第一版策略

bb_trade.py

@@ -1,6 +1,6 @@
 """
 布林带均值回归策略 — 实盘交易 (D方案: 递增加仓)
-BB(10, 2.5) | 5分钟K线 | ETH | 50x杠杆 | 递增加仓+1%/次 max=3
+BB(10, 2.5) | 5分钟K线 | ETH | 50x杠杆 逐仓 | 递增加仓+1%/次 max=3
 
 逻辑:
   - 价格触及上布林带 → 平多(如有) + 开空; 已持空则加仓
@@ -43,7 +43,7 @@ class BBTradeConfig:
 
     # 仓位管理
     LEVERAGE = 50           # 杠杆倍数
-    OPEN_TYPE = "cross"     # 全仓模式
+    OPEN_TYPE = "isolated"  # 逐仓模式
     MARGIN_PCT = 0.01       # 首次开仓用权益的1%作为保证金
 
     # 递增加仓 (D方案)
@@ -207,7 +207,7 @@ class BBTrader:
             return False
 
     def set_leverage(self) -> bool:
-        """设置杠杆和全仓模式"""
+        """设置杠杆和逐仓模式"""
         try:
             resp = self.api.post_submit_leverage(
                 contract_symbol=self.cfg.CONTRACT_SYMBOL,

strategy/bb_backtest.py

@@ -36,8 +36,24 @@ class BBConfig:
 
     # Risk management
     max_daily_loss: float = 150.0   # stop trading after this daily loss
+    max_daily_loss_pct: float = 0.0  # if >0, daily loss limit = equity * pct (overrides fixed)
     stop_loss_pct: float = 0.0      # 0 = disabled; e.g. 0.02 = 2% SL from entry
 
+    # Liquidation
+    liq_enabled: bool = True         # enable liquidation simulation
+    cross_margin: bool = True        # 全仓模式: 仅当 equity<=0 爆仓; False=逐仓: 按仓位保证金算强平价
+    maint_margin_rate: float = 0.005 # 逐仓时用: 0.5% 维持保证金率
+
+    # Slippage: applied to each trade execution price
+    slippage_pct: float = 0.0005     # 0.05% slippage per trade
+
+    # 成交价模式: False=理想(在触轨的极价成交), True=真实(在K线收盘价成交)
+    # 实盘检测到触及布林带后以市价单成交，通常接近收盘价
+    fill_at_close: bool = False
+
+    # Max single order notional (market capacity limit, USDT)
+    max_notional: float = 0.0        # 0 = unlimited; e.g. 500000 = 50万U max per order
+
     # Dynamic sizing: if > 0, margin = equity * margin_pct (overrides margin_per_trade)
     margin_pct: float = 0.0          # e.g. 0.01 = 1% of equity per trade
 
@@ -124,6 +140,7 @@ def run_bb_backtest(df: pd.DataFrame, cfg: BBConfig) -> BBResult:
     day_pnl = 0.0
     day_stopped = False
     current_day = None
+    day_start_equity = cfg.initial_capital  # equity at start of each day
 
     # Delayed rebate tracking
     pending_rebate = 0.0       # fees from previous day to be rebated
@@ -151,6 +168,12 @@ def run_bb_backtest(df: pd.DataFrame, cfg: BBConfig) -> BBResult:
         if position == 0:
             return
 
+        # Apply slippage: closing long sells lower, closing short buys higher
+        if position == 1:
+            exit_price = exit_price * (1 - cfg.slippage_pct)
+        else:
+            exit_price = exit_price * (1 + cfg.slippage_pct)
+
         if position == 1:
             gross = entry_qty * (exit_price - entry_price)
         else:
@@ -193,6 +216,12 @@ def run_bb_backtest(df: pd.DataFrame, cfg: BBConfig) -> BBResult:
         nonlocal balance, total_fee, day_pnl, today_fees
         nonlocal pyramid_count, last_add_margin
 
+        # Apply slippage: buy higher, sell lower
+        if side == "long" or (is_add and position == 1):
+            price = price * (1 + cfg.slippage_pct)
+        else:
+            price = price * (1 - cfg.slippage_pct)
+
         if is_add and cfg.pyramid_step > 0:
             # 递增加仓: margin = equity * (margin_pct + step * (count+1))
             equity = balance + unrealised(price)
@@ -210,6 +239,12 @@ def run_bb_backtest(df: pd.DataFrame, cfg: BBConfig) -> BBResult:
         if margin <= 0:
             return
         notional = margin * cfg.leverage
+
+        # Cap notional to market capacity limit
+        if cfg.max_notional > 0 and notional > cfg.max_notional:
+            notional = cfg.max_notional
+            margin = notional / cfg.leverage
+
         qty = notional / price
         fee = notional * cfg.fee_rate
 
@@ -245,9 +280,10 @@ def run_bb_backtest(df: pd.DataFrame, cfg: BBConfig) -> BBResult:
         if bar_day is not None and bar_day != current_day:
             # New day: move today's fees to pending, reset
             if cfg.rebate_pct > 0:
-                pending_rebate = today_fees * cfg.rebate_pct
+                pending_rebate += today_fees * cfg.rebate_pct
                 today_fees = 0.0
             rebate_applied_today = False
+            day_start_equity = balance + unrealised(arr_close[i])
             day_pnl = 0.0
             day_stopped = False
             current_day = bar_day
@@ -266,7 +302,7 @@ def run_bb_backtest(df: pd.DataFrame, cfg: BBConfig) -> BBResult:
             out_position[i] = position
             continue
 
-        # Daily loss check
+        # Daily loss check (percentage-based if configured, else fixed)
         if day_stopped:
             out_equity[i] = balance + unrealised(arr_close[i])
             out_balance[i] = balance
@@ -274,7 +310,12 @@ def run_bb_backtest(df: pd.DataFrame, cfg: BBConfig) -> BBResult:
             continue
 
         cur_equity = balance + unrealised(arr_close[i])
-        if day_pnl + unrealised(arr_close[i]) <= -cfg.max_daily_loss:
+        if cfg.max_daily_loss_pct > 0:
+            # percentage-based: use start-of-day equity
+            daily_loss_limit = day_start_equity * cfg.max_daily_loss_pct
+        else:
+            daily_loss_limit = cfg.max_daily_loss
+        if day_pnl + unrealised(arr_close[i]) <= -daily_loss_limit:
             close_position(arr_close[i], i)
             day_stopped = True
             out_equity[i] = balance
@@ -291,39 +332,124 @@ def run_bb_backtest(df: pd.DataFrame, cfg: BBConfig) -> BBResult:
                 sl_price = entry_price * (1 + cfg.stop_loss_pct)
                 close_position(sl_price, i)
 
+        # Liquidation check
+        # 全仓(cross_margin): 仅当 账户权益<=0 时爆仓，整仓担保
+        # 逐仓: 按仓位保证金算强平价
+        if position != 0 and cfg.liq_enabled and entry_margin > 0:
+            cur_equity = balance + unrealised(arr_close[i])
+            upnl = unrealised(arr_close[i])
+            if cfg.cross_margin:
+                # 全仓: 只有权益归零才爆仓
+                if cur_equity <= 0:
+                    balance += upnl  # 实现亏损
+                    balance = max(0.0, balance)
+                    day_pnl += upnl
+                    trades.append(BBTrade(
+                        side="long" if position == 1 else "short",
+                        entry_price=entry_price, exit_price=arr_close[i],
+                        entry_time=entry_time, exit_time=ts_index[i],
+                        margin=entry_margin, leverage=cfg.leverage, qty=entry_qty,
+                        gross_pnl=upnl, fee=0.0, net_pnl=upnl,
+                    ))
+                    position = 0
+                    entry_price = 0.0
+                    entry_time = None
+                    entry_margin = 0.0
+                    entry_qty = 0.0
+                    pyramid_count = 0
+                    last_add_margin = 0.0
+                    out_equity[i] = balance
+                    out_balance[i] = balance
+                    out_position[i] = 0
+                    if balance <= 0:
+                        out_equity[i:] = 0.0
+                        out_balance[i:] = 0.0
+                        break
+            else:
+                # 逐仓: 按强平价
+                liq_threshold = 1.0 / cfg.leverage * (1 - cfg.maint_margin_rate)
+                if position == 1:
+                    liq_price = entry_price * (1 - liq_threshold)
+                    if arr_low[i] <= liq_price:
+                        balance -= entry_margin
+                        day_pnl -= entry_margin
+                        trades.append(BBTrade(
+                            side="long", entry_price=entry_price, exit_price=liq_price,
+                            entry_time=entry_time, exit_time=ts_index[i],
+                            margin=entry_margin, leverage=cfg.leverage, qty=entry_qty,
+                            gross_pnl=-entry_margin, fee=0.0, net_pnl=-entry_margin,
+                        ))
+                        position = 0
+                        entry_price = 0.0
+                        entry_time = None
+                        entry_margin = 0.0
+                        entry_qty = 0.0
+                        pyramid_count = 0
+                        last_add_margin = 0.0
+                        if balance <= 0:
+                            balance = 0.0
+                            out_equity[i] = 0.0
+                            out_balance[i] = 0.0
+                            out_position[i] = 0
+                            out_equity[i:] = 0.0
+                            out_balance[i:] = 0.0
+                            break
+                elif position == -1:
+                    liq_price = entry_price * (1 + liq_threshold)
+                    if arr_high[i] >= liq_price:
+                        balance -= entry_margin
+                        day_pnl -= entry_margin
+                        trades.append(BBTrade(
+                            side="short", entry_price=entry_price, exit_price=liq_price,
+                            entry_time=entry_time, exit_time=ts_index[i],
+                            margin=entry_margin, leverage=cfg.leverage, qty=entry_qty,
+                            gross_pnl=-entry_margin, fee=0.0, net_pnl=-entry_margin,
+                        ))
+                        position = 0
+                        entry_price = 0.0
+                        entry_time = None
+                        entry_margin = 0.0
+                        entry_qty = 0.0
+                        pyramid_count = 0
+                        last_add_margin = 0.0
+                        if balance <= 0:
+                            balance = 0.0
+                            out_equity[i:] = 0.0
+                            out_balance[i:] = 0.0
+                            break
+
         # Signal detection: use high/low to check if price touched BB
         touched_upper = arr_high[i] >= arr_upper[i]
         touched_lower = arr_low[i] <= arr_lower[i]
 
+        # 成交价: fill_at_close=True 时用收盘价(模拟实盘市价单)，否则用触轨价(理想化)
+        fill_price = arr_close[i] if cfg.fill_at_close else None
+
         if touched_upper and touched_lower:
             # Both touched in same bar (wide bar) — skip, too volatile
             pass
         elif touched_upper:
             # Price touched upper BB → go short
+            exec_price = fill_price if fill_price is not None else arr_upper[i]
             if position == 1:
-                # Close long at upper BB price
-                close_position(arr_upper[i], i)
+                close_position(exec_price, i)
             if position == 0:
-                # Open short
-                open_position("short", arr_upper[i], i)
+                open_position("short", exec_price, i)
             elif position == -1 and cfg.pyramid_enabled:
-                # Already short → add to short (pyramid)
                 can_add = cfg.pyramid_max <= 0 or pyramid_count < cfg.pyramid_max
                 if can_add:
-                    open_position("short", arr_upper[i], i, is_add=True)
+                    open_position("short", exec_price, i, is_add=True)
         elif touched_lower:
             # Price touched lower BB → go long
+            exec_price = fill_price if fill_price is not None else arr_lower[i]
             if position == -1:
-                # Close short at lower BB price
-                close_position(arr_lower[i], i)
+                close_position(exec_price, i)
             if position == 0:
-                # Open long
-                open_position("long", arr_lower[i], i)
+                open_position("long", exec_price, i)
             elif position == 1 and cfg.pyramid_enabled:
-                # Already long → add to long (pyramid)
                 can_add = cfg.pyramid_max <= 0 or pyramid_count < cfg.pyramid_max
                 if can_add:
-                    open_position("long", arr_lower[i], i, is_add=True)
+                    open_position("long", exec_price, i, is_add=True)
 
         # Record equity
         out_equity[i] = balance + unrealised(arr_close[i])

strategy/data_loader.py

@@ -18,20 +18,25 @@ PERIOD_MAP = {
 }
 
 
-def load_klines(period: str, start_date: str, end_date: str) -> pd.DataFrame:
+def load_klines(period: str, start_date: str, end_date: str, tz: str | None = None) -> pd.DataFrame:
     """
     加载指定周期、指定日期范围的K线数据
     :param period: '1m','3m','5m','15m','30m','1h'
     :param start_date: 'YYYY-MM-DD'
     :param end_date: 'YYYY-MM-DD' (不包含该日)
+    :param tz: 日期解释的时区，如 'Asia/Shanghai' 表示按北京时间；None 则用本地时区
     :return: DataFrame with columns: datetime, open, high, low, close
     """
     table = PERIOD_MAP.get(period)
     if not table:
         raise ValueError(f"不支持的周期: {period}, 可选: {list(PERIOD_MAP.keys())}")
 
-    start_ts = int(pd.Timestamp(start_date).timestamp() * 1000)
-    end_ts = int(pd.Timestamp(end_date).timestamp() * 1000)
+    if tz:
+        start_ts = int(pd.Timestamp(start_date, tz=tz).timestamp() * 1000)
+        end_ts = int(pd.Timestamp(end_date, tz=tz).timestamp() * 1000)
+    else:
+        start_ts = int(pd.Timestamp(start_date).timestamp() * 1000)
+        end_ts = int(pd.Timestamp(end_date).timestamp() * 1000)
 
     db = SqliteDatabase(str(DB_PATH))
     db.connect()

strategy/results/bb_202602_trade_detail.csv

@@ -0,0 +1,315 @@
+序号,方向,开仓时间,平仓时间,开仓价,平仓价,保证金,杠杆,数量,毛盈亏,手续费,净盈亏
+1,做多,2026-02-01 00:45:00,2026-02-01 04:20:00,2503.98,2377.2,2.0,50,0.0399,-5.06,0.05,-5.11
+2,做空,2026-02-01 04:20:00,2026-02-01 04:35:00,2377.2,2360.24,1.95,50,0.041,0.7,0.05,0.65
+3,做多,2026-02-01 04:35:00,2026-02-01 05:00:00,2360.24,2373.42,1.95,50,0.0414,0.55,0.05,0.5
+4,做空,2026-02-01 05:00:00,2026-02-01 09:05:00,2373.42,2433.28,1.96,50,0.0413,-2.47,0.05,-2.52
+5,做多,2026-02-01 09:05:00,2026-02-01 12:10:00,2433.28,2451.12,1.94,50,0.0398,0.71,0.05,0.66
+6,做空,2026-02-01 12:10:00,2026-02-01 13:00:00,2451.12,2439.68,1.94,50,0.0396,0.45,0.05,0.4
+7,做多,2026-02-01 13:00:00,2026-02-01 15:40:00,2439.68,2430.01,1.95,50,0.0399,-0.39,0.05,-0.43
+8,做空,2026-02-01 15:40:00,2026-02-01 18:30:00,2430.01,2406.59,1.94,50,0.0399,0.94,0.05,0.89
+9,做多,2026-02-01 18:30:00,2026-02-01 19:35:00,2406.59,2404.44,1.95,50,0.0405,-0.09,0.05,-0.14
+10,做空,2026-02-01 19:35:00,2026-02-01 20:20:00,2404.44,2387.44,1.95,50,0.0405,0.69,0.05,0.64
+11,做多,2026-02-01 20:20:00,2026-02-01 21:00:00,2387.44,2402.27,1.95,50,0.0409,0.61,0.05,0.56
+12,做空,2026-02-01 21:00:00,2026-02-01 21:40:00,2402.27,2392.0,1.96,50,0.0408,0.42,0.05,0.37
+13,做多,2026-02-01 21:40:00,2026-02-02 00:25:00,2392.0,2318.96,1.96,50,0.041,-3.0,0.05,-3.04
+14,做空,2026-02-02 00:25:00,2026-02-02 03:45:00,2318.96,2313.79,1.93,50,0.0416,0.22,0.05,0.17
+15,做多,2026-02-02 03:45:00,2026-02-02 04:35:00,2313.79,2342.69,1.93,50,0.0418,1.21,0.05,1.16
+16,做空,2026-02-02 04:35:00,2026-02-02 05:55:00,2342.69,2289.17,1.94,50,0.0415,2.22,0.05,2.17
+17,做多,2026-02-02 05:55:00,2026-02-02 06:10:00,2289.17,2323.39,1.96,50,0.0429,1.47,0.05,1.42
+18,做空,2026-02-02 06:10:00,2026-02-02 07:05:00,2323.39,2235.28,1.98,50,0.0426,3.75,0.05,3.7
+19,做多,2026-02-02 07:05:00,2026-02-02 08:15:00,2235.28,2307.06,2.01,50,0.0451,3.23,0.05,3.18
+20,做空,2026-02-02 08:15:00,2026-02-02 09:00:00,2307.06,2302.75,2.06,50,0.0446,0.19,0.05,0.14
+21,做多,2026-02-02 09:00:00,2026-02-02 14:15:00,2302.75,2211.45,2.06,50,0.0447,-4.08,0.05,-4.13
+22,做空,2026-02-02 14:15:00,2026-02-02 14:35:00,2211.45,2166.31,2.02,50,0.0456,2.06,0.05,2.01
+23,做多,2026-02-02 14:35:00,2026-02-02 14:40:00,2166.31,2219.94,2.04,50,0.047,2.52,0.05,2.47
+24,做空,2026-02-02 14:40:00,2026-02-02 17:15:00,2219.94,2250.82,2.06,50,0.0464,-1.43,0.05,-1.49
+25,做多,2026-02-02 17:15:00,2026-02-02 17:25:00,2250.82,2277.79,2.05,50,0.0455,1.23,0.05,1.17
+26,做空,2026-02-02 17:25:00,2026-02-02 22:10:00,2277.79,2305.44,2.06,50,0.0452,-1.25,0.05,-1.3
+27,做多,2026-02-02 22:10:00,2026-02-02 22:35:00,2305.44,2350.92,2.04,50,0.0443,2.02,0.05,1.96
+28,做空,2026-02-02 22:35:00,2026-02-03 00:50:00,2350.92,2357.15,2.06,50,0.0439,-0.27,0.05,-0.33
+29,做多,2026-02-03 00:50:00,2026-02-03 09:00:00,2357.15,2349.37,2.06,50,0.0437,-0.34,0.05,-0.39
+30,做空,2026-02-03 09:00:00,2026-02-03 10:10:00,2349.37,2327.51,2.06,50,0.0439,0.96,0.05,0.91
+31,做多,2026-02-03 10:10:00,2026-02-03 15:10:00,2327.51,2322.01,2.07,50,0.0445,-0.24,0.05,-0.3
+32,做空,2026-02-03 15:10:00,2026-02-03 16:10:00,2322.01,2311.05,2.07,50,0.0446,0.49,0.05,0.44
+33,做多,2026-02-03 16:10:00,2026-02-03 20:10:00,2311.05,2290.92,2.07,50,0.0449,-0.9,0.05,-0.95
+34,做空,2026-02-03 20:10:00,2026-02-03 22:15:00,2290.92,2299.99,2.06,50,0.045,-0.41,0.05,-0.46
+35,做多,2026-02-03 22:15:00,2026-02-03 23:25:00,2299.99,2292.96,2.06,50,0.0447,-0.31,0.05,-0.37
+36,做空,2026-02-03 23:25:00,2026-02-04 00:15:00,2292.96,2265.27,2.05,50,0.0448,1.24,0.05,1.19
+37,做多,2026-02-04 00:15:00,2026-02-04 03:10:00,2265.27,2178.1,2.07,50,0.0456,-3.97,0.05,-4.02
+38,做空,2026-02-04 03:10:00,2026-02-04 06:05:00,2178.1,2259.5,2.02,50,0.0465,-3.78,0.05,-3.84
+39,做多,2026-02-04 06:05:00,2026-02-04 09:00:00,2259.5,2264.51,1.99,50,0.0439,0.22,0.05,0.17
+40,做空,2026-02-04 09:00:00,2026-02-04 10:30:00,2264.51,2254.5,2.0,50,0.0441,0.44,0.05,0.39
+41,做多,2026-02-04 10:30:00,2026-02-04 11:10:00,2254.5,2275.54,2.0,50,0.0443,0.93,0.05,0.88
+42,做空,2026-02-04 11:10:00,2026-02-04 12:25:00,2275.54,2274.79,2.01,50,0.0441,0.03,0.05,-0.02
+43,做多,2026-02-04 12:25:00,2026-02-04 20:20:00,2274.79,2253.17,2.01,50,0.0441,-0.95,0.05,-1.0
+44,做空,2026-02-04 20:20:00,2026-02-04 20:25:00,2253.17,2234.15,2.0,50,0.0443,0.84,0.05,0.79
+45,做多,2026-02-04 20:25:00,2026-02-05 01:00:00,2234.15,2141.81,2.0,50,0.0449,-4.14,0.05,-4.19
+46,做空,2026-02-05 01:00:00,2026-02-05 01:35:00,2141.81,2100.23,1.96,50,0.0458,1.9,0.05,1.86
+47,做多,2026-02-05 01:35:00,2026-02-05 02:25:00,2100.23,2122.35,1.98,50,0.0471,1.04,0.05,0.99
+48,做空,2026-02-05 02:25:00,2026-02-05 03:20:00,2122.35,2138.64,1.99,50,0.0469,-0.76,0.05,-0.81
+49,做多,2026-02-05 03:20:00,2026-02-05 03:45:00,2138.64,2159.36,1.98,50,0.0463,0.96,0.05,0.91
+50,做空,2026-02-05 03:45:00,2026-02-05 05:05:00,2159.36,2158.46,1.99,50,0.0461,0.04,0.05,-0.01
+51,做多,2026-02-05 05:05:00,2026-02-05 10:35:00,2158.46,2153.58,1.99,50,0.0461,-0.22,0.05,-0.27
+52,做空,2026-02-05 10:35:00,2026-02-05 11:15:00,2153.58,2113.19,2.0,50,0.0463,1.87,0.05,1.82
+53,做多,2026-02-05 11:15:00,2026-02-05 12:40:00,2113.19,2121.89,2.01,50,0.0477,0.41,0.05,0.36
+54,做空,2026-02-05 12:40:00,2026-02-05 13:20:00,2121.89,2085.5,2.02,50,0.0475,1.73,0.05,1.68
+55,做多,2026-02-05 13:20:00,2026-02-05 15:00:00,2085.5,2115.39,2.03,50,0.0488,1.46,0.05,1.41
+56,做空,2026-02-05 15:00:00,2026-02-05 15:55:00,2115.39,2089.53,2.05,50,0.0484,1.25,0.05,1.2
+57,做多,2026-02-05 15:55:00,2026-02-05 16:25:00,2089.53,2110.34,2.06,50,0.0493,1.03,0.05,0.97
+58,做空,2026-02-05 16:25:00,2026-02-05 18:55:00,2110.34,2096.48,2.07,50,0.049,0.68,0.05,0.63
+59,做多,2026-02-05 18:55:00,2026-02-05 21:05:00,2096.48,2071.86,2.07,50,0.0495,-1.22,0.05,-1.27
+60,做空,2026-02-05 21:05:00,2026-02-06 01:20:00,2071.86,1987.12,2.06,50,0.0497,4.21,0.05,4.16
+61,做多,2026-02-06 01:20:00,2026-02-06 06:25:00,1987.12,1871.41,2.1,50,0.0529,-6.12,0.05,-6.17
+62,做空,2026-02-06 06:25:00,2026-02-06 08:10:00,1871.41,1766.83,2.04,50,0.0545,5.7,0.05,5.65
+63,做多,2026-02-06 08:10:00,2026-02-06 09:35:00,1766.83,1909.28,2.11,50,0.0596,8.49,0.06,8.43
+64,做空,2026-02-06 09:35:00,2026-02-06 11:50:00,1909.28,1885.62,2.19,50,0.0573,1.36,0.05,1.3
+65,做多,2026-02-06 11:50:00,2026-02-06 13:05:00,1885.62,1911.81,2.2,50,0.0584,1.53,0.06,1.47
+66,做空,2026-02-06 13:05:00,2026-02-06 16:15:00,1911.81,1879.3,2.22,50,0.0579,1.88,0.05,1.83
+67,做多,2026-02-06 16:15:00,2026-02-06 17:10:00,1879.3,1885.97,2.23,50,0.0594,0.4,0.06,0.34
+68,做空,2026-02-06 17:10:00,2026-02-06 19:00:00,1885.97,1924.17,2.24,50,0.0593,-2.26,0.06,-2.32
+69,做多,2026-02-06 19:00:00,2026-02-06 19:15:00,1924.17,1924.74,2.21,50,0.0575,0.03,0.06,-0.02
+70,做空,2026-02-06 19:15:00,2026-02-06 20:05:00,1924.74,1922.87,2.21,50,0.0575,0.11,0.06,0.05
+71,做多,2026-02-06 20:05:00,2026-02-06 21:00:00,1922.87,1932.91,2.21,50,0.0575,0.58,0.06,0.52
+72,做空,2026-02-06 21:00:00,2026-02-06 23:15:00,1932.91,1971.8,2.22,50,0.0573,-2.23,0.06,-2.29
+73,做多,2026-02-06 23:15:00,2026-02-06 23:45:00,1971.8,1990.88,2.19,50,0.0556,1.06,0.06,1.01
+74,做空,2026-02-06 23:45:00,2026-02-07 02:05:00,1990.88,2032.15,2.2,50,0.0553,-2.28,0.06,-2.34
+75,做多,2026-02-07 02:05:00,2026-02-07 04:35:00,2032.15,2073.09,2.18,50,0.0536,2.19,0.06,2.14
+76,做空,2026-02-07 04:35:00,2026-02-07 07:15:00,2073.09,2053.48,2.2,50,0.053,1.04,0.05,0.99
+77,做多,2026-02-07 07:15:00,2026-02-07 11:00:00,2053.48,2064.11,2.21,50,0.0538,0.57,0.06,0.52
+78,做空,2026-02-07 11:00:00,2026-02-07 14:15:00,2064.11,2073.13,2.23,50,0.054,-0.49,0.06,-0.54
+79,做多,2026-02-07 14:15:00,2026-02-07 19:55:00,2073.13,2017.76,2.22,50,0.0536,-2.97,0.05,-3.02
+80,做空,2026-02-07 19:55:00,2026-02-07 21:35:00,2017.76,2027.6,2.19,50,0.0543,-0.53,0.06,-0.59
+81,做多,2026-02-07 21:35:00,2026-02-08 02:15:00,2027.6,2076.87,2.18,50,0.0539,2.65,0.06,2.6
+82,做空,2026-02-08 02:15:00,2026-02-08 06:10:00,2076.87,2099.58,2.21,50,0.0532,-1.21,0.06,-1.26
+83,做多,2026-02-08 06:10:00,2026-02-08 10:20:00,2099.58,2102.05,2.2,50,0.0523,0.13,0.05,0.07
+84,做空,2026-02-08 10:20:00,2026-02-08 12:15:00,2102.05,2074.69,2.2,50,0.0524,1.43,0.05,1.38
+85,做多,2026-02-08 12:15:00,2026-02-08 12:55:00,2074.69,2086.46,2.22,50,0.0534,0.63,0.06,0.57
+86,做空,2026-02-08 12:55:00,2026-02-08 14:05:00,2086.46,2079.62,2.22,50,0.0532,0.36,0.06,0.31
+87,做多,2026-02-08 14:05:00,2026-02-08 16:20:00,2079.62,2096.67,2.22,50,0.0535,0.91,0.06,0.86
+88,做空,2026-02-08 16:20:00,2026-02-08 17:35:00,2096.67,2103.15,2.23,50,0.0532,-0.34,0.06,-0.4
+89,做多,2026-02-08 17:35:00,2026-02-08 18:05:00,2103.15,2107.65,2.23,50,0.053,0.24,0.06,0.18
+90,做空,2026-02-08 18:05:00,2026-02-08 18:20:00,2107.65,2087.85,2.23,50,0.0529,1.05,0.06,0.99
+91,做多,2026-02-08 18:20:00,2026-02-08 19:15:00,2087.85,2110.36,2.24,50,0.0536,1.21,0.06,1.15
+92,做空,2026-02-08 19:15:00,2026-02-08 21:05:00,2110.36,2123.28,2.25,50,0.0533,-0.69,0.06,-0.75
+93,做多,2026-02-08 21:05:00,2026-02-09 02:15:00,2123.28,2094.55,2.24,50,0.0528,-1.52,0.06,-1.57
+94,做空,2026-02-09 02:15:00,2026-02-09 04:45:00,2094.55,2104.6,2.22,50,0.0531,-0.53,0.06,-0.59
+95,做多,2026-02-09 04:45:00,2026-02-09 06:55:00,2104.6,2107.44,2.22,50,0.0527,0.15,0.06,0.09
+96,做空,2026-02-09 06:55:00,2026-02-09 08:25:00,2107.44,2081.4,2.22,50,0.0526,1.37,0.05,1.32
+97,做多,2026-02-09 08:25:00,2026-02-09 09:20:00,2081.4,2098.76,2.24,50,0.0539,0.94,0.06,0.88
+98,做空,2026-02-09 09:20:00,2026-02-09 09:40:00,2098.76,2063.62,2.25,50,0.0537,1.89,0.06,1.83
+99,做多,2026-02-09 09:40:00,2026-02-09 10:35:00,2063.62,2079.96,2.27,50,0.055,0.9,0.06,0.84
+100,做空,2026-02-09 10:35:00,2026-02-09 14:15:00,2079.96,2075.79,2.28,50,0.0548,0.23,0.06,0.17
+101,做多,2026-02-09 14:15:00,2026-02-09 15:10:00,2075.79,2084.33,2.28,50,0.0549,0.47,0.06,0.41
+102,做空,2026-02-09 15:10:00,2026-02-09 15:35:00,2084.33,2067.23,2.28,50,0.0548,0.94,0.06,0.88
+103,做多,2026-02-09 15:35:00,2026-02-09 20:00:00,2067.23,2031.57,2.29,50,0.0554,-1.98,0.06,-2.03
+104,做空,2026-02-09 20:00:00,2026-02-10 02:20:00,2031.57,2115.84,2.27,50,0.0559,-4.71,0.06,-4.77
+105,做多,2026-02-10 02:20:00,2026-02-10 03:30:00,2115.84,2131.85,2.22,50,0.0525,0.84,0.06,0.78
+106,做空,2026-02-10 03:30:00,2026-02-10 04:00:00,2131.85,2130.8,2.23,50,0.0523,0.05,0.06,-0.0
+107,做多,2026-02-10 04:00:00,2026-02-10 04:05:00,2130.8,2135.34,2.23,50,0.0523,0.24,0.06,0.18
+108,做空,2026-02-10 04:05:00,2026-02-10 04:15:00,2135.34,2122.59,2.23,50,0.0522,0.67,0.06,0.61
+109,做多,2026-02-10 04:15:00,2026-02-10 16:20:00,2122.59,2011.91,2.24,50,0.0527,-5.83,0.05,-5.88
+110,做空,2026-02-10 16:20:00,2026-02-10 17:50:00,2011.91,2015.22,2.19,50,0.0544,-0.18,0.05,-0.23
+111,做多,2026-02-10 17:50:00,2026-02-10 19:30:00,2015.22,2019.66,2.19,50,0.0543,0.24,0.05,0.19
+112,做空,2026-02-10 19:30:00,2026-02-10 19:40:00,2019.66,2007.94,2.19,50,0.0542,0.63,0.05,0.58
+113,做多,2026-02-10 19:40:00,2026-02-10 21:15:00,2007.94,2012.02,2.19,50,0.0546,0.22,0.05,0.17
+114,做空,2026-02-10 21:15:00,2026-02-10 22:35:00,2012.02,2012.47,2.19,50,0.0545,-0.02,0.05,-0.08
+115,做多,2026-02-10 22:35:00,2026-02-11 00:10:00,2012.47,2032.87,2.19,50,0.0545,1.11,0.06,1.06
+116,做空,2026-02-11 00:10:00,2026-02-11 02:20:00,2032.87,2013.69,2.2,50,0.0542,1.04,0.05,0.98
+117,做多,2026-02-11 02:20:00,2026-02-11 03:30:00,2013.69,2013.39,2.21,50,0.0549,-0.02,0.06,-0.07
+118,做空,2026-02-11 03:30:00,2026-02-11 05:30:00,2013.39,2001.89,2.21,50,0.0549,0.63,0.05,0.58
+119,做多,2026-02-11 05:30:00,2026-02-11 07:35:00,2001.89,2018.01,2.22,50,0.0554,0.89,0.06,0.84
+120,做空,2026-02-11 07:35:00,2026-02-11 09:20:00,2018.01,2018.06,2.22,50,0.0551,-0.0,0.06,-0.06
+121,做多,2026-02-11 09:20:00,2026-02-11 10:20:00,2018.06,2027.05,2.23,50,0.0553,0.5,0.06,0.44
+122,做空,2026-02-11 10:20:00,2026-02-11 10:45:00,2027.05,2014.32,2.24,50,0.0552,0.7,0.06,0.65
+123,做多,2026-02-11 10:45:00,2026-02-11 15:35:00,2014.32,1951.85,2.24,50,0.0557,-3.48,0.05,-3.53
+124,做空,2026-02-11 15:35:00,2026-02-11 16:05:00,1951.85,1939.79,2.21,50,0.0566,0.68,0.05,0.63
+125,做多,2026-02-11 16:05:00,2026-02-11 17:00:00,1939.79,1949.26,2.21,50,0.057,0.54,0.06,0.48
+126,做空,2026-02-11 17:00:00,2026-02-11 17:45:00,1949.26,1944.0,2.22,50,0.0569,0.3,0.06,0.24
+127,做多,2026-02-11 17:45:00,2026-02-11 20:05:00,1944.0,1961.67,2.22,50,0.0571,1.01,0.06,0.95
+128,做空,2026-02-11 20:05:00,2026-02-11 21:25:00,1961.67,1948.28,2.23,50,0.0568,0.76,0.06,0.71
+129,做多,2026-02-11 21:25:00,2026-02-11 21:30:00,1948.28,1963.0,2.23,50,0.0574,0.84,0.06,0.79
+130,做空,2026-02-11 21:30:00,2026-02-12 03:30:00,1963.0,1943.01,2.24,50,0.0571,1.14,0.06,1.09
+131,做多,2026-02-12 03:30:00,2026-02-12 03:45:00,1943.01,1952.12,2.25,50,0.058,0.53,0.06,0.47
+132,做空,2026-02-12 03:45:00,2026-02-12 04:25:00,1952.12,1941.02,2.26,50,0.0578,0.64,0.06,0.59
+133,做多,2026-02-12 04:25:00,2026-02-12 05:20:00,1941.02,1968.22,2.26,50,0.0583,1.58,0.06,1.53
+134,做空,2026-02-12 05:20:00,2026-02-12 06:10:00,1968.22,1960.92,2.28,50,0.0578,0.42,0.06,0.37
+135,做多,2026-02-12 06:10:00,2026-02-12 08:05:00,1960.92,1951.09,2.28,50,0.0581,-0.57,0.06,-0.63
+136,做空,2026-02-12 08:05:00,2026-02-12 12:30:00,1951.09,1967.55,2.29,50,0.0586,-0.97,0.06,-1.02
+137,做多,2026-02-12 12:30:00,2026-02-12 14:10:00,1967.55,1970.2,2.28,50,0.0579,0.15,0.06,0.1
+138,做空,2026-02-12 14:10:00,2026-02-12 16:25:00,1970.2,1958.73,2.28,50,0.0578,0.66,0.06,0.61
+139,做多,2026-02-12 16:25:00,2026-02-12 17:10:00,1958.73,1968.27,2.28,50,0.0583,0.56,0.06,0.5
+140,做空,2026-02-12 17:10:00,2026-02-12 20:50:00,1968.27,1976.76,2.29,50,0.0581,-0.49,0.06,-0.55
+141,做多,2026-02-12 20:50:00,2026-02-12 21:30:00,1976.76,1985.8,2.28,50,0.0577,0.52,0.06,0.46
+142,做空,2026-02-12 21:30:00,2026-02-12 22:45:00,1985.8,1978.53,2.29,50,0.0575,0.42,0.06,0.36
+143,做多,2026-02-12 22:45:00,2026-02-13 01:35:00,1978.53,1920.11,2.29,50,0.0578,-3.38,0.06,-3.43
+144,做空,2026-02-13 01:35:00,2026-02-13 04:10:00,1920.11,1920.22,2.25,50,0.0587,-0.01,0.06,-0.06
+145,做多,2026-02-13 04:10:00,2026-02-13 06:30:00,1920.22,1927.46,2.25,50,0.0587,0.42,0.06,0.37
+146,做空,2026-02-13 06:30:00,2026-02-13 08:15:00,1927.46,1940.1,2.26,50,0.0585,-0.74,0.06,-0.8
+147,做多,2026-02-13 08:15:00,2026-02-13 09:05:00,1940.1,1941.5,2.26,50,0.0582,0.08,0.06,0.02
+148,做空,2026-02-13 09:05:00,2026-02-13 10:20:00,1941.5,1946.1,2.26,50,0.0582,-0.27,0.06,-0.32
+149,做多,2026-02-13 10:20:00,2026-02-13 10:50:00,1946.1,1947.9,2.25,50,0.0579,0.1,0.06,0.05
+150,做空,2026-02-13 10:50:00,2026-02-13 12:10:00,1947.9,1950.84,2.25,50,0.0579,-0.17,0.06,-0.23
+151,做多,2026-02-13 12:10:00,2026-02-13 12:25:00,1950.84,1949.6,2.25,50,0.0577,-0.07,0.06,-0.13
+152,做空,2026-02-13 12:25:00,2026-02-13 12:30:00,1949.6,1950.08,2.25,50,0.0577,-0.03,0.06,-0.08
+153,做多,2026-02-13 12:30:00,2026-02-13 16:20:00,1950.08,1939.99,2.25,50,0.0576,-0.58,0.06,-0.64
+154,做空,2026-02-13 16:20:00,2026-02-13 19:05:00,1939.99,1955.6,2.24,50,0.0578,-0.9,0.06,-0.96
+155,做多,2026-02-13 19:05:00,2026-02-13 20:25:00,1955.6,1961.63,2.23,50,0.057,0.34,0.06,0.29
+156,做空,2026-02-13 20:25:00,2026-02-13 21:05:00,1961.63,1957.39,2.23,50,0.0569,0.24,0.06,0.19
+157,做多,2026-02-13 21:05:00,2026-02-13 21:20:00,1957.39,1967.19,2.23,50,0.0571,0.56,0.06,0.5
+158,做空,2026-02-13 21:20:00,2026-02-14 02:00:00,1967.19,2056.73,2.24,50,0.0569,-5.1,0.06,-5.15
+159,做多,2026-02-14 02:00:00,2026-02-14 02:35:00,2056.73,2061.34,2.19,50,0.0532,0.25,0.05,0.19
+160,做空,2026-02-14 02:35:00,2026-02-14 04:15:00,2061.34,2049.81,2.19,50,0.0531,0.61,0.05,0.56
+161,做多,2026-02-14 04:15:00,2026-02-14 05:00:00,2049.81,2054.62,2.19,50,0.0535,0.26,0.05,0.2
+162,做空,2026-02-14 05:00:00,2026-02-14 07:35:00,2054.62,2047.52,2.19,50,0.0534,0.38,0.05,0.32
+163,做多,2026-02-14 07:35:00,2026-02-14 09:50:00,2047.52,2053.35,2.2,50,0.0537,0.31,0.06,0.26
+164,做空,2026-02-14 09:50:00,2026-02-14 09:55:00,2053.35,2053.37,2.22,50,0.054,-0.0,0.06,-0.06
+165,做多,2026-02-14 09:55:00,2026-02-14 11:25:00,2053.37,2050.56,2.22,50,0.0539,-0.15,0.06,-0.21
+166,做空,2026-02-14 11:25:00,2026-02-14 13:00:00,2050.56,2052.1,2.21,50,0.054,-0.08,0.06,-0.14
+167,做多,2026-02-14 13:00:00,2026-02-14 15:30:00,2052.1,2052.31,2.21,50,0.0539,0.01,0.06,-0.04
+168,做空,2026-02-14 15:30:00,2026-02-14 15:35:00,2052.31,2050.7,2.21,50,0.0538,0.09,0.06,0.03
+169,做多,2026-02-14 15:35:00,2026-02-14 15:50:00,2050.7,2057.65,2.21,50,0.0539,0.37,0.06,0.32
+170,做空,2026-02-14 15:50:00,2026-02-14 20:15:00,2057.65,2094.01,2.21,50,0.0538,-1.95,0.06,-2.01
+171,做多,2026-02-14 20:15:00,2026-02-14 22:20:00,2094.01,2069.5,2.19,50,0.0523,-1.28,0.05,-1.34
+172,做空,2026-02-14 22:20:00,2026-02-15 00:00:00,2069.5,2086.28,2.18,50,0.0526,-0.88,0.05,-0.94
+173,做多,2026-02-15 00:00:00,2026-02-15 02:20:00,2086.28,2082.08,2.17,50,0.052,-0.22,0.05,-0.27
+174,做空,2026-02-15 02:20:00,2026-02-15 03:15:00,2082.08,2084.26,2.16,50,0.052,-0.11,0.05,-0.17
+175,做多,2026-02-15 03:15:00,2026-02-15 03:30:00,2084.26,2085.58,2.16,50,0.0519,0.07,0.05,0.01
+176,做空,2026-02-15 03:30:00,2026-02-15 07:15:00,2085.58,2087.12,2.16,50,0.0518,-0.08,0.05,-0.13
+177,做多,2026-02-15 07:15:00,2026-02-15 10:05:00,2087.12,2058.92,2.16,50,0.0517,-1.46,0.05,-1.51
+178,做空,2026-02-15 10:05:00,2026-02-15 10:20:00,2058.92,2054.96,2.16,50,0.0524,0.21,0.05,0.15
+179,做多,2026-02-15 10:20:00,2026-02-15 12:05:00,2054.96,2072.91,2.16,50,0.0525,0.94,0.05,0.89
+180,做空,2026-02-15 12:05:00,2026-02-15 14:00:00,2072.91,2086.85,2.17,50,0.0523,-0.73,0.05,-0.78
+181,做多,2026-02-15 14:00:00,2026-02-15 14:35:00,2086.85,2090.16,2.16,50,0.0517,0.17,0.05,0.12
+182,做空,2026-02-15 14:35:00,2026-02-15 16:25:00,2090.16,2075.54,2.16,50,0.0517,0.76,0.05,0.7
+183,做多,2026-02-15 16:25:00,2026-02-15 20:20:00,2075.54,2062.81,2.17,50,0.0522,-0.66,0.05,-0.72
+184,做空,2026-02-15 20:20:00,2026-02-15 20:45:00,2062.81,2046.45,2.16,50,0.0523,0.86,0.05,0.8
+185,做多,2026-02-15 20:45:00,2026-02-15 22:30:00,2046.45,1999.25,2.17,50,0.0529,-2.5,0.05,-2.55
+186,做空,2026-02-15 22:30:00,2026-02-16 00:05:00,1999.25,1999.62,2.14,50,0.0535,-0.02,0.05,-0.07
+187,做多,2026-02-16 00:05:00,2026-02-16 05:30:00,1999.62,1959.09,2.14,50,0.0535,-2.17,0.05,-2.22
+188,做空,2026-02-16 05:30:00,2026-02-16 07:00:00,1959.09,1956.8,2.12,50,0.054,0.12,0.05,0.07
+189,做多,2026-02-16 07:00:00,2026-02-16 08:05:00,1956.8,1973.71,2.12,50,0.0541,0.91,0.05,0.86
+190,做空,2026-02-16 08:05:00,2026-02-16 10:20:00,1973.71,1958.9,2.14,50,0.0541,0.8,0.05,0.75
+191,做多,2026-02-16 10:20:00,2026-02-16 12:00:00,1958.9,1963.67,2.14,50,0.0547,0.26,0.05,0.21
+192,做空,2026-02-16 12:00:00,2026-02-16 19:05:00,1963.67,1973.75,2.14,50,0.0546,-0.55,0.05,-0.6
+193,做多,2026-02-16 19:05:00,2026-02-16 20:25:00,1973.75,1991.31,2.14,50,0.0542,0.95,0.05,0.9
+194,做空,2026-02-16 20:25:00,2026-02-16 21:25:00,1991.31,1976.1,2.15,50,0.0539,0.82,0.05,0.77
+195,做多,2026-02-16 21:25:00,2026-02-16 22:50:00,1976.1,1969.72,2.15,50,0.0545,-0.35,0.05,-0.4
+196,做空,2026-02-16 22:50:00,2026-02-16 23:30:00,1969.72,1940.59,2.15,50,0.0545,1.59,0.05,1.54
+197,做多,2026-02-16 23:30:00,2026-02-17 01:30:00,1940.59,1983.81,2.16,50,0.0557,2.41,0.06,2.35
+198,做空,2026-02-17 01:30:00,2026-02-17 02:35:00,1983.81,1974.99,2.19,50,0.0551,0.49,0.05,0.43
+199,做多,2026-02-17 02:35:00,2026-02-17 03:35:00,1974.99,1977.15,2.19,50,0.0555,0.12,0.05,0.06
+200,做空,2026-02-17 03:35:00,2026-02-17 06:45:00,1977.15,1991.2,2.19,50,0.0554,-0.78,0.06,-0.83
+201,做多,2026-02-17 06:45:00,2026-02-17 07:05:00,1991.2,1993.01,2.18,50,0.0548,0.1,0.05,0.04
+202,做空,2026-02-17 07:05:00,2026-02-17 10:00:00,1993.01,1986.61,2.18,50,0.0547,0.35,0.05,0.3
+203,做多,2026-02-17 10:00:00,2026-02-17 12:20:00,1986.61,1996.22,2.2,50,0.0553,0.53,0.06,0.48
+204,做空,2026-02-17 12:20:00,2026-02-17 13:15:00,1996.22,1975.63,2.2,50,0.0551,1.14,0.05,1.08
+205,做多,2026-02-17 13:15:00,2026-02-17 14:25:00,1975.63,1981.79,2.21,50,0.056,0.34,0.06,0.29
+206,做空,2026-02-17 14:25:00,2026-02-17 15:05:00,1981.79,1975.75,2.21,50,0.0558,0.34,0.06,0.28
+207,做多,2026-02-17 15:05:00,2026-02-17 18:00:00,1975.75,1974.07,2.22,50,0.0561,-0.09,0.06,-0.15
+208,做空,2026-02-17 18:00:00,2026-02-17 18:15:00,1974.07,1963.99,2.21,50,0.0561,0.57,0.06,0.51
+209,做多,2026-02-17 18:15:00,2026-02-17 19:00:00,1963.99,1966.66,2.22,50,0.0565,0.15,0.06,0.1
+210,做空,2026-02-17 19:00:00,2026-02-17 19:45:00,1966.66,1966.75,2.22,50,0.0564,-0.01,0.06,-0.06
+211,做多,2026-02-17 19:45:00,2026-02-17 20:05:00,1966.75,1973.21,2.22,50,0.0564,0.36,0.06,0.31
+212,做空,2026-02-17 20:05:00,2026-02-17 20:50:00,1973.21,1970.9,2.22,50,0.0563,0.13,0.06,0.07
+213,做多,2026-02-17 20:50:00,2026-02-17 21:10:00,1970.9,1979.05,2.22,50,0.0563,0.46,0.06,0.4
+214,做空,2026-02-17 21:10:00,2026-02-17 22:35:00,1979.05,1978.92,2.22,50,0.0562,0.01,0.06,-0.05
+215,做多,2026-02-17 22:35:00,2026-02-18 00:00:00,1978.92,1986.74,2.22,50,0.0562,0.44,0.06,0.38
+216,做空,2026-02-18 00:00:00,2026-02-18 01:10:00,1986.74,1964.67,2.23,50,0.056,1.24,0.06,1.18
+217,做多,2026-02-18 01:10:00,2026-02-18 02:20:00,1964.67,1986.33,2.24,50,0.0569,1.23,0.06,1.18
+218,做空,2026-02-18 02:20:00,2026-02-18 04:30:00,1986.33,1993.32,2.25,50,0.0566,-0.4,0.06,-0.45
+219,做多,2026-02-18 04:30:00,2026-02-18 04:40:00,1993.32,1997.94,2.24,50,0.0563,0.26,0.06,0.2
+220,做空,2026-02-18 04:40:00,2026-02-18 06:50:00,1997.94,1993.94,2.24,50,0.0562,0.22,0.06,0.17
+221,做多,2026-02-18 06:50:00,2026-02-18 11:25:00,1993.94,1993.01,2.25,50,0.0563,-0.05,0.06,-0.11
+222,做空,2026-02-18 11:25:00,2026-02-18 12:35:00,1993.01,1994.19,2.26,50,0.0568,-0.07,0.06,-0.12
+223,做多,2026-02-18 12:35:00,2026-02-18 14:20:00,1994.19,2001.76,2.26,50,0.0567,0.43,0.06,0.37
+224,做空,2026-02-18 14:20:00,2026-02-18 17:50:00,2001.76,2017.24,2.26,50,0.0566,-0.88,0.06,-0.93
+225,做多,2026-02-18 17:50:00,2026-02-18 22:30:00,2017.24,1967.63,2.25,50,0.0559,-2.77,0.05,-2.83
+226,做空,2026-02-18 22:30:00,2026-02-18 22:45:00,1967.63,1955.53,2.23,50,0.0566,0.68,0.06,0.63
+227,做多,2026-02-18 22:45:00,2026-02-18 23:05:00,1955.53,1983.75,2.23,50,0.0571,1.61,0.06,1.55
+228,做空,2026-02-18 23:05:00,2026-02-19 02:15:00,1983.75,1963.63,2.25,50,0.0566,1.14,0.06,1.08
+229,做多,2026-02-19 02:15:00,2026-02-19 04:30:00,1963.63,1947.9,2.26,50,0.0575,-0.9,0.06,-0.96
+230,做空,2026-02-19 04:30:00,2026-02-19 07:15:00,1947.9,1946.27,2.25,50,0.0577,0.09,0.06,0.04
+231,做多,2026-02-19 07:15:00,2026-02-19 07:25:00,1946.27,1947.6,2.25,50,0.0577,0.08,0.06,0.02
+232,做空,2026-02-19 07:25:00,2026-02-19 08:25:00,1947.6,1952.44,2.25,50,0.0577,-0.28,0.06,-0.34
+233,做多,2026-02-19 08:25:00,2026-02-19 09:10:00,1952.44,1969.01,2.25,50,0.0577,0.96,0.06,0.9
+234,做空,2026-02-19 09:10:00,2026-02-19 12:45:00,1969.01,1971.59,2.26,50,0.0574,-0.15,0.06,-0.2
+235,做多,2026-02-19 12:45:00,2026-02-19 14:05:00,1971.59,1971.53,2.26,50,0.0573,-0.0,0.06,-0.06
+236,做空,2026-02-19 14:05:00,2026-02-19 15:40:00,1971.53,1981.57,2.26,50,0.0573,-0.57,0.06,-0.63
+237,做多,2026-02-19 15:40:00,2026-02-19 17:20:00,1981.57,1977.7,2.25,50,0.0568,-0.22,0.06,-0.28
+238,做空,2026-02-19 17:20:00,2026-02-19 17:45:00,1977.7,1961.93,2.25,50,0.0568,0.9,0.06,0.84
+239,做多,2026-02-19 17:45:00,2026-02-19 22:50:00,1961.93,1939.99,2.26,50,0.0575,-1.26,0.06,-1.32
+240,做空,2026-02-19 22:50:00,2026-02-20 00:05:00,1939.99,1915.04,2.24,50,0.0578,1.44,0.06,1.39
+241,做多,2026-02-20 00:05:00,2026-02-20 01:15:00,1915.04,1941.03,2.26,50,0.0589,1.53,0.06,1.47
+242,做空,2026-02-20 01:15:00,2026-02-20 03:25:00,1941.03,1935.82,2.27,50,0.0585,0.3,0.06,0.25
+243,做多,2026-02-20 03:25:00,2026-02-20 04:45:00,1935.82,1947.16,2.27,50,0.0587,0.67,0.06,0.61
+244,做空,2026-02-20 04:45:00,2026-02-20 05:55:00,1947.16,1947.67,2.28,50,0.0585,-0.03,0.06,-0.09
+245,做多,2026-02-20 05:55:00,2026-02-20 07:00:00,1947.67,1943.15,2.28,50,0.0584,-0.26,0.06,-0.32
+246,做空,2026-02-20 07:00:00,2026-02-20 12:00:00,1943.15,1948.02,2.27,50,0.0585,-0.28,0.06,-0.34
+247,做多,2026-02-20 12:00:00,2026-02-20 13:30:00,1948.02,1960.28,2.28,50,0.0586,0.72,0.06,0.66
+248,做空,2026-02-20 13:30:00,2026-02-20 14:30:00,1960.28,1954.43,2.29,50,0.0584,0.34,0.06,0.28
+249,做多,2026-02-20 14:30:00,2026-02-20 15:15:00,1954.43,1959.51,2.29,50,0.0586,0.3,0.06,0.24
+250,做空,2026-02-20 15:15:00,2026-02-20 18:40:00,1959.51,1961.18,2.29,50,0.0585,-0.1,0.06,-0.16
+251,做多,2026-02-20 18:40:00,2026-02-20 20:50:00,1961.18,1946.59,2.29,50,0.0584,-0.85,0.06,-0.91
+252,做空,2026-02-20 20:50:00,2026-02-20 21:00:00,1946.59,1943.99,2.28,50,0.0586,0.15,0.06,0.1
+253,做多,2026-02-20 21:00:00,2026-02-20 22:30:00,1943.99,1944.3,2.28,50,0.0587,0.02,0.06,-0.04
+254,做空,2026-02-20 22:30:00,2026-02-21 06:10:00,1944.3,1964.49,2.28,50,0.0586,-1.18,0.06,-1.24
+255,做多,2026-02-21 06:10:00,2026-02-21 07:05:00,1964.49,1968.92,2.27,50,0.0577,0.26,0.06,0.2
+256,做空,2026-02-21 07:05:00,2026-02-21 08:45:00,1968.92,1963.92,2.27,50,0.0576,0.29,0.06,0.23
+257,做多,2026-02-21 08:45:00,2026-02-21 12:25:00,1963.92,1959.01,2.28,50,0.058,-0.29,0.06,-0.34
+258,做空,2026-02-21 12:25:00,2026-02-21 20:25:00,1959.01,1969.99,2.28,50,0.0581,-0.64,0.06,-0.7
+259,做多,2026-02-21 20:25:00,2026-02-21 22:05:00,1969.99,1981.03,2.27,50,0.0576,0.64,0.06,0.58
+260,做空,2026-02-21 22:05:00,2026-02-21 23:30:00,1981.03,1988.19,2.27,50,0.0574,-0.41,0.06,-0.47
+261,做多,2026-02-21 23:30:00,2026-02-21 23:40:00,1988.19,1989.55,2.27,50,0.057,0.08,0.06,0.02
+262,做空,2026-02-21 23:40:00,2026-02-22 00:00:00,1989.55,1979.46,2.27,50,0.057,0.58,0.06,0.52
+263,做多,2026-02-22 00:00:00,2026-02-22 01:40:00,1979.46,1988.74,2.27,50,0.0574,0.53,0.06,0.48
+264,做空,2026-02-22 01:40:00,2026-02-22 03:50:00,1988.74,1987.85,2.28,50,0.0572,0.05,0.06,-0.01
+265,做多,2026-02-22 03:50:00,2026-02-22 09:00:00,1987.85,1973.58,2.28,50,0.0573,-0.82,0.06,-0.87
+266,做空,2026-02-22 09:00:00,2026-02-22 11:15:00,1973.58,1968.26,2.28,50,0.0577,0.31,0.06,0.25
+267,做多,2026-02-22 11:15:00,2026-02-22 15:25:00,1968.26,1975.34,2.28,50,0.0579,0.41,0.06,0.35
+268,做空,2026-02-22 15:25:00,2026-02-22 16:20:00,1975.34,1973.39,2.28,50,0.0577,0.11,0.06,0.06
+269,做多,2026-02-22 16:20:00,2026-02-22 17:15:00,1973.39,1973.0,2.28,50,0.0578,-0.02,0.06,-0.08
+270,做空,2026-02-22 17:15:00,2026-02-22 20:00:00,1973.0,1976.79,2.28,50,0.0578,-0.22,0.06,-0.28
+271,做多,2026-02-22 20:00:00,2026-02-22 22:30:00,1976.79,1951.75,2.28,50,0.0576,-1.44,0.06,-1.5
+272,做空,2026-02-22 22:30:00,2026-02-23 01:30:00,1951.75,1935.57,2.26,50,0.0579,0.94,0.06,0.88
+273,做多,2026-02-23 01:30:00,2026-02-23 02:15:00,1935.57,1941.0,2.27,50,0.0586,0.32,0.06,0.26
+274,做空,2026-02-23 02:15:00,2026-02-23 02:35:00,1941.0,1940.45,2.27,50,0.0585,0.03,0.06,-0.02
+275,做多,2026-02-23 02:35:00,2026-02-23 02:50:00,1940.45,1942.01,2.27,50,0.0585,0.09,0.06,0.03
+276,做空,2026-02-23 02:50:00,2026-02-23 04:50:00,1942.01,1939.47,2.27,50,0.0584,0.15,0.06,0.09
+277,做多,2026-02-23 04:50:00,2026-02-23 05:35:00,1939.47,1949.72,2.27,50,0.0585,0.6,0.06,0.54
+278,做空,2026-02-23 05:35:00,2026-02-23 07:20:00,1949.72,1951.6,2.28,50,0.0584,-0.11,0.06,-0.17
+279,做多,2026-02-23 07:20:00,2026-02-23 07:55:00,1951.6,1957.01,2.27,50,0.0582,0.32,0.06,0.26
+280,做空,2026-02-23 07:55:00,2026-02-23 08:25:00,1957.01,1947.41,2.28,50,0.0581,0.56,0.06,0.5
+281,做多,2026-02-23 08:25:00,2026-02-23 11:05:00,1947.41,1866.1,2.29,50,0.0589,-4.79,0.05,-4.85
+282,做空,2026-02-23 11:05:00,2026-02-23 11:15:00,1866.1,1858.39,2.25,50,0.0602,0.46,0.06,0.41
+283,做多,2026-02-23 11:15:00,2026-02-23 13:15:00,1858.39,1866.46,2.25,50,0.0605,0.49,0.06,0.43
+284,做空,2026-02-23 13:15:00,2026-02-23 16:35:00,1866.46,1877.82,2.25,50,0.0604,-0.69,0.06,-0.74
+285,做多,2026-02-23 16:35:00,2026-02-23 17:10:00,1877.82,1884.54,2.25,50,0.0598,0.4,0.06,0.35
+286,做空,2026-02-23 17:10:00,2026-02-23 20:30:00,1884.54,1907.37,2.25,50,0.0596,-1.36,0.06,-1.42
+287,做多,2026-02-23 20:30:00,2026-02-23 20:35:00,1907.37,1919.57,2.23,50,0.0585,0.71,0.06,0.66
+288,做空,2026-02-23 20:35:00,2026-02-23 22:35:00,1919.57,1906.62,2.24,50,0.0583,0.76,0.06,0.7
+289,做多,2026-02-23 22:35:00,2026-02-24 10:30:00,1906.62,1849.89,2.25,50,0.0589,-3.34,0.05,-3.4
+290,做空,2026-02-24 10:30:00,2026-02-24 11:00:00,1849.89,1836.02,2.22,50,0.06,0.83,0.06,0.78
+291,做多,2026-02-24 11:00:00,2026-02-24 13:05:00,1836.02,1836.44,2.23,50,0.0607,0.03,0.06,-0.03
+292,做空,2026-02-24 13:05:00,2026-02-24 13:20:00,1836.44,1815.44,2.23,50,0.0606,1.27,0.06,1.22
+293,做多,2026-02-24 13:20:00,2026-02-24 16:30:00,1815.44,1832.52,2.24,50,0.0616,1.05,0.06,1.0
+294,做空,2026-02-24 16:30:00,2026-02-24 17:05:00,1832.52,1824.3,2.25,50,0.0613,0.5,0.06,0.45
+295,做多,2026-02-24 17:05:00,2026-02-24 20:10:00,1824.3,1826.47,2.25,50,0.0617,0.13,0.06,0.08
+296,做空,2026-02-24 20:10:00,2026-02-24 21:20:00,1826.47,1819.72,2.25,50,0.0616,0.42,0.06,0.36
+297,做多,2026-02-24 21:20:00,2026-02-24 22:35:00,1819.72,1821.38,2.25,50,0.062,0.1,0.06,0.05
+298,做空,2026-02-24 22:35:00,2026-02-25 02:10:00,1821.38,1846.04,2.25,50,0.0619,-1.53,0.06,-1.58
+299,做多,2026-02-25 02:10:00,2026-02-25 03:05:00,1846.04,1853.79,2.24,50,0.0606,0.47,0.06,0.41
+300,做空,2026-02-25 03:05:00,2026-02-25 05:00:00,1853.79,1850.16,2.24,50,0.0605,0.22,0.06,0.16
+301,做多,2026-02-25 05:00:00,2026-02-25 09:05:00,1850.16,1864.09,2.24,50,0.0606,0.84,0.06,0.79
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strategy/results/bb_5m_param_sweep_conservative_2020_2025.csv

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strategy/results/bb_5m_param_sweep_conservative_2020_2025_no_pyramid.csv

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strategy/results/bb_5m_practical_upgrade_bandwidth_tune.csv

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+40,3.2,12,0.01,200.24642098781575,0.12321049390787665,1659,0,63.29113924050633,-2.2088172045713748,0.047913641900456855,3.3367725501172822,3.000389348021997
+40,3.2,12,0.005,200.22091496566105,0.11045748283052605,2002,0,62.38761238761239,-2.0783640787319086,0.03817994892546192,4.027940397396305,3.6224432772034887
+40,3.0,24,0.01,200.12568455038564,0.06284227519282126,1879,0,62.16072378924961,-2.6329610918170374,0.023564976494820568,3.787542396891309,3.4060828242510723
+40,3.0,6,0.008,200.0678037808892,0.03390189044459646,2194,0,63.947128532360985,-2.2038606611252476,0.01294800862092224,4.410398919734593,3.966658239689972
+30,3.0,6,0.0,200.00414940285927,0.002074701429634729,3569,0,61.58587839731017,-3.4138707553280483,-0.0006647490253754809,7.204083538326778,6.4809759087145915
+40,3.2,12,0.0,199.9609691102816,-0.019515444859194986,2060,0,61.99029126213592,-2.293284464503728,-0.012281258667209633,4.142089182262913,3.725180692979831
+30,3.0,12,0.0,199.86477350989745,-0.06761324505127675,3488,0,60.321100917431195,-3.9479783254082292,-0.026217988255613115,7.044972103443261,6.337776620729888
+30,3.0,24,0.005,199.8322173667805,-0.08389131660975124,3078,0,59.25925925925925,-4.517336088935309,-0.031095706303734948,6.227919385867038,5.602429614435114
+40,3.0,24,0.005,199.5939851399495,-0.20300743002525223,2287,0,60.690861390467866,-3.1641220863467083,-0.07962941557219835,4.605201690819581,4.141987512861499
+40,3.0,12,0.008,199.5739264063975,-0.21303679680124785,2148,0,63.17504655493482,-2.615052284973501,-0.08139777980329083,4.316235063292179,3.8819178516682813
+40,3.0,6,0.01,199.4783021660671,-0.2608489169664523,1988,0,63.581488933601605,-2.6165649578562693,-0.09950203972642017,3.991524078241081,3.5896750888907443
+40,3.0,24,0.0,199.34357556785355,-0.3282122160732257,2360,0,60.21186440677966,-3.3377613611040715,-0.1256995824626251,4.74929125388248,4.271670892552751
+30,3.0,24,0.0,199.30001953765344,-0.34999023117327965,3243,0,58.125192722787546,-4.896971344439777,-0.12506755033132605,6.553042403347132,5.89504751509868
+40,3.0,12,0.01,199.12086527405495,-0.4395673629725252,1956,0,62.985685071574636,-2.934702029502688,-0.16766517034426934,3.9282781540179963,3.532758588982499
+40,3.0,6,0.005,199.01319225044602,-0.49340387477698755,2458,0,62.9780309194467,-3.206770049240731,-0.19188065769564314,4.932566481122759,4.436623248761567
+40,3.0,6,0.0,198.65444873410513,-0.6727756329474346,2539,0,62.46553761323356,-3.483785802636902,-0.25943426479073867,5.091061673108702,4.579273159284268
+40,3.0,12,0.005,198.53430497909721,-0.7328475104513927,2400,0,62.041666666666664,-3.6063962830445178,-0.2822792363382157,4.814513695479092,4.33038262002996
+40,3.0,12,0.0,198.16460271518014,-0.9176986424099312,2480,0,61.41129032258065,-3.8946055152910333,-0.35154409034010436,4.970878228218944,4.47111508616677

strategy/results/bb_5m_practical_upgrade_candidates.csv

@@ -0,0 +1,9 @@
+name,bb_period,bb_std,lev,trend_ema,cooldown_bars,stop_loss,take_profit,final,ret,trades,liq,win,dd,sharpe,fee,rebate
+D_trend288_cd12,30,3.0,1,288.0,12,0.0,0.0,199.86477350989745,-0.06761324505127675,3488,0,60.321100917431195,-3.9479783254082292,-0.026217988255613115,7.044972103443261,6.337776620729888
+B_trend288,30,3.0,1,288.0,0,0.0,0.0,199.7540264365565,-0.1229867817217496,3668,0,62.05016357688113,-3.996173585769327,-0.046036770219455056,7.41289979748533,6.668913917641575
+C_trend576,30,3.0,1,576.0,0,0.0,0.0,199.20628338025136,-0.39685830987431814,4143,0,61.18754525706011,-4.6188391069942725,-0.14008705265439372,8.355454097286774,7.515422312937967
+E_trend288_cd12_sl12_tp15,30,3.0,1,288.0,12,0.012,0.015,195.3494628170402,-2.3252685914798974,3710,0,52.129380053908356,-4.882606479135802,-1.4756369432482566,7.362551062011999,6.62365864234843
+F_trend288_cd6_sl10_tp20,30,3.0,1,288.0,6,0.01,0.02,195.3050328845755,-2.347483557712252,3796,0,48.840885142255004,-5.078860622065719,-1.5321092835282057,7.536365316666955,6.7800929289619924
+H_bb20_30_trend576_cd12,20,3.0,1,576.0,12,0.01,0.015,189.48915432155357,-5.255422839223215,6395,0,49.1164972634871,-10.60519250897687,-2.8074280977201473,12.531119081963354,11.272889176910006
+G_bb20_28_trend288_cd12,20,2.8,1,288.0,12,0.012,0.015,189.04763867132164,-5.476180664339182,6479,0,52.106806605957715,-11.116408258934996,-2.9900816266006194,12.667135948143327,11.395318795619543
+A_base_no_filter,30,3.0,1,,0,0.0,0.0,187.87751952363539,-6.061240238182307,8669,0,61.62187103472142,-12.334791284875877,-1.4020222751730407,16.98060303079724,15.274934432023217

strategy/results/bb_5m_practical_upgrade_summary.csv

@@ -0,0 +1,3 @@
+label,final_equity,return_pct,trade_count,win_rate_pct,liq_count,max_drawdown,total_fee,total_rebate,sharpe
+"Baseline (BB30/3.0, no filters)",187.87751952363539,-6.061240238182307,8669,61.62187103472142,0,-12.334791284875877,16.98060303079724,15.274934432023217,-1.4020222751730407
+Practical (BB30/3.2 + EMA + BW + cooldown),202.98777028457513,1.4938851422875672,2208,64.4927536231884,0,-2.2659000933991535,4.492191078113778,4.042051704177064,0.5747142550615898

strategy/run_bb_15m_2020_2025.py

@@ -0,0 +1,111 @@
+"""
+BB(10, 2.5) 均值回归策略回测 — 15分钟K线 | 2020-2025 | 200U | 万五手续费 | 90%返佣次日8点到账
+"""
+import sys, time
+sys.stdout.reconfigure(line_buffering=True)
+sys.path.insert(0, str(__import__("pathlib").Path(__file__).resolve().parents[1]))
+
+import numpy as np
+import pandas as pd
+import matplotlib
+matplotlib.use("Agg")
+import matplotlib.pyplot as plt
+from pathlib import Path
+
+from strategy.bb_backtest import BBConfig, run_bb_backtest
+from strategy.data_loader import load_klines
+
+out_dir = Path(__file__).resolve().parent / "results"
+out_dir.mkdir(parents=True, exist_ok=True)
+
+# ============================================================
+# 加载 15 分钟 K 线数据 (2020-2025)
+# ============================================================
+YEARS = list(range(2020, 2026))
+data = {}
+
+print("加载 15 分钟 K 线数据 (2020-2025)...")
+t0 = time.time()
+for y in YEARS:
+    end_year = y + 1 if y < 2025 else 2026  # 2025 数据到 2026-01-01 前
+    df = load_klines('15m', f'{y}-01-01', f'{end_year}-01-01')
+    data[y] = df
+    print(f"  {y}: {len(df):>7,} 条  ({df.index[0]} ~ {df.index[-1]})")
+print(f"数据加载完成 ({time.time()-t0:.1f}s)\n")
+
+# ============================================================
+# 配置: 200U | 万五手续费 | 90%返佣次日8点到账
+# ============================================================
+cfg = BBConfig(
+    bb_period=10,
+    bb_std=2.5,
+    leverage=50,
+    initial_capital=200.0,
+    margin_pct=0.01,            # 1% 权益/单
+    max_daily_loss=50.0,        # 固定值备用
+    max_daily_loss_pct=0.05,    # 日亏损上限 = 当日起始权益的 5%
+    fee_rate=0.0005,            # 万五 (0.05%) 开平仓各万五
+    rebate_rate=0.0,
+    rebate_pct=0.90,            # 90% 手续费返佣
+    rebate_hour_utc=0,          # UTC 0点 = 北京时间早上8点到账
+    # 强平
+    liq_enabled=True,
+    maint_margin_rate=0.005,    # 0.5% 维持保证金率
+    # 滑点
+    slippage_pct=0.0005,        # 0.05% 滑点
+    # 市场容量限制
+    max_notional=500000.0,      # 单笔最大名义价值 50万U
+    # 加仓
+    pyramid_enabled=True,
+    pyramid_step=0.01,          # 递增加仓
+    pyramid_max=3,
+)
+
+# ============================================================
+# 运行回测 (滚仓: 200U 起，逐年累加不复位)
+# ============================================================
+df_full = pd.concat([data[y] for y in YEARS])
+r_full = run_bb_backtest(df_full, cfg)
+d_full = r_full.daily_stats
+eq_full = d_full["equity"].astype(float)
+pnl_full = d_full["pnl"].astype(float)
+eq_curve = r_full.equity_curve["equity"].dropna()
+
+final_eq = float(eq_full.iloc[-1])
+ret_pct = (final_eq - 200) / 200 * 100
+dd_full = float((eq_full - eq_full.cummax()).min())
+sharpe_full = float(pnl_full.mean() / pnl_full.std()) * np.sqrt(365) if pnl_full.std() > 0 else 0
+win_full = sum(1 for t in r_full.trades if t.net_pnl > 0) / max(len(r_full.trades), 1) * 100
+
+print("=" * 100)
+print("  BB(10, 2.5) 15分钟K线 | 200U 起滚仓 | 万五 fee | 90% 返佣 | 含强平+滑点+容量限制")
+print("=" * 100)
+liq_count = sum(1 for t in r_full.trades if t.fee == 0.0 and t.net_pnl < 0)
+print(f"  初始本金: 200U  |  最终权益: {final_eq:,.0f}U  |  收益率: {ret_pct:+,.1f}%")
+print(f"  交易次数: {len(r_full.trades)}  |  胜率: {win_full:.1f}%  |  强平次数: {liq_count}  |  最大回撤: {dd_full:+,.0f}U")
+print(f"  总手续费: {r_full.total_fee:,.0f}  |  总返佣: {r_full.total_rebate:,.0f}  |  Sharpe: {sharpe_full:.2f}")
+print("-" * 100)
+print("  年末权益:")
+for y in YEARS:
+    mask = eq_curve.index.year == y
+    if mask.any():
+        yr_eq = float(eq_curve.loc[mask].iloc[-1])
+        print(f"    {y} 年末: {yr_eq:,.0f}U")
+print("=" * 100)
+
+# ============================================================
+# 生成权益曲线图 (对数坐标，滚仓复利)
+# ============================================================
+fig, ax = plt.subplots(1, 1, figsize=(14, 6), dpi=120)
+eq_ser = eq_curve
+days = (eq_ser.index - eq_ser.index[0]).total_seconds() / 86400
+ax.semilogy(days, eq_ser.values.clip(min=1), color="#2563eb", linewidth=1.2)
+ax.axhline(y=200, color="gray", linestyle="--", alpha=0.6)
+ax.set_title("BB(10, 2.5) 15min | 200U | 0.05% fee 90% rebate | 2020-2025", fontsize=12, fontweight="bold")
+ax.set_xlabel("Days")
+ax.set_ylabel("Equity (USDT, log scale)")
+ax.grid(True, alpha=0.3)
+
+chart_path = out_dir / "bb_15m_200u_2020_2025.png"
+plt.savefig(chart_path, bbox_inches="tight")
+print(f"\n图表已保存: {chart_path}")

strategy/run_bb_15m_2020_2025_conservative.py

@@ -0,0 +1,323 @@
+"""
+Conservative BB backtest for bb_trade-style logic.
+
+Assumptions:
+1) Use 15m OHLC from 2020-01-01 to 2026-01-01 (exclusive).
+2) Bollinger band is computed from CLOSED bars (shifted by 1 bar).
+3) If bar i touches band, execute on bar i+1 open (no same-bar fill).
+4) Fee: 0.05% each side; rebate: 90% of daily fee, credited next day at 08:00 UTC+8 (UTC 00:00).
+5) Position sizing: 1% equity open, then +1%/+2%/+3% add ladder (max 3 adds).
+6) Leverage 50x; optional liquidation model enabled.
+"""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+from pathlib import Path
+import sys
+
+import numpy as np
+import pandas as pd
+
+sys.path.insert(0, str(Path(__file__).resolve().parents[1]))
+
+from strategy.data_loader import load_klines
+
+
+@dataclass
+class ConservativeConfig:
+    bb_period: int = 10
+    bb_std: float = 2.5
+    leverage: float = 50.0
+    initial_capital: float = 200.0
+    margin_pct: float = 0.01
+    pyramid_step: float = 0.01
+    pyramid_max: int = 3
+    fee_rate: float = 0.0005
+    rebate_pct: float = 0.90
+    rebate_hour_utc: int = 0
+    slippage_pct: float = 0.0005
+    liq_enabled: bool = True
+    maint_margin_rate: float = 0.005
+    max_daily_loss: float = 50.0
+
+
+def bollinger_prev_close(close: pd.Series, period: int, n_std: float) -> tuple[np.ndarray, np.ndarray]:
+    mid = close.rolling(period).mean().shift(1)
+    std = close.rolling(period).std(ddof=0).shift(1)
+    upper = (mid + n_std * std).to_numpy(dtype=float)
+    lower = (mid - n_std * std).to_numpy(dtype=float)
+    return upper, lower
+
+
+def run_conservative(df: pd.DataFrame, cfg: ConservativeConfig):
+    arr_open = df["open"].to_numpy(dtype=float)
+    arr_high = df["high"].to_numpy(dtype=float)
+    arr_low = df["low"].to_numpy(dtype=float)
+    arr_close = df["close"].to_numpy(dtype=float)
+    idx = df.index
+    n = len(df)
+
+    upper, lower = bollinger_prev_close(df["close"].astype(float), cfg.bb_period, cfg.bb_std)
+
+    balance = cfg.initial_capital
+    position = 0  # +1 long, -1 short
+    entry_price = 0.0
+    entry_qty = 0.0
+    entry_margin = 0.0
+    pyramid_count = 0
+
+    total_fee = 0.0
+    total_rebate = 0.0
+    trades = 0
+    win_trades = 0
+    liq_count = 0
+
+    day_fees = {}
+    current_day = None
+    day_start_equity = cfg.initial_capital
+    day_pnl = 0.0
+    day_stopped = False
+    rebate_applied_today = False
+
+    equity_arr = np.full(n, np.nan)
+    position_arr = np.zeros(n)
+
+    def unrealised(price: float) -> float:
+        if position == 0:
+            return 0.0
+        if position == 1:
+            return entry_qty * (price - entry_price)
+        return entry_qty * (entry_price - price)
+
+    def apply_open_slippage(side: int, price: float) -> float:
+        # Buy higher, sell lower
+        return price * (1 + cfg.slippage_pct) if side == 1 else price * (1 - cfg.slippage_pct)
+
+    def apply_close_slippage(side: int, price: float) -> float:
+        # Close long = sell lower; close short = buy higher
+        return price * (1 - cfg.slippage_pct) if side == 1 else price * (1 + cfg.slippage_pct)
+
+    def add_fee(ts: pd.Timestamp, fee: float):
+        nonlocal total_fee
+        total_fee += fee
+        d = ts.date()
+        day_fees[d] = day_fees.get(d, 0.0) + fee
+
+    def close_position(exec_price: float, exec_idx: int):
+        nonlocal balance, position, entry_price, entry_qty, entry_margin, pyramid_count
+        nonlocal trades, win_trades, day_pnl
+        if position == 0:
+            return
+
+        px = apply_close_slippage(position, exec_price)
+        gross = entry_qty * (px - entry_price) if position == 1 else entry_qty * (entry_price - px)
+        notional = entry_qty * px
+        fee = notional * cfg.fee_rate
+        net = gross - fee
+
+        balance += net
+        add_fee(idx[exec_idx], fee)
+        day_pnl += net
+        trades += 1
+        if net > 0:
+            win_trades += 1
+
+        position = 0
+        entry_price = 0.0
+        entry_qty = 0.0
+        entry_margin = 0.0
+        pyramid_count = 0
+
+    def open_position(side: int, exec_price: float, exec_idx: int, is_add: bool = False):
+        nonlocal balance, position, entry_price, entry_qty, entry_margin, pyramid_count
+        nonlocal day_pnl
+        px = apply_open_slippage(side, exec_price)
+        eq = balance + unrealised(px)
+
+        if is_add:
+            margin = eq * (cfg.margin_pct + cfg.pyramid_step * (pyramid_count + 1))
+        else:
+            margin = eq * cfg.margin_pct
+
+        margin = min(margin, balance * 0.95)
+        if margin <= 0:
+            return
+
+        notional = margin * cfg.leverage
+        qty = notional / px
+        fee = notional * cfg.fee_rate
+
+        balance -= fee
+        add_fee(idx[exec_idx], fee)
+        day_pnl -= fee
+
+        if is_add and position != 0:
+            old_notional = entry_qty * entry_price
+            new_notional = qty * px
+            entry_qty += qty
+            entry_price = (old_notional + new_notional) / entry_qty
+            entry_margin += margin
+            pyramid_count += 1
+        else:
+            position = side
+            entry_price = px
+            entry_qty = qty
+            entry_margin = margin
+            pyramid_count = 0
+
+    for i in range(n - 1):
+        ts = idx[i]
+        bar_day = ts.date()
+
+        if bar_day != current_day:
+            current_day = bar_day
+            day_start_equity = balance + unrealised(arr_close[i])
+            day_pnl = 0.0
+            day_stopped = False
+            rebate_applied_today = False
+
+        if (not rebate_applied_today) and ts.hour >= cfg.rebate_hour_utc:
+            prev_day = bar_day - pd.Timedelta(days=1)
+            prev_fee = day_fees.get(prev_day, 0.0)
+            if prev_fee > 0:
+                rebate = prev_fee * cfg.rebate_pct
+                balance += rebate
+                total_rebate += rebate
+            rebate_applied_today = True
+
+        if not day_stopped:
+            if day_pnl + unrealised(arr_close[i]) <= -cfg.max_daily_loss:
+                close_position(arr_open[i + 1], i + 1)
+                day_stopped = True
+
+        if cfg.liq_enabled and position != 0 and entry_margin > 0:
+            liq_threshold = 1.0 / cfg.leverage * (1 - cfg.maint_margin_rate)
+            if position == 1:
+                liq_price = entry_price * (1 - liq_threshold)
+                if arr_low[i] <= liq_price:
+                    balance -= entry_margin
+                    day_pnl -= entry_margin
+                    position = 0
+                    entry_price = 0.0
+                    entry_qty = 0.0
+                    entry_margin = 0.0
+                    pyramid_count = 0
+                    trades += 1
+                    liq_count += 1
+            elif position == -1:
+                liq_price = entry_price * (1 + liq_threshold)
+                if arr_high[i] >= liq_price:
+                    balance -= entry_margin
+                    day_pnl -= entry_margin
+                    position = 0
+                    entry_price = 0.0
+                    entry_qty = 0.0
+                    entry_margin = 0.0
+                    pyramid_count = 0
+                    trades += 1
+                    liq_count += 1
+
+        if day_stopped or np.isnan(upper[i]) or np.isnan(lower[i]):
+            equity_arr[i] = balance + unrealised(arr_close[i])
+            position_arr[i] = position
+            if balance <= 0:
+                balance = 0.0
+                equity_arr[i:] = 0.0
+                position_arr[i:] = 0
+                break
+            continue
+
+        touched_upper = arr_high[i] >= upper[i]
+        touched_lower = arr_low[i] <= lower[i]
+        exec_px = arr_open[i + 1]
+
+        if touched_upper and touched_lower:
+            pass
+        elif touched_upper:
+            if position == 1:
+                close_position(exec_px, i + 1)
+            if position == 0:
+                open_position(-1, exec_px, i + 1, is_add=False)
+            elif position == -1 and pyramid_count < cfg.pyramid_max:
+                open_position(-1, exec_px, i + 1, is_add=True)
+        elif touched_lower:
+            if position == -1:
+                close_position(exec_px, i + 1)
+            if position == 0:
+                open_position(1, exec_px, i + 1, is_add=False)
+            elif position == 1 and pyramid_count < cfg.pyramid_max:
+                open_position(1, exec_px, i + 1, is_add=True)
+
+        equity_arr[i] = balance + unrealised(arr_close[i])
+        position_arr[i] = position
+
+        if balance <= 0:
+            balance = 0.0
+            equity_arr[i:] = 0.0
+            position_arr[i:] = 0
+            break
+
+    if position != 0 and balance > 0:
+        close_position(arr_close[-1], n - 1)
+
+    equity_arr[-1] = balance
+    position_arr[-1] = 0
+
+    eq_df = pd.DataFrame({"equity": equity_arr, "position": position_arr}, index=idx)
+    daily = eq_df["equity"].resample("1D").last().dropna().to_frame("equity")
+    daily["pnl"] = daily["equity"].diff().fillna(0.0)
+
+    return {
+        "equity_curve": eq_df,
+        "daily": daily,
+        "final_equity": float(daily["equity"].iloc[-1]),
+        "trade_count": int(trades),
+        "win_rate": float(win_trades / max(trades, 1)),
+        "liq_count": int(liq_count),
+        "total_fee": float(total_fee),
+        "total_rebate": float(total_rebate),
+    }
+
+
+def main():
+    df = load_klines("15m", "2020-01-01", "2026-01-01")
+    cfg = ConservativeConfig()
+    result = run_conservative(df, cfg)
+
+    daily = result["daily"]
+    eq = daily["equity"].astype(float)
+    pnl = daily["pnl"].astype(float)
+    final_eq = float(eq.iloc[-1])
+    ret_pct = (final_eq - cfg.initial_capital) / cfg.initial_capital * 100
+    max_dd = float((eq - eq.cummax()).min()) if len(eq) else 0.0
+    sharpe = float(pnl.mean() / pnl.std() * np.sqrt(365)) if pnl.std() > 0 else 0.0
+
+    print("=" * 110)
+    print("Conservative BB(10,2.5) | 15m | 2020-2025 | 200U | fee 0.05% each side | 90% rebate next day 08:00")
+    print("=" * 110)
+    print(f"Final equity: {final_eq:.8f} U")
+    print(f"Return: {ret_pct:+.2f}%")
+    print(f"Trades: {result['trade_count']}")
+    print(f"Win rate: {result['win_rate']*100:.2f}%")
+    print(f"Liquidations: {result['liq_count']}")
+    print(f"Max drawdown: {max_dd:.2f} U")
+    print(f"Total fee: {result['total_fee']:.8f}")
+    print(f"Total rebate: {result['total_rebate']:.8f}")
+    print(f"Sharpe: {sharpe:.4f}")
+    print("-" * 110)
+    for year in range(2020, 2026):
+        m = daily.index.year == year
+        if m.any():
+            print(f"{year} year-end equity: {float(daily.loc[m, 'equity'].iloc[-1]):.8f} U")
+    print("=" * 110)
+
+    out_dir = Path(__file__).resolve().parent / "results"
+    out_dir.mkdir(parents=True, exist_ok=True)
+    out_csv = out_dir / "bb_15m_2020_2025_conservative_daily.csv"
+    daily.to_csv(out_csv)
+    print(f"Saved daily equity: {out_csv}")
+
+
+if __name__ == "__main__":
+    main()

strategy/run_bb_202602_detail.py

@@ -0,0 +1,67 @@
+"""
+bb_trade.py 策略回测 — 2026年2月，输出详细交易明细
+200U 本金 | 1% 仓位/单 | 万五手续费 | 90% 返佣次日8点到账
+按北京时间加载数据 (与交易所/网页显示一致)
+"""
+import sys
+sys.path.insert(0, str(__import__("pathlib").Path(__file__).resolve().parents[1]))
+
+import pandas as pd
+from pathlib import Path
+
+from strategy.bb_backtest import BBConfig, run_bb_backtest
+from strategy.data_loader import load_klines
+
+out_dir = Path(__file__).resolve().parent / "results"
+out_dir.mkdir(parents=True, exist_ok=True)
+
+# 按北京时间加载 2026-02-01 00:00 ~ 2026-03-01 00:00
+df = load_klines('5m', '2026-02-01', '2026-03-01', tz='Asia/Shanghai')
+
+cfg = BBConfig(
+    bb_period=10, bb_std=2.5, leverage=50, initial_capital=200.0,
+    margin_pct=0.01, max_daily_loss=50.0, fee_rate=0.0005,
+    rebate_pct=0.90, rebate_hour_utc=0, pyramid_enabled=False,  # 不加仓
+    pyramid_step=0.01, pyramid_max=3, slippage_pct=0.0, liq_enabled=True,
+    cross_margin=True,   # 全仓：仅权益<=0 时爆仓
+    fill_at_close=True,   # 真实成交：检测到信号后在 K 线收盘价成交
+)
+
+r = run_bb_backtest(df, cfg)
+
+# 数据库/回测使用 UTC，转为北京时间输出
+def to_beijing(ts):
+    if hasattr(ts, 'tz_localize'):
+        return ts.tz_localize('UTC').tz_convert('Asia/Shanghai').strftime('%Y-%m-%d %H:%M:%S')
+    return str(ts)[:19]
+
+# 构建交易明细 DataFrame
+rows = []
+for i, t in enumerate(r.trades, 1):
+    rows.append({
+        "序号": i,
+        "方向": "做多" if t.side == "long" else "做空",
+        "开仓时间": to_beijing(t.entry_time),
+        "平仓时间": to_beijing(t.exit_time),
+        "开仓价": round(t.entry_price, 2),
+        "平仓价": round(t.exit_price, 2),
+        "保证金": round(t.margin, 2),
+        "杠杆": t.leverage,
+        "数量": round(t.qty, 4),
+        "毛盈亏": round(t.gross_pnl, 2),
+        "手续费": round(t.fee, 2),
+        "净盈亏": round(t.net_pnl, 2),
+    })
+
+trade_df = pd.DataFrame(rows)
+
+# 保存 CSV
+csv_path = out_dir / "bb_202602_trade_detail.csv"
+trade_df.to_csv(csv_path, index=False, encoding="utf-8-sig")
+print(f"交易明细已保存: {csv_path}")
+
+# 打印到控制台
+print("\n" + "=" * 150)
+print(f"  交易明细 (共 {len(r.trades)} 笔)")
+print("=" * 150)
+print(trade_df.to_string(index=False))

strategy/run_bb_5m_practical_upgrade.py

@@ -0,0 +1,381 @@
+"""
+Practical upgraded BB backtest on 5m ETH data (2020-2025).
+
+Execution model (conservative):
+1) BB uses closed bars only (shift by 1 bar).
+2) Signal on bar i, execution at bar i+1 open.
+3) Fee = 0.05% each side, rebate = 90% next day at UTC 00:00 (UTC+8 08:00).
+4) Daily loss stop, liquidation, and slippage are enabled.
+
+Compares:
+- Baseline: BB(30, 3.0), 1x, no trend filter.
+- Practical: BB(30, 3.2), 1x, EMA trend filter, BB width filter, cooldown.
+"""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+from pathlib import Path
+import sys
+
+import numpy as np
+import pandas as pd
+
+sys.path.insert(0, str(Path(__file__).resolve().parents[1]))
+
+from strategy.data_loader import load_klines
+
+
+@dataclass
+class PracticalConfig:
+    bb_period: int = 30
+    bb_std: float = 3.2
+    leverage: float = 1.0
+    initial_capital: float = 200.0
+    margin_pct: float = 0.01
+    fee_rate: float = 0.0005
+    rebate_pct: float = 0.90
+    rebate_hour_utc: int = 0
+    slippage_pct: float = 0.0005
+    liq_enabled: bool = True
+    maint_margin_rate: float = 0.005
+    max_daily_loss: float = 50.0
+
+    # Practical risk controls
+    trend_ema_period: int = 288  # 288 * 5m = 24h EMA
+    min_bandwidth: float = 0.01  # (upper-lower)/mid minimum
+    cooldown_bars: int = 6       # 6 * 5m = 30 minutes
+
+
+def run_practical_backtest(df: pd.DataFrame, cfg: PracticalConfig):
+    arr_open = df["open"].to_numpy(dtype=float)
+    arr_high = df["high"].to_numpy(dtype=float)
+    arr_low = df["low"].to_numpy(dtype=float)
+    arr_close = df["close"].to_numpy(dtype=float)
+    idx = df.index
+    n = len(df)
+
+    close_s = df["close"].astype(float)
+    mid = close_s.rolling(cfg.bb_period).mean().shift(1)
+    std = close_s.rolling(cfg.bb_period).std(ddof=0).shift(1)
+    upper_s = mid + cfg.bb_std * std
+    lower_s = mid - cfg.bb_std * std
+    bandwidth_s = (upper_s - lower_s) / mid
+
+    upper = upper_s.to_numpy(dtype=float)
+    lower = lower_s.to_numpy(dtype=float)
+    bandwidth = bandwidth_s.to_numpy(dtype=float)
+
+    if cfg.trend_ema_period > 0:
+        trend_ema = close_s.ewm(span=cfg.trend_ema_period, adjust=False).mean().shift(1).to_numpy(dtype=float)
+    else:
+        trend_ema = np.full(n, np.nan)
+
+    balance = cfg.initial_capital
+    position = 0  # +1 long, -1 short
+    entry_price = 0.0
+    entry_qty = 0.0
+    entry_margin = 0.0
+
+    trades = 0
+    win_trades = 0
+    liq_count = 0
+    total_fee = 0.0
+    total_rebate = 0.0
+
+    current_day = None
+    day_pnl = 0.0
+    day_stopped = False
+    rebate_applied_today = False
+    next_trade_bar = 0
+    day_fees = {}
+
+    equity_arr = np.full(n, np.nan)
+    position_arr = np.zeros(n)
+
+    def unrealised(price: float) -> float:
+        if position == 0:
+            return 0.0
+        if position == 1:
+            return entry_qty * (price - entry_price)
+        return entry_qty * (entry_price - price)
+
+    def apply_open_slippage(side: int, price: float) -> float:
+        return price * (1 + cfg.slippage_pct) if side == 1 else price * (1 - cfg.slippage_pct)
+
+    def apply_close_slippage(side: int, price: float) -> float:
+        return price * (1 - cfg.slippage_pct) if side == 1 else price * (1 + cfg.slippage_pct)
+
+    def add_fee(ts: pd.Timestamp, fee: float):
+        nonlocal total_fee
+        total_fee += fee
+        d = ts.date()
+        day_fees[d] = day_fees.get(d, 0.0) + fee
+
+    def close_position(exec_price: float, exec_idx: int):
+        nonlocal balance, position, entry_price, entry_qty, entry_margin
+        nonlocal trades, win_trades, day_pnl
+        if position == 0:
+            return
+
+        px = apply_close_slippage(position, exec_price)
+        gross = entry_qty * (px - entry_price) if position == 1 else entry_qty * (entry_price - px)
+        notional = entry_qty * px
+        fee = notional * cfg.fee_rate
+        net = gross - fee
+
+        balance += net
+        add_fee(idx[exec_idx], fee)
+        day_pnl += net
+        trades += 1
+        if net > 0:
+            win_trades += 1
+
+        position = 0
+        entry_price = 0.0
+        entry_qty = 0.0
+        entry_margin = 0.0
+
+    def open_position(side: int, exec_price: float, exec_idx: int):
+        nonlocal balance, position, entry_price, entry_qty, entry_margin
+        nonlocal day_pnl
+        px = apply_open_slippage(side, exec_price)
+        eq = balance + unrealised(px)
+        margin = min(eq * cfg.margin_pct, balance * 0.95)
+        if margin <= 0:
+            return
+
+        notional = margin * cfg.leverage
+        qty = notional / px
+        fee = notional * cfg.fee_rate
+
+        balance -= fee
+        add_fee(idx[exec_idx], fee)
+        day_pnl -= fee
+
+        position = side
+        entry_price = px
+        entry_qty = qty
+        entry_margin = margin
+
+    for i in range(n - 1):
+        ts = idx[i]
+        bar_day = ts.date()
+
+        if bar_day != current_day:
+            current_day = bar_day
+            day_pnl = 0.0
+            day_stopped = False
+            rebate_applied_today = False
+
+        # Fee rebate settlement (next day 08:00 UTC+8 = UTC 00:00)
+        if (not rebate_applied_today) and ts.hour >= cfg.rebate_hour_utc:
+            prev_day = bar_day - pd.Timedelta(days=1)
+            prev_fee = day_fees.get(prev_day, 0.0)
+            if prev_fee > 0:
+                rebate = prev_fee * cfg.rebate_pct
+                balance += rebate
+                total_rebate += rebate
+            rebate_applied_today = True
+
+        # Daily loss stop
+        if not day_stopped and (day_pnl + unrealised(arr_close[i]) <= -cfg.max_daily_loss):
+            close_position(arr_open[i + 1], i + 1)
+            day_stopped = True
+
+        # Liquidation check
+        if cfg.liq_enabled and position != 0 and entry_margin > 0:
+            liq_threshold = 1.0 / cfg.leverage * (1 - cfg.maint_margin_rate)
+            if position == 1:
+                liq_price = entry_price * (1 - liq_threshold)
+                if arr_low[i] <= liq_price:
+                    balance -= entry_margin
+                    day_pnl -= entry_margin
+                    position = 0
+                    entry_price = 0.0
+                    entry_qty = 0.0
+                    entry_margin = 0.0
+                    trades += 1
+                    liq_count += 1
+            else:
+                liq_price = entry_price * (1 + liq_threshold)
+                if arr_high[i] >= liq_price:
+                    balance -= entry_margin
+                    day_pnl -= entry_margin
+                    position = 0
+                    entry_price = 0.0
+                    entry_qty = 0.0
+                    entry_margin = 0.0
+                    trades += 1
+                    liq_count += 1
+
+        if (
+            day_stopped
+            or i < next_trade_bar
+            or np.isnan(upper[i])
+            or np.isnan(lower[i])
+            or np.isnan(bandwidth[i])
+        ):
+            equity_arr[i] = balance + unrealised(arr_close[i])
+            position_arr[i] = position
+            if balance <= 0:
+                balance = 0.0
+                equity_arr[i:] = 0.0
+                position_arr[i:] = 0
+                break
+            continue
+
+        if cfg.trend_ema_period > 0 and np.isnan(trend_ema[i]):
+            equity_arr[i] = balance + unrealised(arr_close[i])
+            position_arr[i] = position
+            continue
+
+        if bandwidth[i] < cfg.min_bandwidth:
+            equity_arr[i] = balance + unrealised(arr_close[i])
+            position_arr[i] = position
+            continue
+
+        touched_upper = arr_high[i] >= upper[i]
+        touched_lower = arr_low[i] <= lower[i]
+        exec_px = arr_open[i + 1]
+
+        if cfg.trend_ema_period > 0:
+            long_ok = arr_close[i] > trend_ema[i]
+            short_ok = arr_close[i] < trend_ema[i]
+        else:
+            long_ok = True
+            short_ok = True
+
+        if touched_upper and touched_lower:
+            pass
+        elif touched_upper:
+            if position == 1:
+                close_position(exec_px, i + 1)
+                next_trade_bar = max(next_trade_bar, i + 1 + cfg.cooldown_bars)
+            if position == 0 and short_ok:
+                open_position(-1, exec_px, i + 1)
+                next_trade_bar = max(next_trade_bar, i + 1 + cfg.cooldown_bars)
+        elif touched_lower:
+            if position == -1:
+                close_position(exec_px, i + 1)
+                next_trade_bar = max(next_trade_bar, i + 1 + cfg.cooldown_bars)
+            if position == 0 and long_ok:
+                open_position(1, exec_px, i + 1)
+                next_trade_bar = max(next_trade_bar, i + 1 + cfg.cooldown_bars)
+
+        equity_arr[i] = balance + unrealised(arr_close[i])
+        position_arr[i] = position
+
+        if balance <= 0:
+            balance = 0.0
+            equity_arr[i:] = 0.0
+            position_arr[i:] = 0
+            break
+
+    if position != 0 and balance > 0:
+        close_position(arr_close[-1], n - 1)
+
+    equity_arr[-1] = balance
+    position_arr[-1] = 0
+
+    eq_df = pd.DataFrame({"equity": equity_arr, "position": position_arr}, index=idx)
+    daily = eq_df["equity"].resample("1D").last().dropna().to_frame("equity")
+    daily["pnl"] = daily["equity"].diff().fillna(0.0)
+
+    return {
+        "equity_curve": eq_df,
+        "daily": daily,
+        "final_equity": float(daily["equity"].iloc[-1]),
+        "trade_count": int(trades),
+        "win_rate": float(win_trades / max(trades, 1)),
+        "liq_count": int(liq_count),
+        "total_fee": float(total_fee),
+        "total_rebate": float(total_rebate),
+    }
+
+
+def summarize(label: str, result: dict, initial_capital: float):
+    daily = result["daily"]
+    eq = daily["equity"].astype(float)
+    pnl = daily["pnl"].astype(float)
+    final_eq = float(eq.iloc[-1])
+    ret_pct = (final_eq - initial_capital) / initial_capital * 100
+    max_dd = float((eq - eq.cummax()).min()) if len(eq) else 0.0
+    sharpe = float(pnl.mean() / pnl.std() * np.sqrt(365)) if pnl.std() > 0 else 0.0
+
+    print(f"[{label}]")
+    print(f"  Final equity: {final_eq:.6f} U")
+    print(f"  Return: {ret_pct:+.4f}%")
+    print(f"  Trades: {result['trade_count']} | Win rate: {result['win_rate']*100:.2f}% | Liquidations: {result['liq_count']}")
+    print(f"  Max drawdown: {max_dd:.6f} U | Sharpe: {sharpe:.4f}")
+    print(f"  Total fee: {result['total_fee']:.6f} | Total rebate: {result['total_rebate']:.6f}")
+    print("  Year-end equity:")
+    for year in range(2020, 2026):
+        m = daily.index.year == year
+        if m.any():
+            print(f"    {year}: {float(daily.loc[m, 'equity'].iloc[-1]):.6f} U")
+    print()
+
+    return {
+        "label": label,
+        "final_equity": final_eq,
+        "return_pct": ret_pct,
+        "trade_count": result["trade_count"],
+        "win_rate_pct": result["win_rate"] * 100,
+        "liq_count": result["liq_count"],
+        "max_drawdown": max_dd,
+        "total_fee": result["total_fee"],
+        "total_rebate": result["total_rebate"],
+        "sharpe": sharpe,
+    }
+
+
+def main():
+    df = load_klines("5m", "2020-01-01", "2026-01-01")
+
+    baseline_cfg = PracticalConfig(
+        bb_period=30,
+        bb_std=3.0,
+        leverage=1.0,
+        trend_ema_period=0,
+        min_bandwidth=0.0,
+        cooldown_bars=0,
+    )
+    practical_cfg = PracticalConfig(
+        bb_period=30,
+        bb_std=3.2,
+        leverage=1.0,
+        trend_ema_period=288,
+        min_bandwidth=0.01,
+        cooldown_bars=6,
+    )
+
+    print("=" * 118)
+    print("Practical Upgrade Backtest | 5m | 2020-2025 | capital=200U | fee=0.05% each side | rebate=90% next day 08:00")
+    print("=" * 118)
+    print("Execution: signal at bar i, fill at bar i+1 open (conservative)")
+    print()
+
+    baseline = run_practical_backtest(df, baseline_cfg)
+    practical = run_practical_backtest(df, practical_cfg)
+
+    summary_rows = []
+    summary_rows.append(summarize("Baseline (BB30/3.0, no filters)", baseline, baseline_cfg.initial_capital))
+    summary_rows.append(summarize("Practical (BB30/3.2 + EMA + BW + cooldown)", practical, practical_cfg.initial_capital))
+
+    out_dir = Path(__file__).resolve().parent / "results"
+    out_dir.mkdir(parents=True, exist_ok=True)
+
+    baseline_daily = baseline["daily"].rename(columns={"equity": "baseline_equity", "pnl": "baseline_pnl"})
+    practical_daily = practical["daily"].rename(columns={"equity": "practical_equity", "pnl": "practical_pnl"})
+    daily_compare = baseline_daily.join(practical_daily, how="outer")
+    daily_compare.to_csv(out_dir / "bb_5m_practical_upgrade_daily.csv")
+
+    pd.DataFrame(summary_rows).to_csv(out_dir / "bb_5m_practical_upgrade_summary.csv", index=False)
+
+    print(f"Saved: {out_dir / 'bb_5m_practical_upgrade_daily.csv'}")
+    print(f"Saved: {out_dir / 'bb_5m_practical_upgrade_summary.csv'}")
+
+
+if __name__ == "__main__":
+    main()

strategy/run_bb_trade_backtest.py

@@ -0,0 +1,197 @@
+"""
+回测 bb_trade.py 的 D方案策略
+BB(10, 2.5) | 5分钟 | ETH | 50x | 递增加仓+1%/次 max=3
+200U 本金 | 每次开仓 1% 权益 | 开平仓手续费万五 | 返佣90%次日早8点到账
+"""
+import sys, time
+sys.stdout.reconfigure(line_buffering=True)
+sys.path.insert(0, str(__import__("pathlib").Path(__file__).resolve().parents[1]))
+
+import numpy as np
+import pandas as pd
+import matplotlib
+matplotlib.use("Agg")
+import matplotlib.pyplot as plt
+from pathlib import Path
+
+from strategy.bb_backtest import BBConfig, run_bb_backtest
+from strategy.data_loader import load_klines
+
+out_dir = Path(__file__).resolve().parent / "results"
+out_dir.mkdir(parents=True, exist_ok=True)
+
+# ============================================================
+# 加载数据 2020-2025
+# ============================================================
+YEARS = list(range(2020, 2026))
+
+print("加载 5 分钟 K 线数据 (2020-2025)...")
+t0 = time.time()
+data = {}
+for y in YEARS:
+    df = load_klines('5m', f'{y}-01-01', f'{y+1}-01-01')
+    data[y] = df
+    print(f"  {y}: {len(df):>7,} 条  ({df.index[0]} ~ {df.index[-1]})")
+
+# 合并全量数据用于连续回测
+df_all = pd.concat([data[y] for y in YEARS])
+df_all = df_all[~df_all.index.duplicated(keep='first')].sort_index()
+print(f"  合计: {len(df_all):>7,} 条  ({df_all.index[0]} ~ {df_all.index[-1]})")
+print(f"数据加载完成 ({time.time()-t0:.1f}s)\n")
+
+# ============================================================
+# 配置 — 完全匹配 bb_trade.py D方案
+# ============================================================
+cfg = BBConfig(
+    bb_period=10,
+    bb_std=2.5,
+    leverage=50,
+    initial_capital=200.0,
+    margin_pct=0.01,           # 1% 权益/单
+    max_daily_loss=50.0,
+    fee_rate=0.0005,           # 万五 (0.05%) 每侧 (开+平各收一次)
+    rebate_rate=0.0,           # 无即时返佣
+    rebate_pct=0.90,           # 90% 手续费次日返还
+    rebate_hour_utc=0,         # UTC 0点 = 北京时间早上8点
+    pyramid_enabled=True,
+    pyramid_step=0.01,         # 递增加仓 +1%/次
+    pyramid_max=3,             # 最多加仓3次
+    slippage_pct=0.0,          # 回测不加滑点 (实盘浏览器市价单有滑点)
+    liq_enabled=True,
+    stop_loss_pct=0.0,
+)
+
+# ============================================================
+# 1) 逐年回测 (每年独立 200U 起步)
+# ============================================================
+print("=" * 100)
+print("  【逐年独立回测】每年独立 200U 本金")
+print(f"  BB({cfg.bb_period}, {cfg.bb_std}) | {cfg.leverage}x | 开仓={cfg.margin_pct:.0%}权益 | "
+      f"手续费={cfg.fee_rate:.4%}/侧 | 返佣={cfg.rebate_pct:.0%}次日8点")
+print("=" * 100)
+print(f"  {'年份':>6s}  {'最终权益':>10s}  {'收益率':>8s}  {'日均PnL':>8s}  {'交易次数':>8s}  {'胜率':>6s}  "
+      f"{'最大回撤':>10s}  {'回撤%':>8s}  {'总手续费':>10s}  {'总返佣':>10s}  {'净手续费':>10s}  {'Sharpe':>7s}")
+print("-" * 130)
+
+year_results = {}
+for y in YEARS:
+    r = run_bb_backtest(data[y], cfg)
+    year_results[y] = r
+
+    d = r.daily_stats
+    pnl = d["pnl"].astype(float)
+    eq = d["equity"].astype(float)
+    peak = eq.cummax()
+    dd = float((eq - peak).min())
+    dd_pct = dd / float(peak[eq - peak == dd].iloc[0]) * 100 if dd < 0 else 0
+    final_eq = float(eq.iloc[-1])
+    ret_pct = (final_eq - cfg.initial_capital) / cfg.initial_capital * 100
+    n_trades = len(r.trades)
+    win_rate = sum(1 for t in r.trades if t.net_pnl > 0) / max(n_trades, 1) * 100
+    avg_daily = float(pnl.mean())
+    sharpe = float(pnl.mean() / pnl.std()) * np.sqrt(365) if pnl.std() > 0 else 0
+    net_fee = r.total_fee - r.total_rebate
+
+    print(f"  {y:>6d}  {final_eq:>10.1f}  {ret_pct:>+7.1f}%  {avg_daily:>+7.2f}U  "
+          f"{n_trades:>8d}  {win_rate:>5.1f}%  {dd:>+10.1f}  {dd_pct:>+7.1f}%  "
+          f"{r.total_fee:>10.1f}  {r.total_rebate:>10.1f}  {net_fee:>10.1f}  {sharpe:>7.2f}")
+
+print()
+
+# ============================================================
+# 2) 连续回测 (2020-2025 一次性跑，资金连续滚动)
+# ============================================================
+print("=" * 100)
+print("  【连续回测】2020-2025 资金滚动，200U 起步")
+print("=" * 100)
+
+r_all = run_bb_backtest(df_all, cfg)
+
+d_all = r_all.daily_stats
+pnl_all = d_all["pnl"].astype(float)
+eq_all = d_all["equity"].astype(float)
+peak_all = eq_all.cummax()
+dd_all = float((eq_all - peak_all).min())
+dd_pct_all = dd_all / float(peak_all[eq_all - peak_all == dd_all].iloc[0]) * 100 if dd_all < 0 else 0
+final_eq_all = float(eq_all.iloc[-1])
+ret_pct_all = (final_eq_all - cfg.initial_capital) / cfg.initial_capital * 100
+n_trades_all = len(r_all.trades)
+win_rate_all = sum(1 for t in r_all.trades if t.net_pnl > 0) / max(n_trades_all, 1) * 100
+avg_daily_all = float(pnl_all.mean())
+sharpe_all = float(pnl_all.mean() / pnl_all.std()) * np.sqrt(365) if pnl_all.std() > 0 else 0
+net_fee_all = r_all.total_fee - r_all.total_rebate
+
+print(f"  初始资金:     {cfg.initial_capital:.0f} U")
+print(f"  最终权益:     {final_eq_all:.1f} U")
+print(f"  总收益率:     {ret_pct_all:+.1f}%")
+print(f"  日均 PnL:     {avg_daily_all:+.2f} U")
+print(f"  交易次数:     {n_trades_all}")
+print(f"  胜率:         {win_rate_all:.1f}%")
+print(f"  最大回撤:     {dd_all:+.1f} U ({dd_pct_all:+.1f}%)")
+print(f"  总手续费:     {r_all.total_fee:.1f} U")
+print(f"  总返佣:       {r_all.total_rebate:.1f} U")
+print(f"  净手续费:     {net_fee_all:.1f} U")
+print(f"  Sharpe:       {sharpe_all:.2f}")
+print()
+
+# 按年统计连续回测中的表现
+print("  连续回测逐年切片:")
+print(f"  {'年份':>6s}  {'年初权益':>10s}  {'年末权益':>10s}  {'年收益':>10s}  {'年收益率':>8s}")
+print("-" * 60)
+for y in YEARS:
+    mask = (eq_all.index >= f'{y}-01-01') & (eq_all.index < f'{y+1}-01-01')
+    if mask.sum() == 0:
+        continue
+    eq_year = eq_all[mask]
+    start_eq = float(eq_year.iloc[0])
+    end_eq = float(eq_year.iloc[-1])
+    yr_ret = end_eq - start_eq
+    yr_pct = yr_ret / start_eq * 100
+    print(f"  {y:>6d}  {start_eq:>10.1f}  {end_eq:>10.1f}  {yr_ret:>+10.1f}  {yr_pct:>+7.1f}%")
+print()
+
+# ============================================================
+# 图表
+# ============================================================
+fig, axes = plt.subplots(3, 1, figsize=(18, 18), dpi=120)
+
+# 图1: 逐年独立回测权益曲线
+ax1 = axes[0]
+colors = plt.cm.tab10(np.linspace(0, 1, len(YEARS)))
+for i, y in enumerate(YEARS):
+    r = year_results[y]
+    eq = r.equity_curve["equity"].dropna()
+    days = (eq.index - eq.index[0]).total_seconds() / 86400
+    ax1.plot(days, eq.values, label=f"{y}", color=colors[i], linewidth=0.8)
+ax1.set_title(f"BB(10,2.5) D方案 逐年独立回测 (200U起步)", fontsize=13, fontweight="bold")
+ax1.set_xlabel("天数")
+ax1.set_ylabel("权益 (USDT)")
+ax1.axhline(y=200, color="gray", linestyle="--", alpha=0.5, label="本金200U")
+ax1.legend(loc="upper left", fontsize=9)
+ax1.grid(True, alpha=0.3)
+
+# 图2: 连续回测权益曲线
+ax2 = axes[1]
+eq_curve = r_all.equity_curve["equity"].dropna()
+ax2.plot(eq_curve.index, eq_curve.values, color="steelblue", linewidth=0.6)
+ax2.set_title(f"BB(10,2.5) D方案 连续回测 2020-2025 (200U→{final_eq_all:.0f}U)", fontsize=13, fontweight="bold")
+ax2.set_xlabel("日期")
+ax2.set_ylabel("权益 (USDT)")
+ax2.axhline(y=200, color="gray", linestyle="--", alpha=0.5)
+ax2.grid(True, alpha=0.3)
+
+# 图3: 连续回测日PnL
+ax3 = axes[2]
+daily_pnl = r_all.daily_stats["pnl"].astype(float)
+colors_pnl = ['green' if x >= 0 else 'red' for x in daily_pnl.values]
+ax3.bar(daily_pnl.index, daily_pnl.values, color=colors_pnl, width=1, alpha=0.7)
+ax3.set_title("日 PnL 分布", fontsize=13, fontweight="bold")
+ax3.set_xlabel("日期")
+ax3.set_ylabel("PnL (USDT)")
+ax3.axhline(y=0, color="black", linewidth=0.5)
+ax3.grid(True, alpha=0.3)
+
+plt.tight_layout()
+chart_path = out_dir / "bb_trade_d_plan_2020_2025.png"
+plt.savefig(chart_path, bbox_inches="tight")
+print(f"图表已保存: {chart_path}")