try:
+            response = self.contractAPI.get_assets_detail()[0]
+            if response["code"] == 1000:
+                data = response["data"]
+                if isinstance(data, dict):
+                    return float(data.get("available_balance", 0))
+                for asset in data:
+                    if asset.get("currency") == "USDT":
+                        return float(asset.get("available_balance", 0))
+            return None
+        except Exception as e:
+            logger.error(f"余额查询异常: {e}")
+            return None
+
+    def get_position_status(self):
+        try:
+            response = self.contractAPI.get_position(
+                contract_symbol=self.contract_symbol
+            )[0]
+            if response["code"] == 1000:
+                positions = response["data"]
+                if not positions:
+                    self.start = 0
+                    self.open_avg_price = None
+                    self.current_amount = None
+                    self.position_cross = None
+                    return True
+                self.start = 1 if positions[0]["position_type"] == 1 else -1
+                self.open_avg_price = positions[0]["open_avg_price"]
+                self.current_amount = positions[0]["current_amount"]
+                self.position_cross = positions[0]["position_cross"]
+                return True
+            return False
+        except Exception as e:
+            logger.error(f"持仓查询异常: {e}")
+            return False
+
+    def set_leverage(self):
+        try:
+            response = self.contractAPI.post_submit_leverage(
+                contract_symbol=self.contract_symbol,
+                leverage=self.leverage,
+                open_type=self.open_type,
+            )[0]
+            if response["code"] == 1000:
+                logger.success(f"全仓 {self.leverage}x 杠杆设置成功")
+                return True
+            logger.error(f"杠杆设置失败: {response}")
+            return False
+        except Exception as e:
+            logger.error(f"设置杠杆异常: {e}")
+            return False
+
+    # ==================== 浏览器 ====================
+
+    def _open_browser(self):
+        try:
+            bit_port = openBrowser(id=self.bit_id)
+            co = ChromiumOptions()
+            co.set_local_port(port=bit_port)
+            self.page = ChromiumPage(addr_or_opts=co)
+            return True
+        except Exception:
+            return False
+
+    def close_extra_tabs(self):
+        try:
+            for idx, tab in enumerate(self.page.get_tabs()):
+                if idx > 0:
+                    tab.close()
+            return True
+        except Exception:
+            return False
+
+    def click_safe(self, xpath, sleep=0.5):
+        try:
+            ele = self.page.ele(xpath)
+            if not ele:
+                return False
+            ele.scroll.to_see(center=True)
+            time.sleep(sleep)
+            ele.click(by_js=True)
+            return True
+        except Exception:
+            return False
+
+    def 平仓(self):
+        logger.info("执行平仓...")
+        self.click_safe('x://span[normalize-space(text()) ="市价"]')
+        time.sleep(0.5)
+        self.ding("执行平仓操作")
+
+    def 开单(self, marketPriceLongOrder=0, size=None):
+        if size is None or size <= 0:
+            logger.warning("开单金额无效")
+            return False
+        direction_str = "做多" if marketPriceLongOrder == 1 else "做空"
+        logger.info(f"执行{direction_str}，金额: {size}")
+        size = max(1, min(25, int(size)))
+        try:
+            self.click_safe('x://button[normalize-space(text()) ="市价"]')
+            self.page.ele('x://*[@id="size_0"]').input(str(size))
+            if marketPriceLongOrder == -1:
+                self.click_safe('x://span[normalize-space(text()) ="卖出/做空"]')
+            else:
+                self.click_safe('x://span[normalize-space(text()) ="买入/做多"]')
+            self.ding(f"执行{direction_str}，金额: {size}")
+            return True
+        except Exception as e:
+            logger.error(f"开单异常: {e}")
+            return False
+
+    def ding(self, msg, error=False):
+        prefix = "❌五分之一：" if error else "🔔五分之一："
+        full_msg = f"{prefix}{msg}"
+        if error:
+            logger.error(msg)
+            for _ in range(3):
+                ding_executor.submit(self._send_ding_safe, full_msg)
+        else:
+            logger.info(msg)
+            ding_executor.submit(self._send_ding_safe, full_msg)
+
+    def _send_ding_safe(self, msg):
+        try:
+            send_dingtalk_message(msg)
+        except Exception as e:
+            logger.warning(f"消息发送失败: {e}")
+
+    def _send_position_message(self, latest_kline):
+        current_price = float(latest_kline["close"])
+        balance = self.get_available_balance()
+        self.balance = balance if balance is not None else 0.0
+        if self.start != 0:
+            open_avg_price = float(self.open_avg_price)
+            current_amount = float(self.current_amount)
+            position_cross = float(getattr(self, "position_cross", 0) or 0)
+            if self.start == 1:
+                unrealized_pnl = current_amount * 0.001 * (
+                    current_price - open_avg_price
+                )
+            else:
+                unrealized_pnl = current_amount * 0.001 * (
+                    open_avg_price - current_price
+                )
+            pnl_rate = (
+                (current_price - open_avg_price) / open_avg_price * 100
+                if self.start == 1
+                else (open_avg_price - current_price) / open_avg_price * 100
+            )
+            direction_str = "空" if self.start == -1 else "多"
+            msg = (
+                f"【五分之一 {self.contract_symbol}】\n"
+                f"方向：{direction_str}\n"
+                f"现价：{current_price:.2f}\n"
+                f"开仓均价：{open_avg_price:.2f}\n"
+                f"浮动盈亏：{unrealized_pnl:+.2f} USDT ({pnl_rate:+.2f}%)\n"
+                f"余额：{self.balance:.2f}"
+            )
+        else:
+            msg = (
+                f"【五分之一 {self.contract_symbol}】\n"
+                f"方向：无\n"
+                f"现价：{current_price:.2f}\n"
+                f"余额：{self.balance:.2f}"
+            )
+        self.ding(msg)
+
+    # ==================== 主循环 ====================
+
+    def action(self):
+        if not self.set_leverage():
+            logger.error("杠杆设置失败")
+            return
+        if not self._open_browser():
+            self.ding("打开浏览器失败！", error=True)
+            return
+        logger.info("浏览器打开成功")
+        self.close_extra_tabs()
+        self.page.get("https://derivatives.bitmart.com/zh-CN/futures/ETHUSDT")
+        time.sleep(2)
+        self.click_safe('x://button[normalize-space(text()) ="市价"]')
+        logger.info(
+            f"五分之一策略（3分钟K线）开始监测，间隔: {self.check_interval}秒"
+        )
+
+        last_report_time = 0
+        report_interval = 300
+
+        while True:
+            for _ in range(5):
+                if self._open_browser():
+                    break
+                time.sleep(5)
+            else:
+                self.ding("打开浏览器失败！", error=True)
+                return
+            self.close_extra_tabs()
+            self.page.get("https://derivatives.bitmart.com/zh-CN/futures/ETHUSDT")
+            time.sleep(2)
+            self.click_safe('x://button[normalize-space(text()) ="市价"]')
+
+            try:
+                kline_data = self.get_klines()
+                if not kline_data or len(kline_data) < 3:
+                    logger.warning("K线数据不足...")
+                    time.sleep(self.check_interval)
+                    continue
+
+                curr = kline_data[-1]
+                if not self.get_position_status():
+                    logger.warning("获取仓位失败，使用缓存")
+
+                direction, trigger_price, valid_prev, curr_kline = (
+                    self.check_trigger(kline_data)
+                )
+
+                if direction:
+                    curr_kline_id = curr_kline["id"]
+                    if self.last_trade_kline_id == curr_kline_id:
+                        self.last_trigger_kline_id = curr_kline_id
+                        self.last_trigger_direction = direction
+                        time.sleep(self.check_interval)
+                        continue
+
+                    if (direction == "long" and self.start == 1) or (
+                        direction == "short" and self.start == -1
+                    ):
+                        self.last_trigger_kline_id = curr_kline_id
+                        self.last_trigger_direction = direction
+                        time.sleep(self.check_interval)
+                        continue
+
+                    balance = self.get_available_balance()
+                    trade_size = (balance or 0) * self.risk_percent
+                    executed = False
+
+                    if direction == "long":
+                        if self.start == -1:
+                            self.平仓()
+                            time.sleep(1)
+                            self.开单(marketPriceLongOrder=1, size=trade_size)
+                            executed = True
+                        elif self.start == 0:
+                            self.开单(marketPriceLongOrder=1, size=trade_size)
+                            executed = True
+                    elif direction == "short":
+                        if self.start == 1:
+                            self.平仓()
+                            time.sleep(1)
+                            self.开单(marketPriceLongOrder=-1, size=trade_size)
+                            executed = True
+                        elif self.start == 0:
+                            self.开单(marketPriceLongOrder=-1, size=trade_size)
+                            executed = True
+
+                    self.last_trigger_kline_id = curr_kline_id
+                    self.last_trigger_direction = direction
+                    if executed:
+                        self.last_trade_kline_id = curr_kline_id
+                        self.get_position_status()
+                        self._send_position_message(curr_kline)
+                        last_report_time = time.time()
+
+                if time.time() - last_report_time >= report_interval:
+                    if self.get_position_status():
+                        self._send_position_message(kline_data[-1])
+                    last_report_time = time.time()
+
+                time.sleep(self.check_interval)
+
+            except Exception as e:
+                logger.error(f"主循环异常: {e}")
+                time.sleep(self.check_interval)
+            time.sleep(3)
+            if random.randint(1, 10) > 7:
+                self.page.close()
+                time.sleep(15)
+
+
+if __name__ == "__main__":
+    try:
+        OpenBasedFifthStrategy(bit_id=BIT_ID).action()
+    except KeyboardInterrupt:
+        logger.info("程序被用户中断")
+    finally:
+        ding_executor.shutdown(wait=True)
+        logger.info("已退出")

交易/bitmart-五分之一策略交易.py

@@ -19,7 +19,7 @@ BitMart 五分之一回归策略交易（精准版）
 4. 精准判断（使用1分钟K线）：
    - 当当前3分钟K线同时触及做多和做空价格时，拉取该3分钟对应的3根1分钟K线判断哪个方向先被触发
 """
-
+import random
 import time
 import datetime
 from concurrent.futures import ThreadPoolExecutor
@@ -71,6 +71,18 @@ class BitmartOneFifthStrategy:
         self.last_trigger_kline_id = None
         self.last_trigger_direction = None
         self.last_trade_kline_id = None
+        
+        # 反手信号当前价格容差（美元）
+        # 当检测到反手信号时，当前价格必须在触发价附近才执行
+        # 避免"先涨后跌"或"先跌后涨"的情况下错误开仓
+        self.reverse_price_tolerance = 2.0  # 2美元容差
+        
+        # 基于开仓价格的反手信号参数
+        # 记录开仓时使用的前一根K线实体大小（用于计算反手触发价）
+        self.entry_prev_body = None  # 开仓时前一根K线的实体大小
+        self.entry_price = None  # 开仓价格（用于计算反手触发价）
+        self.entry_kline_id = None  # 开仓时的K线ID（用于判断是否在同一根K线内）
+        self.first_minute_reverse_executed = False  # 当前K线是否已执行过第一分钟反手
 
     # ========================= 五分之一策略核心 =========================
 
@@ -158,10 +170,105 @@ class BitmartOneFifthStrategy:
                 return 'short' if d_short < d_long else 'long'
         return None
 
-    def check_realtime_trigger(self, kline_data):
+    def check_first_minute_reverse_signal(self, curr_kline, kline_data):
+        """
+        检测基于开仓价格的反手信号（只在3分钟K线的第一分钟有效）
+        
+        反手规则：
+        - 空仓反手开多：开空仓后，价格涨到 开仓价格 + 前一根K线实体/5 → 平空开多
+        - 多仓反手开空：开多仓后，价格跌到 开仓价格 - 前一根K线实体/5 → 平多开空
+        
+        :param curr_kline: 当前3分钟K线数据
+        :param kline_data: 所有K线数据（用于获取前一根K线实体）
+        :return: (方向, 触发价格) 或 (None, None)
+        """
+        # 检查是否有持仓
+        if self.start == 0:
+            return None, None
+        
+        curr_kline_id = curr_kline['id']
+        
+        # 如果K线切换了，重置第一分钟反手标记
+        if self.entry_kline_id != curr_kline_id:
+            self.first_minute_reverse_executed = False
+            self.entry_kline_id = curr_kline_id  # 更新当前K线ID
+        
+        # 检查当前K线是否已执行过第一分钟反手
+        if self.first_minute_reverse_executed:
+            return None, None
+        
+        # 获取开仓价格（如果没有记录，使用API返回的开仓均价）
+        entry_price = self.entry_price
+        if entry_price is None and self.open_avg_price:
+            entry_price = float(self.open_avg_price)
+        if entry_price is None:
+            return None, None
+        
+        # 获取前一根有效K线的实体大小
+        valid_prev_idx, valid_prev = self.find_valid_prev_bar(kline_data, len(kline_data) - 1, self.min_body_size)
+        if valid_prev is None:
+            return None, None
+        prev_body = self.get_body_size(valid_prev)
+        
+        # 计算反手触发价格
+        reverse_offset = prev_body / 5
+        
+        # 获取第一分钟K线
+        bars_1m = self.get_1m_bars_for_3m_bar(curr_kline)
+        if not bars_1m or len(bars_1m) < 1:
+            return None, None
+        
+        first_1m = bars_1m[0]  # 第一分钟K线
+        first_1m_high = float(first_1m['high'])
+        first_1m_low = float(first_1m['low'])
+        first_1m_close = float(first_1m['close'])
+        
+        if self.start == -1:
+            # 持有空仓，检测反手开多信号
+            # 反手触发价 = 开仓价格 + 前一根实体/5
+            reverse_long_trigger = entry_price + reverse_offset
+            
+            # 检查第一分钟是否触及反手触发价
+            if first_1m_high >= reverse_long_trigger:
+                # 第一分钟高点触及反手触发价，并且当前价格在触发价附近
+                if first_1m_close >= reverse_long_trigger - self.reverse_price_tolerance:
+                    logger.info(f"🔄 第一分钟反手信号检测：持空仓，第一分钟高点{first_1m_high:.2f}>=反手触发价{reverse_long_trigger:.2f}")
+                    logger.info(f"   开仓价={entry_price:.2f}, 前一根实体={prev_body:.2f}, 实体/5={reverse_offset:.2f}")
+                    return 'long', reverse_long_trigger
+                else:
+                    logger.debug(f"第一分钟反手信号被过滤：当前价格{first_1m_close:.2f}已远离触发价{reverse_long_trigger:.2f}")
+        
+        elif self.start == 1:
+            # 持有多仓，检测反手开空信号
+            # 反手触发价 = 开仓价格 - 前一根实体/5
+            reverse_short_trigger = entry_price - reverse_offset
+            
+            # 检查第一分钟是否触及反手触发价
+            if first_1m_low <= reverse_short_trigger:
+                # 第一分钟低点触及反手触发价，并且当前价格在触发价附近
+                if first_1m_close <= reverse_short_trigger + self.reverse_price_tolerance:
+                    logger.info(f"🔄 第一分钟反手信号检测：持多仓，第一分钟低点{first_1m_low:.2f}<=反手触发价{reverse_short_trigger:.2f}")
+                    logger.info(f"   开仓价={entry_price:.2f}, 前一根实体={prev_body:.2f}, 实体/5={reverse_offset:.2f}")
+                    return 'short', reverse_short_trigger
+                else:
+                    logger.debug(f"第一分钟反手信号被过滤：当前价格{first_1m_close:.2f}已远离触发价{reverse_short_trigger:.2f}")
+        
+        return None, None
+
+    def check_realtime_trigger(self, kline_data, current_position=0):
         """
         实时检测当前3分钟K线是否触发信号
-        若多空都触发，优先用1分钟K线判断先后，否则用开盘价距离
+        
+        参数:
+            kline_data: K线数据列表
+            current_position: 当前持仓状态 (1=多, -1=空, 0=无)
+        
+        逻辑优化：
+        - 当已有持仓时，只关心反向信号（有多仓只看空信号，有空仓只看多信号）
+        - 无仓位时，用1分钟K线判断先触发的方向
+        - 【重要】反手信号不仅要求K线高/低点触及触发价，还要求当前价格在触发价附近
+          避免"先涨后跌"或"先跌后涨"的情况下错误开仓
+        
         返回：(方向, 触发价格, 有效前一根K线, 当前K线) 或 (None, None, None, None)
         """
         if len(kline_data) < 2:
@@ -181,31 +288,57 @@ class BitmartOneFifthStrategy:
 
         c_high = float(curr['high'])
         c_low = float(curr['low'])
+        c_close = float(curr['close'])  # 当前价格（用于检查价格是否仍在触发价附近）
+        
         long_triggered = c_high >= long_trigger
         short_triggered = c_low <= short_trigger
 
         direction = None
         trigger_price = None
 
-        if long_triggered and short_triggered:
-            bars_1m = self.get_1m_bars_for_3m_bar(curr)
-            if bars_1m:
-                direction = self.determine_trigger_order_by_1m(
-                    bars_1m, long_trigger, short_trigger
-                )
-                trigger_price = long_trigger if direction == 'long' else short_trigger
-            if direction is None:
-                c_open = float(curr['open'])
-                d_long = abs(long_trigger - c_open)
-                d_short = abs(short_trigger - c_open)
-                direction = 'short' if d_short <= d_long else 'long'
-                trigger_price = long_trigger if direction == 'long' else short_trigger
-        elif short_triggered:
-            direction = 'short'
-            trigger_price = short_trigger
-        elif long_triggered:
-            direction = 'long'
-            trigger_price = long_trigger
+        # 关键优化：根据当前持仓状态决定关注哪个方向的信号
+        if current_position == 1:
+            # 当前是多仓，只关心空信号（用于平多开空）
+            if short_triggered:
+                # 【重要】额外检查：当前价格必须在做空触发价附近或下方
+                # 如果价格已经涨回去了（当前价格远高于做空触发价），则不触发
+                if c_close <= short_trigger + self.reverse_price_tolerance:
+                    direction = 'short'
+                    trigger_price = short_trigger
+                else:
+                    logger.debug(f"空信号被过滤：当前价格{c_close:.2f}已远离做空触发价{short_trigger:.2f}（容差{self.reverse_price_tolerance}）")
+                    
+        elif current_position == -1:
+            # 当前是空仓，只关心多信号（用于平空开多）
+            if long_triggered:
+                # 【重要】额外检查：当前价格必须在做多触发价附近或上方
+                # 如果价格已经跌回去了（当前价格远低于做多触发价），则不触发
+                if c_close >= long_trigger - self.reverse_price_tolerance:
+                    direction = 'long'
+                    trigger_price = long_trigger
+                else:
+                    logger.debug(f"多信号被过滤：当前价格{c_close:.2f}已远离做多触发价{long_trigger:.2f}（容差{self.reverse_price_tolerance}）")
+        else:
+            # 无仓位，按原逻辑判断先触发的方向
+            if long_triggered and short_triggered:
+                bars_1m = self.get_1m_bars_for_3m_bar(curr)
+                if bars_1m:
+                    direction = self.determine_trigger_order_by_1m(
+                        bars_1m, long_trigger, short_trigger
+                    )
+                    trigger_price = long_trigger if direction == 'long' else short_trigger
+                if direction is None:
+                    c_open = float(curr['open'])
+                    d_long = abs(long_trigger - c_open)
+                    d_short = abs(short_trigger - c_open)
+                    direction = 'short' if d_short <= d_long else 'long'
+                    trigger_price = long_trigger if direction == 'long' else short_trigger
+            elif short_triggered:
+                direction = 'short'
+                trigger_price = short_trigger
+            elif long_triggered:
+                direction = 'long'
+                trigger_price = long_trigger
 
         if direction is None:
             return None, None, None, None
@@ -383,7 +516,7 @@ class BitmartOneFifthStrategy:
         """
         prefix = "❌五分之一策略：" if error else "🔔五分之一策略："
         full_msg = f"{prefix}{msg}"
-        
+
         if error:
             logger.error(msg)
             # 异步发送多条错误消息
@@ -393,7 +526,7 @@ class BitmartOneFifthStrategy:
             logger.info(msg)
             # 异步发送单条消息
             ding_executor.submit(self._send_ding_safe, full_msg)
-    
+
     def _send_ding_safe(self, msg):
         """
         安全发送钉钉消息，捕获异常防止线程崩溃
@@ -449,7 +582,74 @@ class BitmartOneFifthStrategy:
 
                 curr = kline_data[-1]
                 curr_time_str = datetime.datetime.fromtimestamp(curr['id']).strftime('%H:%M:%S')
-                direction, trigger_price, valid_prev, curr_kline = self.check_realtime_trigger(kline_data)
+                
+                # 优化：先获取持仓状态，再检测信号（传入持仓状态以便只关注反向信号）
+                if not self.get_position_status():
+                    logger.warning("获取仓位信息失败，使用缓存的持仓状态")
+                
+                # ========== 第一分钟反手信号检测 ==========
+                # 如果有持仓，先检测基于开仓价格的第一分钟反手信号
+                first_min_direction = None
+                first_min_trigger_price = None
+                if self.start != 0:
+                    first_min_direction, first_min_trigger_price = self.check_first_minute_reverse_signal(curr, kline_data)
+                
+                # 如果检测到第一分钟反手信号，优先执行
+                if first_min_direction:
+                    curr_kline_id = curr['id']
+                    if self.last_trade_kline_id != curr_kline_id:
+                        logger.info(f"{'=' * 50}")
+                        # 安全获取开仓价格和前一根实体
+                        entry_price_display = self.entry_price if self.entry_price else (float(self.open_avg_price) if self.open_avg_price else 0)
+                        entry_body_display = self.entry_prev_body if self.entry_prev_body else 0
+                        logger.info(f"🔄 第一分钟反手信号触发！方向: {first_min_direction}, 触发价: {first_min_trigger_price:.2f}")
+                        logger.info(f"  开仓价: {entry_price_display:.2f}, 前一根实体/5: {entry_body_display/5:.2f}")
+                        logger.info(f"  当前持仓: {self.start} (1=多, -1=空)")
+                        
+                        balance = self.get_available_balance()
+                        trade_size = (balance or 0) * self.risk_percent
+                        
+                        if first_min_direction == 'long' and self.start == -1:
+                            logger.info("📈 第一分钟反手：平空仓，反手开多")
+                            self.平仓()
+                            time.sleep(1)
+                            self.开单(marketPriceLongOrder=1, size=trade_size)
+                            self.first_minute_reverse_executed = True
+                            self.last_trade_kline_id = curr_kline_id
+                            # 更新开仓信息
+                            valid_prev_idx, valid_prev = self.find_valid_prev_bar(kline_data, len(kline_data) - 1, self.min_body_size)
+                            if valid_prev:
+                                self.entry_prev_body = self.get_body_size(valid_prev)
+                            self.entry_price = float(curr['close'])
+                            self.entry_kline_id = curr_kline_id
+                            self.get_position_status()
+                            self._send_position_message(curr)
+                            
+                        elif first_min_direction == 'short' and self.start == 1:
+                            logger.info("📉 第一分钟反手：平多仓，反手开空")
+                            self.平仓()
+                            time.sleep(1)
+                            self.开单(marketPriceLongOrder=-1, size=trade_size)
+                            self.first_minute_reverse_executed = True
+                            self.last_trade_kline_id = curr_kline_id
+                            # 更新开仓信息
+                            valid_prev_idx, valid_prev = self.find_valid_prev_bar(kline_data, len(kline_data) - 1, self.min_body_size)
+                            if valid_prev:
+                                self.entry_prev_body = self.get_body_size(valid_prev)
+                            self.entry_price = float(curr['close'])
+                            self.entry_kline_id = curr_kline_id
+                            self.get_position_status()
+                            self._send_position_message(curr)
+                        
+                        logger.info(f"{'=' * 50}")
+                        time.sleep(self.check_interval)
+                        continue
+                
+                # ========== 原有的五分之一信号检测 ==========
+                # 传入当前持仓状态，确保有持仓时只关注反向信号
+                direction, trigger_price, valid_prev, curr_kline = self.check_realtime_trigger(
+                    kline_data, current_position=self.start
+                )
 
                 if direction:
                     curr_kline_id = curr_kline['id']
@@ -458,16 +658,15 @@ class BitmartOneFifthStrategy:
                         self.last_trigger_direction = direction
                         time.sleep(self.check_interval)
                         continue
-                    if not self.get_position_status():
-                        logger.warning("获取仓位信息失败")
-                        time.sleep(self.check_interval)
-                        continue
 
                     prev_time = datetime.datetime.fromtimestamp(valid_prev['id']).strftime('%H:%M')
                     prev_type = "阳线" if self.is_bullish(valid_prev) else "阴线"
                     prev_body = self.get_body_size(valid_prev)
 
+                    # 由于 check_realtime_trigger 已经考虑了持仓状态，这里理论上不会出现同向信号
+                    # 但保留这个检查作为安全措施
                     if (direction == "long" and self.start == 1) or (direction == "short" and self.start == -1):
+                        logger.debug(f"同向信号被过滤: direction={direction}, position={self.start}")
                         self.last_trigger_kline_id = curr_kline_id
                         self.last_trigger_direction = direction
                         time.sleep(self.check_interval)
@@ -512,6 +711,13 @@ class BitmartOneFifthStrategy:
                     self.last_trigger_direction = direction
                     if executed:
                         self.last_trade_kline_id = curr_kline_id
+                        # 记录开仓信息，用于第一分钟反手信号检测
+                        self.entry_price = trigger_price  # 开仓触发价格
+                        self.entry_prev_body = self.get_body_size(valid_prev)  # 前一根K线实体大小
+                        self.entry_kline_id = curr_kline_id  # 开仓时的K线ID
+                        self.first_minute_reverse_executed = False  # 重置第一分钟反手标记
+                        logger.info(f"  记录开仓信息：开仓价={self.entry_price:.2f}, 前一根实体={self.entry_prev_body:.2f}, K线ID={self.entry_kline_id}")
+                        
                         self.get_position_status()
                         self._send_position_message(curr_kline)
                         last_report_time = time.time()
@@ -529,9 +735,11 @@ class BitmartOneFifthStrategy:
             except Exception as e:
                 logger.error(f"主循环异常: {e}")
                 time.sleep(self.check_interval)
-            time.sleep(15)
-            self.page.close()
-            time.sleep(15)
+            time.sleep(3)
+
+            if random.randint(1,10)>7:
+                self.page.close()
+                time.sleep(15)
 
     def _send_position_message(self, latest_kline):
         current_price = float(latest_kline["close"])