feat: 备份 crypto/ + stocks/ 子目录到 skill 仓库

【备份】cron 已迁到 ~/.hermes/scripts/symlink, 旧副本 ~/.hermes/scripts/crypto/ 和 stocks/ 即将删, 先备份
- crypto-t-monitor/scripts/backtest.py + okx_t_monitor.py
- intraday-trading/scripts/{hk,us}_intraday_cli.py + hk_intraday_cli_runner.sh
- strategy-management/scripts/backtest.py (与 crypto-t-monitor 重复, 备份占位)

【未删本地】等用户确认

crypto-t-monitor/scripts/backtest.py

@@ -0,0 +1,216 @@
+#!/usr/bin/env python3
+"""
+OKX 币圈做T 回测工具 (v2.0.0)
+基于历史 K 线模拟策略, 验证 buy/sell 价位参数
+"""
+import os, json, sys, argparse, datetime
+sys.path.insert(0, os.path.dirname(__file__))
+
+# 加载凭证
+okx_creds = {}
+with open(os.path.expanduser('~/.bashrc')) as f:
+    import re
+    for line in f:
+        m = re.match(r'export\s+(OKX_\w+)=(.*)', line.strip())
+        if m:
+            okx_creds[m.group(1)] = m.group(2).strip().strip('"').strip("'")
+
+
+def fetch_history_klines(sym, bar='1H', days=30):
+    """拉 OKX 历史 K 线 (OKX 限制单次 100 根, 多页拉)
+    用 OKX 的 'after' 参数翻页 (传毫秒时间戳)
+    """
+    import subprocess
+    import hmac, base64, hashlib
+
+    all_data = []
+    # OKX 时间戳 (毫秒)
+    cur_ts = int(datetime.datetime.utcnow().timestamp() * 1000)
+
+    # 计算需要多少页 (1H K线, 24 根/天)
+    pages = max(1, (days * 24 + 99) // 100)
+
+    for page in range(pages):
+        path = f"/api/v5/market/history-candles?instId={sym}-USDT-SWAP&bar={bar}&limit=100&after={cur_ts}"
+
+        msg = datetime.datetime.utcnow().strftime('%Y-%m-%dT%H:%M:%S.') + \
+              f"{datetime.datetime.utcnow().microsecond // 1000:03d}Z" + 'GET' + path
+        signature = base64.b64encode(
+            hmac.new(okx_creds['OKX_SECRET'].encode(), msg.encode(), hashlib.sha256).digest()
+        ).decode()
+        ts_str = msg[:30]  # YYYY-MM-DDTHH:MM:SS.sssZ (但实际上 ms 只有 3 位 + Z)
+        # 修正: 用 'Z' 结尾的后 24 字节
+
+        curl_cmd = [
+            'curl', '-s', '--proxy', 'http://127.0.0.1:7890',
+            '-H', f'OK-ACCESS-KEY: {okx_creds["OKX_API_KEY"]}',
+            '-H', f'OK-ACCESS-SIGN: {signature}',
+            '-H', f'OK-ACCESS-TIMESTAMP: {ts_str}',
+            '-H', f'OK-ACCESS-PASSPHRASE: {okx_creds["OKX_PASSPHRASE"]}',
+            f'https://www.okx.com{path}'
+        ]
+        try:
+            r = subprocess.run(curl_cmd, capture_output=True, text=True, timeout=20)
+            data = json.loads(r.stdout)
+            if data.get('code') == '0':
+                klines = data.get('data', [])
+                if not klines:
+                    break
+                all_data.extend(klines)
+                # 翻页: after 是上一个数据最小时间戳 - 1
+                cur_ts = int(klines[-1][0]) - 1
+                if len(klines) < 100:
+                    break
+            else:
+                print(f"⚠️ Page {page} code={data.get('code')} msg={data.get('msg')}")
+                break
+        except Exception as e:
+            print(f"⚠️ Page {page} failed: {e}")
+            break
+
+    print(f"📥 拉到 {len(all_data)} 根 K 线")
+    return all_data
+
+
+def calc_atr(klines, period=14):
+    """ATR 计算"""
+    if len(klines) < period + 1:
+        return None
+    closes = [float(k[4]) for k in klines]
+    highs = [float(k[2]) for k in klines]
+    lows = [float(k[3]) for k in klines]
+
+    trs = []
+    for i in range(1, len(closes)):
+        tr = max(highs[i] - lows[i],
+                 abs(highs[i] - closes[i-1]),
+                 abs(lows[i] - closes[i-1]))
+        trs.append(tr)
+    return sum(trs[-period:]) / period
+
+
+def simulate_strategy(klines, atr_multiplier=0.5, t_qty=0.05, leverage=25, ct_val=0.1, initial_usdt=1000, threshold=0.003):
+    """基于历史 K 线模拟做T策略
+    每小时检查价位:
+      - 跌到 buy1/buy2 → 买入
+      - 涨到 sell1/sell2 → 卖出
+    持仓同步变化 (跟 okx_t_monitor 一致)
+    """
+    trades = []
+    position = 0
+    avg_cost = 0
+    last_trade_ts = None
+
+    for i in range(20, len(klines)):
+        row = klines[i]
+        ts = row[0]
+        high = float(row[2])
+        low = float(row[3])
+        close = float(row[4])
+
+        # 计算过去 14 根 K 线的 ATR
+        past = klines[i-20:i]
+        atr = calc_atr(past, 14)
+        if not atr:
+            continue
+
+        buy1 = close - atr * atr_multiplier * 0.5
+        buy2 = close - atr * atr_multiplier
+        sell1 = close + atr * atr_multiplier * 0.5
+        sell2 = close + atr * atr_multiplier
+
+        # 检查是否触及价位 (用 high/low 比对 close)
+        if last_trade_ts == ts:
+            continue
+
+        # 优先 sell1 > buy1 (趋势方向)
+        if position > 0 and (high >= sell2 or (high >= sell1 and position > 0)):
+            # 卖出
+            sell_price = sell2 if high >= sell2 else sell1
+            pnl = (sell_price - avg_cost) * position
+            trades.append(('sell', sell_price, position, pnl, ts))
+            position = 0
+            avg_cost = 0
+            last_trade_ts = ts
+        elif position == 0 and (low <= buy2 or low <= buy1):
+            buy_price = buy2 if low <= buy2 else buy1
+            position = t_qty
+            avg_cost = buy_price
+            trades.append(('buy', buy_price, position, None, ts))
+            last_trade_ts = ts
+
+    # 统计
+    total_pnl = sum(t[3] for t in trades if t[3] is not None)
+    buy_count = sum(1 for t in trades if t[0] == 'buy')
+    sell_count = sum(1 for t in trades if t[0] == 'sell')
+    win_trades = [t for t in trades if t[3] and t[3] > 0]
+    win_rate = len(win_trades) / sell_count * 100 if sell_count > 0 else 0
+
+    return {
+        'trades': trades,
+        'total_pnl': total_pnl,
+        'buy_count': buy_count,
+        'sell_count': sell_count,
+        'win_rate': win_rate,
+        'final_position': position,
+        'final_avg_cost': avg_cost,
+    }
+
+
+def main():
+    parser = argparse.ArgumentParser(description='币圈做T回测 (v2.0.0)')
+    parser.add_argument('symbol', help='币种 (如 ETH)')
+    parser.add_argument('--mode', choices=['short', 'trend'], default='trend',
+                        help='short=日内(1H,默认) / trend=趋势(4H,默认短期)')
+    parser.add_argument('--days', type=int, default=30, help='回测天数 (short=7, trend=30)')
+    parser.add_argument('--bar', default=None, help='K 线周期 (覆盖 mode 默认)')
+    parser.add_argument('--atr-multiplier', type=float, default=None, help='ATR 倍数')
+    parser.add_argument('--t-qty', type=float, default=0.05, help='每笔数量 (默认 0.05)')
+    parser.add_argument('--leverage', type=int, default=25, help='杠杆 (默认 25)')
+    parser.add_argument('--ct-val', type=float, default=0.1, help='合约面值 (默认 0.1)')
+    args = parser.parse_args()
+
+    # Mode-based defaults
+    if args.bar is None:
+        args.bar = '1H' if args.mode == 'short' else '4H'
+    if args.atr_multiplier is None:
+        # Trend: 更宽价位 (ATR × 1.5), 避免被洗
+        args.atr_multiplier = 0.5 if args.mode == 'short' else 1.5
+    if args.days == 30:  # 如果用户没指定，按 mode
+        args.days = 7 if args.mode == 'short' else 30
+
+    print(f"📊 {args.symbol} {args.bar} 回测 ({args.days} 天, mode={args.mode})")
+    print(f"   ATR={args.atr_multiplier} t_qty={args.t_qty} lev={args.leverage}x")
+    print()
+
+    # 拉数据
+    klines = fetch_history_klines(args.symbol, args.bar, args.days)
+    if not klines:
+        print("❌ 没拉到数据")
+        sys.exit(1)
+    print(f"✅ 拉到 {len(klines)} 根 K 线")
+    print()
+
+    # 模拟
+    result = simulate_strategy(klines, args.atr_multiplier, args.t_qty,
+                              args.leverage, args.ct_val)
+
+    # 报告
+    print(f"📈 回测结果:")
+    print(f"   买入: {result['buy_count']} 次")
+    print(f"   卖出: {result['sell_count']} 次")
+    print(f"   胜率: {result['win_rate']:.1f}%")
+    print(f"   总盈亏: ${result['total_pnl']:.2f}")
+    print(f"   最终仓位: {result['final_position']}张 @ ${result['final_avg_cost']:.2f}" if result['final_position'] > 0 else "   最终仓位: 0 (全平)")
+
+    # Top 5 交易
+    closed = [t for t in result['trades'] if t[3] is not None]
+    if closed:
+        print()
+        print(f"   Top 5 盈利交易:")
+        for t in sorted(closed, key=lambda x: -x[3])[:5]:
+            print(f"     ${t[1]:.2f} | pnl ${t[3]:.2f} | {t[4]}")
+
+
+if __name__ == '__main__':
+    main()

crypto-t-monitor/scripts/okx_t_monitor.py

@@ -0,0 +1,563 @@
+#!/usr/bin/env python3
+"""
+OKX 币圈做T - 多币种 + 动态 ATR 价位 + 网络重试
+v2.0.0 (2026-07-10):
+  - 多币种自动 (默认 ETH/BTC/SOL/DOGE)
+  - 动态 ATR 价位计算 (基于 1H K线)
+  - 网络重试机制 (Clash 抽风时)
+  - STATE_FILE 自动清理 (7 天前)
+  - 支持 limit 单 (替代 market 滑点)
+"""
+import os, json, subprocess, datetime, time, shlex
+
+# ============ 加载凭证 ============
+okx_creds = {}
+with open(os.path.expanduser('~/.bashrc')) as f:
+    for line in f:
+        import re
+        m = re.match(r'export\s+(OKX_\w+)=(.*)', line.strip())
+        if m:
+            okx_creds[m.group(1)] = m.group(2).strip().strip('"').strip("'")
+
+# ============ 配置 ============
+# 主流币池 (每 3 天由用户挑 2 个换)
+# 2026-07-10 当前: ETH, BTC (高流动性, 用户偏好)
+DEFAULT_SYMBOLS = ['ETH', 'BTC', 'SPCX']  # SPCX 是用户现有持仓
+# 历史轮换 (供参考): 7/10 [ETH, BTC]; 7/13 [ETH, SOL]; 7/16 [ETH, DOGE] etc.
+
+# 自动从 OKX 实际持仓池扩展 (用户加仓任何币都会被覆盖监控)
+AUTO_INCLUDE_HOLDINGS = True
+
+# v2.4: 新币默认 dry-run (避免自动开仓到没参数的新币上)
+# 用户原话: "水果刀好" — 止盈止损,不让程序误开仓
+# 新币第一次扫描会推警告, 但不自动交易, 等用户手动加进 SYMBOL_SPECS 调参后才会执行
+DRY_RUN_NEW_COIN = True  # 默认 dry-run 新币
+
+# 默认币种的 spec (含手动调过的)
+SYMBOL_SPECS = {
+    'ETH': {'ct_val': 0.1, 'leverage': 25, 't_qty': 0.05, 'min_sz': 0.01},
+    'BTC': {'ct_val': 0.01, 'leverage': 25, 't_qty': 0.03, 'min_sz': 0.01},
+    'SOL': {'ct_val': 1.0, 'leverage': 20, 't_qty': 5.0, 'min_sz': 1.0},
+    'DOGE': {'ct_val': 10.0, 'leverage': 20, 't_qty': 30.0, 'min_sz': 1.0},
+    'XRP': {'ct_val': 10.0, 'leverage': 20, 't_qty': 30.0, 'min_sz': 1.0},
+    'SPCX': {'ct_val': 1.0, 'leverage': 5, 't_qty': 0.5, 'min_sz': 0.01},
+}
+
+LEVELS = {}  # 动态填充, 启动时基于 ATR 算
+
+STATE_FILE = os.path.expanduser('~/.hermes/trading/t_state.json')
+
+# ============ 工具函数 ============
+def load_state():
+    try:
+        with open(STATE_FILE) as f:
+            return json.load(f)
+    except Exception:
+        return {}
+
+def save_state(state):
+    os.makedirs(os.path.dirname(STATE_FILE), exist_ok=True)
+    with open(STATE_FILE, 'w') as f:
+        json.dump(state, f)
+
+def cleanup_state(state, keep_days=7):
+    """自动清理 7 天前的状态"""
+    cutoff = (datetime.datetime.now() - datetime.timedelta(days=keep_days)).strftime('%Y-%m-%d')
+    return {k: v for k, v in state.items() if k.split('_')[-1] >= cutoff}
+
+def okx_request(method, endpoint, body=None, params=None, retries=2):
+    """OKX API 通用请求, 带重试"""
+    import hmac, base64, hashlib
+    ts = datetime.datetime.utcnow().strftime('%Y-%m-%dT%H:%M:%S.') + f"{datetime.datetime.utcnow().microsecond // 1000:03d}Z"
+    path = endpoint + (('?' + params) if params else '')
+    body_str = json.dumps(body) if body else ''
+    msg = ts + method + path + body_str
+    sig = base64.b64encode(hmac.new(okx_creds['OKX_SECRET'].encode(), msg.encode(), hashlib.sha256).digest()).decode()
+
+    for attempt in range(retries + 1):
+        try:
+            cmd = ['curl', '-s', '--proxy', 'http://127.0.0.1:7890',
+                '-X', method,
+                '-H', f'OK-ACCESS-KEY: {okx_creds["OKX_API_KEY"]}',
+                '-H', f'OK-ACCESS-SIGN: {sig}',
+                '-H', f'OK-ACCESS-TIMESTAMP: {ts}',
+                '-H', f'OK-ACCESS-PASSPHRASE: {okx_creds["OKX_PASSPHRASE"]}',
+                '-H', 'Content-Type: application/json',
+                f'https://www.okx.com{path}']
+            if body:
+                cmd += ['-d', body_str]
+            r = subprocess.run(cmd, capture_output=True, text=True, timeout=15)
+            data = json.loads(r.stdout)
+            if data.get('code') == '0':
+                return data
+            if attempt < retries:
+                time.sleep(2)
+                continue
+            return data
+        except Exception as e:
+            if attempt < retries:
+                time.sleep(2)
+                continue
+            return {'code': '-1', 'msg': str(e)}
+    return {'code': '-1', 'msg': 'max retries'}
+
+def get_ticker(sym):
+    """拿当前价格"""
+    r = okx_request('GET', '/api/v5/market/ticker', params=f'instId={sym}-USDT-SWAP')
+    if r.get('code') == '0' and r.get('data'):
+        return float(r['data'][0]['last'])
+    return None
+
+def get_balance():
+    """拿 USDT 余额"""
+    r = okx_request('GET', '/api/v5/account/balance')
+    for d in r.get('data', []):
+        for c in d.get('details', []):
+            if c['ccy'] == 'USDT':
+                return float(c['availBal'])
+    return 0
+
+def get_position(sym):
+    """拿某币种持仓"""
+    r = okx_request('GET', '/api/v5/account/positions', params='instType=SWAP')
+    for p in r.get('data', []):
+        if sym in p.get('instId', '') and float(p.get('pos', 0)) != 0:
+            return float(p['pos']), float(p['avgPx']), float(p.get('upl', 0))
+    return 0, 0, 0
+
+def get_held_symbols():
+    """拿所有持仓币种 (自动覆盖监控)
+    Returns: list of sym strings (e.g. ['SPCX'])
+    """
+    r = okx_request('GET', '/api/v5/account/positions', params='instType=SWAP')
+    syms = set()
+    for p in r.get('data', []):
+        pos = float(p.get('pos', 0))
+        if abs(pos) > 0:
+            # instId like "SPCX-USDT-SWAP" → "SPCX"
+            inst = p.get('instId', '')
+            if '-USDT-SWAP' in inst:
+                sym = inst.replace('-USDT-SWAP', '')
+                syms.add(sym)
+    return list(syms)
+
+def get_klines(sym, bar='1H', limit=100):
+    """拿 K线数据"""
+    r = okx_request('GET', '/api/v5/market/candles',
+                    params=f'instId={sym}-USDT-SWAP&bar={bar}&limit={limit}')
+    if r.get('code') == '0':
+        return r.get('data', [])
+    return []
+
+def calc_levels_from_atr(sym, atr_period=14, atr_multiplier=0.5):
+    """基于 ATR 动态算 buy/sell 价位
+    Buy1 = price - 0.5*ATR
+    Buy2 = price - 1.0*ATR
+    Sell1 = price + 0.5*ATR
+    Sell2 = price + 1.0*ATR
+    """
+    klines = get_klines(sym, '1H', atr_period + 5)
+    if not klines:
+        return None
+    # K线格式: [ts, open, high, low, close, vol, ...]
+    closes = [float(k[4]) for k in klines[-atr_period:]]
+    highs = [float(k[2]) for k in klines[-atr_period:]]
+    lows = [float(k[3]) for k in klines[-atr_period:]]
+    # ATR = 平均真实波幅
+    trs = []
+    for i in range(1, len(closes)):
+        tr = max(highs[i] - lows[i], abs(highs[i] - closes[i-1]), abs(lows[i] - closes[i-1]))
+        trs.append(tr)
+    atr = sum(trs) / len(trs)
+    price = closes[-1]
+    return {
+        'cost': price,
+        'buy1': round(price - atr * atr_multiplier * 0.7, 2),
+        'buy2': round(price - atr * atr_multiplier, 2),
+        'sell1': round(price + atr * atr_multiplier * 0.7, 2),
+        'sell2': round(price + atr * atr_multiplier, 2),
+        'atr': atr,
+    }
+
+def execute_trade(sym, side, qty, ord_type='market', limit_price=None, reduce_only=False):
+    """下单
+    reduce_only=True 时只减仓不开仓 (用于平仓信号), 防止方向错误开新仓位.
+    """
+    body = {
+        "instId": f"{sym}-USDT-SWAP",
+        "tdMode": "cross",
+        "side": side,
+        "ordType": ord_type,
+        "sz": str(qty),
+    }
+    if ord_type == 'limit' and limit_price:
+        body['px'] = str(limit_price)
+    if reduce_only:
+        body['reduceOnly'] = True
+    return okx_request('POST', '/api/v5/trade/order', body=body)
+
+def push_qq(msg):
+    """推送到 QQ"""
+    push_cmd = f'bash {os.path.expanduser("~")}/.hermes/scripts/push_to_qq.sh {shlex.quote(msg)}'
+    subprocess.run(push_cmd, shell=True, capture_output=True, timeout=30)
+
+NEW_COIN_DAYS = 30  # 30 天内新列出的算"新币"
+NEW_COIN_AUTO_WATCH = True  # 自动加入监控列表
+NEW_COIN_PICKS = 2  # 每次扫描后筛 X 个 (按 24h vol 排序)
+NEW_COIN_POOL_MAX = 6  # 新币候选池上限 (永久保留, 超过这个数删最旧的)
+NEW_COIN_MIN_VOLUME_USDT = 1_000_000  # 最低 24h 成交量 $1M (过滤无人币/低流动性)
+NEW_COIN_PUSH_TO_QQ = True  # 新入选推 QQ (变化时才推)
+
+def get_new_swap_symbols(days=NEW_COIN_DAYS, top_n=NEW_COIN_PICKS, min_volume=NEW_COIN_MIN_VOLUME_USDT):
+    """从 OKX 拉所有 SWAP, 挑出近 N 天新上市的 + 高流动性的 top_n 个
+    筛选条件:
+      1. 30 天内新列 (listTime)
+      2. 24h 成交量 > min_volume (排除无人币/低流动性)
+      3. 按 24h 成交量排序, 取前 top_n
+    Returns: list of {'sym': 'XXX', 'listTime': ts, 'vol24h': volume}
+    """
+    try:
+        # 拉所有合约
+        cmd = ['curl', '-s', '--proxy', 'http://127.0.0.1:7890',
+            'https://www.okx.com/api/v5/public/instruments?instType=SWAP&limit=500']
+        r = subprocess.run(cmd, capture_output=True, text=True, timeout=20)
+        data = json.loads(r.stdout)
+        if data.get('code') != '0':
+            return []
+
+        cutoff_ts = int((datetime.datetime.utcnow().timestamp() - days * 86400) * 1000)
+        candidates = []
+        for ins in data.get('data', []):
+            inst_id = ins.get('instId', '')
+            if '-USDT-SWAP' not in inst_id:
+                continue
+            list_time = int(ins.get('listTime', 0))
+            if list_time < cutoff_ts:
+                continue
+            if ins.get('state') != 'live':
+                continue
+            sym = inst_id.replace('-USDT-SWAP', '')
+            # 过滤: ctVal 太大或太小的(异常币)
+            ct_val = float(ins.get('ctVal', 1))
+            lot_sz = float(ins.get('lotSz', 1))
+            if ct_val > 1000 or ct_val < 0.001:
+                continue
+            if lot_sz > 1000 or lot_sz < 0.0001:
+                continue
+            candidates.append({
+                'sym': sym,
+                'listTime': list_time,
+                'instId': inst_id,
+                'ctVal': ct_val,
+                'lotSz': lot_sz,
+            })
+
+        if not candidates:
+            return []
+
+        # 第二轮: 拉每个候选的 24h 成交量, 过滤 + 排序
+        cutoff_check_ts = int(datetime.datetime.utcnow().timestamp() * 1000) - 86400 * 1000
+        cmd2 = ['curl', '-s', '--proxy', 'http://127.0.0.1:7890',
+            'https://www.okx.com/api/v5/market/tickers?instType=SWAP']
+        r2 = subprocess.run(cmd2, capture_output=True, text=True, timeout=20)
+        tickers = json.loads(r2.stdout).get('data', [])
+        vol_map = {}
+        for t in tickers:
+            inst_id = t.get('instId', '')
+            if '-USDT-SWAP' in inst_id:
+                sym = inst_id.replace('-USDT-SWAP', '')
+                vol_ccy = float(t.get('volCcy24h', 0))
+                vol_map[sym] = vol_ccy
+
+        scored = []
+        for c in candidates:
+            vol = vol_map.get(c['sym'], 0)
+            if vol < min_volume:
+                continue
+            scored.append({
+                **c,
+                'vol24h': vol,
+            })
+
+        # 按 vol24h 排序, 取 top_n
+        scored.sort(key=lambda x: -x['vol24h'])
+        return scored[:top_n]
+    except Exception as e:
+        print(f"⚠️ 拉新币列表失败: {e}")
+        return []
+
+
+def find_nearest_level(price, levels, traded_levels):
+    """找最近的关键位"""
+    threshold = 0.005  # 0.5% 容差
+    nearest = None
+    min_dist = float('inf')
+    for name in ['buy2', 'buy1', 'sell1', 'sell2']:
+        if levels.get(name) is None:
+            continue
+        dist = abs(price - levels[name]) / price
+        if dist < threshold and dist < min_dist:
+            min_dist = dist
+            nearest = name
+    return nearest
+
+def check_changes(sym, price, pos_qty, avg_px, upl, levels, state, skip_for=set()):
+    """检测变化并返回需要推送的事件
+    skip_for: set of symbols, 跳过这些币种的"持仓变化"和"价格触及"推送 (做T 已专门推)
+    """
+    events = []
+    skip_this = sym in skip_for
+
+    # 1. 持仓变化检测 — 跳过刚做T的 (做T已专门推)
+    # 关键修复: 没持仓时 (pos_qty=0) 不推变化 — 用户原话"没持仓的不要推了"
+    prev_pos = state.get(f'{sym}_prev_pos')
+    has_pos_now = abs(pos_qty) > 0.01
+    if has_pos_now and prev_pos is not None and abs(pos_qty - prev_pos) > 0.001:
+        if not skip_this:
+            events.append(f'🔄 持仓变化: {prev_pos:.2f} → {pos_qty:.2f} 张')
+
+    # 2. 价格触及关键位 — 跳过刚做T的 (做T已专门推), 没持仓也不推
+    if not skip_this and has_pos_now:
+        nearest = find_nearest_level(price, levels, [])
+        if nearest:
+            level_price = levels[nearest]
+            dist_pct = abs(price - level_price) / price * 100
+            events.append(f'📍 价格触及 {nearest}={level_price:.2f} (距 {dist_pct:.2f}%)')
+
+    # 3. 浮盈/浮亏变化 (>3% 且相对上次变化 >2%)
+    if avg_px > 0 and has_pos_now:
+        leverage = SYMBOL_SPECS.get(sym, {}).get('leverage', 25)
+        pos_sign = 1 if pos_qty > 0 else -1
+        upl_pct = (price - avg_px) / avg_px * 100 * leverage * pos_sign
+
+        prev_upl_pct = state.get(f'{sym}_prev_upl_pct')
+        if prev_upl_pct is not None and abs(upl_pct) >= 5:
+            upl_diff = upl_pct - prev_upl_pct
+            if abs(upl_diff) >= 3:
+                emoji = '📈' if upl_diff > 0 else '📉'
+                events.append(f'{emoji} 浮盈变化: {prev_upl_pct:.1f}% → {upl_pct:.1f}% ({upl_diff:+.1f}%)')
+
+    return events
+
+def monitor():
+    state = load_state()
+    state = cleanup_state(state)
+    today = datetime.datetime.now().strftime('%Y-%m-%d')
+
+    # 1. 新币扫描 (每次挑前 2, 池子最多保留 6)
+    new_coin_picks = []
+    if NEW_COIN_AUTO_WATCH:
+        new_coin_picks = get_new_swap_symbols()
+        if new_coin_picks and NEW_COIN_PUSH_TO_QQ:
+            curr_pick_syms = sorted([p['sym'] for p in new_coin_picks])
+            # 看本次挑的与上次是否变化 (变化才推)
+            prev_picks = state.get('_new_coin_picks', [])
+            if prev_picks != curr_pick_syms:
+                msg = f"🆕 新币扫描 (30 天内新上市, vol 前 {NEW_COIN_PICKS}):\n\n"
+                for p in new_coin_picks:
+                    days_ago = (datetime.datetime.utcnow().timestamp() - p['listTime']/1000) / 86400
+                    msg += f"📊 {p['sym']}: 24h vol ${p['vol24h']/1e6:.1f}M | 上线 {days_ago:.1f} 天前\n"
+                msg += f"\n💡 已自动加入监控池 (上限 {NEW_COIN_POOL_MAX} 个)"
+                print(f"📤 推 QQ: 新币扫描 ({len(new_coin_picks)} 个)")
+                push_qq(msg)
+            state['_new_coin_picks'] = curr_pick_syms
+
+    # 2. 管理"新币候选池" — 上限 6, 超过删最旧的
+    # 池子结构: {'sym': 'XXX', 'added_at': ts, 'vol24h': vol}
+    new_coin_pool = state.get('_new_coin_pool', [])  # 按 added_at 升序 (oldest first)
+    new_pick_data = [{'sym': p['sym'], 'added_at': datetime.datetime.utcnow().timestamp(), 'vol24h': p['vol24h']} for p in new_coin_picks]
+    curr_syms = set([p['sym'] for p in new_pick_data])
+
+    # 加本次新挑的 (注意去重)
+    for p in new_pick_data:
+        if not any(x['sym'] == p['sym'] for x in new_coin_pool):
+            new_coin_pool.append(p)
+    # 删掉不在本次名单的超过 30 天或失流动性的
+    # (虽然我们只添, 但已经加入的币可能下架, 这里只做"超限裁剪")
+
+    # 超限裁剪: 按 added_at 升序, 删最早的 (保留最新的 NEW_COIN_POOL_MAX 个)
+    if len(new_coin_pool) > NEW_COIN_POOL_MAX:
+        # 按 added_at 升序排序
+        new_coin_pool.sort(key=lambda x: x['added_at'])
+        removed = new_coin_pool[:len(new_coin_pool) - NEW_COIN_POOL_MAX]
+        new_coin_pool = new_coin_pool[len(new_coin_pool) - NEW_COIN_POOL_MAX:]
+        msg = f"🗑️ 新币池超限 (>{NEW_COIN_POOL_MAX}), 移除: {[r['sym'] for r in removed]}"
+        print(msg)
+        if NEW_COIN_PUSH_TO_QQ:
+            push_qq(msg)
+
+    state['_new_coin_pool'] = new_coin_pool
+    new_coin_syms = [p['sym'] for p in new_coin_pool]
+
+    # 合并币种池: 默认主流币 + 实际持仓 + 新币池 (全部)
+    syms_to_monitor = list(DEFAULT_SYMBOLS)
+    if AUTO_INCLUDE_HOLDINGS:
+        held = get_held_symbols()
+        for s in held:
+            if s not in syms_to_monitor:
+                syms_to_monitor.append(s)
+    for s in new_coin_syms:
+        if s not in syms_to_monitor:
+            syms_to_monitor.append(s)
+    # 加进 SYMBOL_SPECS (用户后续可调整参数)
+    for sym in syms_to_monitor:
+        if sym not in SYMBOL_SPECS:
+            SYMBOL_SPECS[sym] = {
+                'ct_val': 1.0, 'leverage': 10, 't_qty': 1.0, 'min_sz': 0.01
+            }
+            print(f"📌 新增监控: {sym} (使用默认参数)")
+
+    # 拉所有币种的当前状态
+    syms_to_check = []
+    for sym in syms_to_monitor:
+        try:
+            pos_qty, avg_px, upl = get_position(sym)
+            price = get_ticker(sym)
+            if not price:
+                continue
+            syms_to_check.append((sym, pos_qty, avg_px, upl, price))
+        except Exception as e:
+            print(f"⚠️ {sym} 数据获取失败: {e}")
+
+    # === 变化检测 ===
+    any_change = False
+    # 先看是否需要做T (但先不成交), 收集 making_trade 列表, 用于 check_changes dedup
+    doing_trade = set()
+    pending_actions = {}  # sym -> (action, level_name, traded_levels_now, atr_levels, levels)
+
+    for sym, pos_qty, avg_px, upl, price in syms_to_check:
+        levels = {}
+        # 容错: 当 abs(pos_qty) > 0.01 才算真实持仓, 避免 OKX 浮点残值触发
+        has_position = abs(pos_qty) > 0.01
+        if has_position:
+            atr_levels = calc_levels_from_atr(sym)
+            if atr_levels:
+                levels = {**atr_levels, **SYMBOL_SPECS[sym]}
+
+        # 检查是否触及价位 (不执行)
+        # 用户原话 2026-07-15: 加减仓和平仓不一样, 要看持仓方向
+        # - 触及支撑位 (buy1/buy2, 价格跌到这):
+        #   - 多仓 → 加仓顺势 (低成本买入)
+        #   - 空仓 → 平仓获利 (回补)
+        # - 触及阻力位 (sell1/sell2, 价格涨到这):
+        #   - 多仓 → 平仓获利 (高抛)
+        #   - 空仓 → 加仓顺势 (顺势加空)
+        if has_position and levels:
+            state_key = f"{sym}_{today}"
+            traded_levels = state.get(state_key, [])
+            t_qty = levels.get('t_qty', 0.05)
+            threshold = 0.003
+            action = None
+            level_name = None
+            is_short = pos_qty < 0  # 空仓
+
+            # 支撑位触及: buy1/buy2
+            if abs(price - levels['buy2']) / price < threshold and 'buy2' not in traded_levels:
+                level_name = 'buy2'
+                action = 'buy' if is_short else 'buy'  # 都是 buy (空=平, 多=加)
+            elif abs(price - levels['buy1']) / price < threshold and 'buy1' not in traded_levels:
+                level_name = 'buy1'
+                action = 'buy' if is_short else 'buy'
+            # 阻力位触及: sell1/sell2
+            elif abs(price - levels['sell1']) / price < threshold and 'sell1' not in traded_levels:
+                level_name = 'sell1'
+                action = 'sell' if is_short else 'sell'  # 都是 sell (空=加, 多=平)
+            elif abs(price - levels['sell2']) / price < threshold and 'sell2' not in traded_levels:
+                level_name = 'sell2'
+                action = 'sell' if is_short else 'sell'
+            if action:
+                pending_actions[sym] = {
+                    'action': action,
+                    'level_name': level_name,
+                    'traded_levels': traded_levels,
+                    'levels': levels,
+                    'price': price,
+                    't_qty': t_qty,
+                }
+
+        # 变化检测 — 跳过即将做T的 (避免重复推)
+        events = check_changes(sym, price, pos_qty, avg_px, upl, levels, state,
+                                skip_for=set(pending_actions.keys()))
+        if events:
+            any_change = True
+            level_info = ''
+            if levels:
+                level_info = f'\n📊 关键位: buy1={levels.get("buy1","-")} buy2={levels.get("buy2","-")} sell1={levels.get("sell1","-")} sell2={levels.get("sell2","-")}'
+            msg = f"🔔 {sym} 变化提醒\n\n💰 价格: ${price:.2f}\n📦 持仓: {pos_qty:.2f}张\n" + "\n".join(events) + level_info
+            print(f"📤 推 QQ: {sym} 变化")
+            push_qq(msg)
+
+        # 更新 state
+        state[f'{sym}_prev_pos'] = pos_qty
+        if avg_px > 0 and has_position:
+            leverage = SYMBOL_SPECS.get(sym, {}).get('leverage', 25)
+            pos_sign = 1 if pos_qty > 0 else -1
+            state[f'{sym}_prev_upl_pct'] = (price - avg_px) / avg_px * 100 * leverage * pos_sign
+        else:
+            state[f'{sym}_prev_upl_pct'] = None
+
+    # === 做T 执行 ===
+    for sym, action_info in pending_actions.items():
+        action = action_info['action']
+        level_name = action_info['level_name']
+        levels = action_info['levels']
+        t_qty = action_info['t_qty']
+        price = action_info['price']
+        traded_levels = action_info['traded_levels']
+
+        doing_trade.add(sym)
+        avail = get_balance()
+        pos_qty, avg_price, upl = get_position(sym)
+
+        if action == 'buy':
+            margin_needed = levels['ct_val'] * price * t_qty / levels['leverage']
+            if avail < margin_needed:
+                print(f"⚠️ {sym} 余额不足 (需要 {margin_needed:.2f}, 可用 {avail:.2f})")
+                continue
+            # buy: 空仓=平仓 (reduceOnly), 多仓=加仓
+            reduce_only = pos_qty < 0
+            result = execute_trade(sym, 'buy', t_qty, reduce_only=reduce_only)
+        else:
+            # sell: 多仓=平仓 (reduceOnly), 空仓=加空
+            if pos_qty > 0 and abs(pos_qty) < t_qty:
+                print(f"⚠️ {sym} 多仓持仓不足")
+                continue
+            reduce_only = pos_qty > 0
+            result = execute_trade(sym, 'sell', t_qty, reduce_only=reduce_only)
+
+        if result.get('code') == '0':
+            traded_levels.append(level_name)
+            state[f"{sym}_{today}"] = traded_levels
+            state[f'{sym}_trade_at'] = datetime.datetime.utcnow().timestamp()
+            save_state(state)
+
+            # 文案根据 pos 方向区分 (用户原话 2026-07-15: "做空时 buy2 触发应该是平仓不是低吸")
+            if action == 'buy':
+                emoji = '🟢回补平仓' if pos_qty < 0 else '🟢低吸加仓'
+            else:  # sell
+                emoji = '🔴高抛平仓' if pos_qty > 0 else '🔴做空加仓'
+            msg = f"✅ 做T自动执行 v2.3\n\n{emoji} {sym} {t_qty}张 @ ${price:.2f}\n级别: {levels[level_name]}（{level_name}）\nATR: ${levels['atr']:.2f}\n\n"
+
+            time.sleep(1)
+            new_pos, new_avg, new_upl = get_position(sym)
+            new_avail = get_balance()
+            msg += f"📊 持仓: {new_pos:.2f}张 @ ${new_avg:.2f}\n💰 可用: ${new_avail:.2f}\n💹 浮盈: ${new_upl:.2f}"
+
+            print(f"📤 推 QQ: {sym} 做T成功")
+            push_qq(msg)
+            print(f"✅ {sym} {action} {level_name}")
+        else:
+            err_msg = f"❌ {sym} {action} {level_name} 失败: {result.get('msg', 'unknown')}"
+            print(err_msg)
+            push_qq(err_msg)
+
+
+    # 静默模式 (没任何变化)
+    save_state(state)
+    if not any_change and not pending_actions:
+        print("💤 静默: 无持仓, 无变化")
+    elif not any_change:
+        print("💤 静默: 有持仓但无价格变化/触及关键位")
+
+if __name__ == '__main__':
+    monitor()

intraday-trading/scripts/hk_intraday_cli.py

@@ -0,0 +1,279 @@
+#!/usr/bin/env python3
+"""港股日内交易监控+自动下单 - CLI 路径"""
+import os, sys, json, time
+from datetime import datetime
+
+# 强制 CLI 路径走 .com 海外域 (避免 602315)
+os.environ['LONGBRIDGE_HTTP_URL'] = 'https://openapi.longbridge.com'
+os.environ['LONGBRIDGE_REGION'] = 'ap'
+os.environ['LONGBRIDGE_TRADE_ENABLED'] = 'true'
+
+# 替换 longport 模块为 CLI helper (Python SDK 走 cn 域会 602315)
+sys.path.insert(0, '/home/openclaw/.hermes/scripts')
+import longbridge_cli_helper as _helper
+_fake_longport = type(sys)('longport')
+_fake_longport.openapi = _helper
+sys.modules['longport'] = _fake_longport
+sys.modules['longport.openapi'] = _helper
+from longport import openapi  # 现在 openapi 实际是 helper
+
+# 剩余代码跟原版一致
+config = {}
+with open(os.path.expanduser('~/.bashrc'), 'r') as f:
+    for line in f:
+        if line.startswith('export LONGPORT_'):
+            key, value = line.strip().split('=', 1)
+            config[key.replace('export ', '')] = value
+
+os.environ['LONGPORT_APP_KEY'] = config.get('LONGPORT_APP_KEY', '')
+os.environ['LONGPORT_APP_SECRET'] = config.get('LONGPORT_APP_SECRET', '')
+os.environ['LONGPORT_ACCESS_TOKEN'] = config.get('LONGPORT_ACCESS_TOKEN', '')
+
+ctx = openapi.QuoteContext(config=None)
+
+# === 余额 + 持仓 ===
+bals = openapi.account_balance()
+hkd_cash = 0
+usd_cash = 0
+if bals:
+    for b in bals:
+        cur = str(b.currency).upper()
+        cash = float(getattr(b, 'cash_available', 0) or 0)
+        if cash <= 0:
+            cash = float(getattr(b, 'buy_power', 0) or 0)
+        if 'USD' in cur:
+            usd_cash += cash
+        elif 'HKD' in cur:
+            hkd_cash += cash
+print(f"💰 HKD cash: {hkd_cash:.0f} | USD cash: {usd_cash:.2f}")
+print(f"💰 单笔仓位 (HKD): {hkd_cash*0.25:.0f} | (USD): {usd_cash*0.25:.2f}")
+
+# 持仓
+held_symbols = set()
+positions = openapi.stock_positions()
+for ch in positions.channels:
+    for p in ch.positions:
+        held_symbols.add(p.symbol)
+        print(f"  持仓: {p.symbol} {p.quantity}股 @ {p.cost_price}")
+
+# === 读取盘前候选 ===
+screen_file = os.path.expanduser('~/.hermes/skills/trading/quant-factor-mining/artifacts/hk_intraday_latest.json')
+if not os.path.exists(screen_file):
+    print("❌ 未找到盘前筛选结果")
+    sys.exit(1)
+
+with open(screen_file) as f:
+    screen = json.load(f)
+
+# 取 TOP 3
+candidates = [r for r in screen.get('results', [])[:3]]
+print(f"\n🎯 监控标的:")
+for c in candidates:
+    print(f"  {c['ticker']}: 评分 {c['score']:.1f} | ADR {c['avg_adr']:.2f}%")
+
+# === 读取入场记录 ===
+entry_file = os.path.expanduser('~/.hermes/trading/hk_intraday_entries.json')
+entries = {}
+if os.path.exists(entry_file):
+    try:
+        entries = json.load(open(entry_file))
+    except:
+        entries = {}
+
+# === 遍历每个候选, 检查入场/出场信号 ===
+for c in candidates:
+    ticker = c['ticker']
+    try:
+        q = ctx.quote([ticker])[0]
+        current = float(q.last_done)
+    except Exception as e:
+        print(f"⏳ {ticker}: 行情获取失败: {e}")
+        continue
+
+    # 简化版信号: 价格突破 SMA5 且 SMA5 > SMA10 → 入场
+    try:
+        cs = ctx.candlesticks(ticker, openapi.Period.Day, 30, openapi.AdjustType.ForwardAdjust)
+        closes = [float(c2.close) for c2 in cs]
+        sma5 = sum(closes[-5:]) / 5
+        sma10 = sum(closes[-10:]) / 10
+    except Exception as e:
+        print(f"⏳ {ticker}: K线失败: {e}")
+        continue
+
+    if ticker in held_symbols:
+        print(f"⏳ {ticker}: 已有持仓,跳过入场检查 | 现价 {current:.2f}")
+        continue
+
+    # 如果已有日内入场记录, 也跳过(防止重复下单)
+    if ticker in entries:
+        # 检查出场信号
+        entry = entries[ticker]
+        e_shares = entry.get('shares', 0)
+        e_order_id = entry.get('order_id', '')
+
+        if not e_order_id:
+            print(f"⚠️ {ticker}: 有入场记录但无订单ID, 跳过")
+            continue
+
+        if current <= entry['stop_loss']:
+            print(f"\n🛑 {ticker} 触发止损! {current:.2f} <= {entry['stop_loss']}")
+            try:
+                openapi.submit_order(
+                    symbol=ticker, order_type=openapi.OrderType.MO,
+                    side=openapi.OrderSide.Sell,
+                    submitted_quantity=e_shares,
+                    time_in_force=openapi.TimeInForceType.Day,
+                )
+                print(f"  ✅ 止损平仓: 卖 {e_shares}股 @ 市价")
+                del entries[ticker]
+                with open(entry_file, 'w') as f:
+                    json.dump(entries, f, indent=2)
+            except Exception as e:
+                print(f"  ❌ 平仓失败: {e}")
+        elif current >= entry['take_profit']:
+            print(f"\n🎯 {ticker} 触发止盈! {current:.2f} >= {entry['take_profit']}")
+            try:
+                openapi.submit_order(
+                    symbol=ticker, order_type=openapi.OrderType.MO,
+                    side=openapi.OrderSide.Sell,
+                    submitted_quantity=e_shares,
+                    time_in_force=openapi.TimeInForceType.Day,
+                )
+                print(f"  ✅ 止盈平仓: 卖 {e_shares}股 @ 市价")
+                del entries[ticker]
+                with open(entry_file, 'w') as f:
+                    json.dump(entries, f, indent=2)
+            except Exception as e:
+                print(f"  ❌ 平仓失败: {e}")
+        else:
+            print(f"⏳ {ticker}: 已入场,持仓中 | 现价 {current:.2f} | 止损 {entry['stop_loss']} | 止盈 {entry['take_profit']}")
+        continue
+
+    # === 入场信号 ===
+    if current > sma5 > sma10 and current > closes[-2]:
+        # 计算仓位: 20% cash (按标的货币), 按 lot_size 取整
+        price = round(current, 2)
+        # 港股 lot_size 可能 100/200/500/1000/2000 (ticker 依赖), 美股=1
+        lot_size = openapi.get_lot_size(ticker) if hasattr(openapi, 'get_lot_size') else 100
+        # 选对应货币的 cash
+        cash = hkd_cash  # 港股账户默认 HKD
+        target_value = cash * 0.20
+        shares = int(target_value / price / lot_size) * lot_size
+        if shares < lot_size:
+            print(f"⏳ {ticker}: 信号但余额不足 (需要{lot_size}股 @ {price})")
+            continue
+
+        stop_loss = round(price * 0.985, 2)
+        take_profit = round(price * 1.025, 2)
+
+        # 调整下单价格到合法范围 (港股 9 档保护规则)
+        adjusted_price = openapi.adjust_price_for_order(ticker, price, 'buy') if hasattr(openapi, 'adjust_price_for_order') else price
+        if abs(adjusted_price - price) > 0.05:
+            print(f"  ⚠️ 价格调整: {price} → {adjusted_price} (盘口约束)")
+
+        # 基于 adjusted_price 重新算止损止盈
+        stop_loss = round(adjusted_price * 0.985, 2)
+        take_profit = round(adjusted_price * 1.025, 2)
+
+        print(f"\n🔔 {ticker} 入场信号!")
+        print(f"  方向: 做多 | 现价 {current:.2f} | SMA5 {sma5:.2f}")
+        print(f"  止损: {stop_loss} | 止盈: {take_profit} | 股数: {shares}")
+
+        # 自动下单
+        try:
+            resp = openapi.submit_order(
+                symbol=ticker, order_type=openapi.OrderType.LO,
+                side=openapi.OrderSide.Buy,
+                submitted_quantity=shares,
+                time_in_force=openapi.TimeInForceType.Day,
+                submitted_price=adjusted_price,
+            )
+            order_id = resp.order_id
+            print(f"  ⏳ 已提交: {order_id}")
+
+            # 反查 status (700 RMB 教训)
+            import time as _t
+            status = 'Unknown'
+            detail = None
+            for retry in range(3):
+                _t.sleep(0.5)
+                try:
+                    detail = openapi.order_detail(order_id)
+                    status = str(detail.status).split('.')[-1] if detail else 'Unknown'
+                    if status not in ('New', 'NotReported'):
+                        break
+                except Exception:
+                    continue
+
+            if status == 'Filled':
+                print(f"  ✅ 成交: {order_id}")
+            elif status == 'Rejected':
+                print(f"  ❌ 被拒: {order_id} | 跳过")
+                continue
+            elif status == 'Canceled':
+                print(f"  🚫 已撤: {order_id}")
+                continue
+            else:
+                print(f"  ⚠️ 已挂单未成交: {order_id} (status={status})")
+
+            # 记录 (用 adjusted_price 作为 entry_price)
+            entries[ticker] = {
+                'side': 'buy',
+                'entry_price': adjusted_price,
+                'stop_loss': stop_loss,
+                'take_profit': take_profit,
+                'shares': shares,
+                'order_id': order_id,
+                'time': datetime.now().isoformat(),
+            }
+            os.makedirs(os.path.dirname(entry_file), exist_ok=True)
+            with open(entry_file, 'w') as f:
+                json.dump(entries, f, indent=2)
+        except Exception as e:
+            print(f"  ❌ 下单失败: {e}")
+
+    elif ticker in entries:
+        # === 出场信号 ===
+        entry = entries[ticker]
+        e_shares = entry.get('shares', 0)
+        e_order_id = entry.get('order_id', '')
+
+        if not e_order_id:
+            print(f"⚠️ {ticker}: 无订单ID, 跳过")
+            continue
+
+        if current <= entry['stop_loss']:
+            print(f"🛑 {ticker} 止损! {current:.2f} <= {entry['stop_loss']}")
+            try:
+                openapi.submit_order(
+                    symbol=ticker, order_type=openapi.OrderType.MO,
+                    side=openapi.OrderSide.Sell,
+                    submitted_quantity=e_shares,
+                    time_in_force=openapi.TimeInForceType.Day,
+                )
+                print(f"  ✅ 止损平仓: 卖 {e_shares}股")
+                del entries[ticker]
+                with open(entry_file, 'w') as f:
+                    json.dump(entries, f, indent=2)
+            except Exception as e:
+                print(f"  ❌ 平仓失败: {e}")
+
+        elif current >= entry['take_profit']:
+            print(f"🎯 {ticker} 止盈! {current:.2f} >= {entry['take_profit']}")
+            try:
+                openapi.submit_order(
+                    symbol=ticker, order_type=openapi.OrderType.MO,
+                    side=openapi.OrderSide.Sell,
+                    submitted_quantity=e_shares,
+                    time_in_force=openapi.TimeInForceType.Day,
+                )
+                print(f"  ✅ 止盈平仓: 卖 {e_shares}股")
+                del entries[ticker]
+                with open(entry_file, 'w') as f:
+                    json.dump(entries, f, indent=2)
+            except Exception as e:
+                print(f"  ❌ 平仓失败: {e}")
+    else:
+        print(f"⏳ {ticker}: 等待信号 | 现价 {current:.2f} | SMA5 {sma5:.2f} | SMA10 {sma10:.2f}")
+
+print("\n=== 完成 ===")

intraday-trading/scripts/hk_intraday_cli_runner.sh

@@ -0,0 +1,31 @@
+#!/bin/bash
+# 港股日内交易 CLI runner
+# 用法: bash hk_intraday_cli_runner.sh
+# 走 ~/.local/bin/longbridge CLI (不用 Python SDK), 走 openapi.longbridge.com (AWS 海外)
+set -e
+
+LOG=/tmp/hk_intraday_cli.log
+SIGNAL_FILE=/tmp/hk_intraday_signals.json
+
+echo "=== HK 日内 CLI runner @ $(date) ===" > $LOG
+
+# 0. 确保 hosts 干净 (cn 域名指向 AWS 海外 IP 是有毒的, 真实 DNS 解析即可)
+# 真实 DNS: openapi.longbridge.com → 18.163.160.163 (AWS 香港)
+
+# 1. 用 proxychains + CLI 查持仓 + 余额 + 信号生成
+LONGBRIDGE_REGION=ap LONGBRIDGE_TRADE_ENABLED=true \
+  proxychains4 -f ~/.proxychains/proxychains.conf \
+  ~/.local/bin/longbridge --profile lb_real balance 2>&1 | tee -a $LOG
+
+# 2. 列出当前订单
+LONGBRIDGE_REGION=ap \
+  proxychains4 -f ~/.proxychains/proxychains.conf \
+  ~/.local/bin/longbridge --profile lb_real orders 2>&1 | tee -a $LOG
+
+# 3. 给个示例: 如果有持仓, 显示; 没持仓, 给信号
+# (实际信号生成+下单逻辑,需要跟 intraday-trading skill 的 strategy 对接)
+# 先跑通 CLI 路径, 信号生成后期补
+
+echo "" >> $LOG
+echo "=== CLI runner 完成 @ $(date) ===" >> $LOG
+cat $LOG

intraday-trading/scripts/us_intraday_cli.py

@@ -0,0 +1,279 @@
+#!/usr/bin/env python3
+"""港股日内交易监控+自动下单 - CLI 路径"""
+import os, sys, json, time
+from datetime import datetime
+
+# 强制 CLI 路径走 .com 海外域 (避免 602315)
+os.environ['LONGBRIDGE_HTTP_URL'] = 'https://openapi.longbridge.com'
+os.environ['LONGBRIDGE_REGION'] = 'ap'
+os.environ['LONGBRIDGE_TRADE_ENABLED'] = 'true'
+
+# 替换 longport 模块为 CLI helper (Python SDK 走 cn 域会 602315)
+sys.path.insert(0, '/home/openclaw/.hermes/scripts')
+import longbridge_cli_helper as _helper
+_fake_longport = type(sys)('longport')
+_fake_longport.openapi = _helper
+sys.modules['longport'] = _fake_longport
+sys.modules['longport.openapi'] = _helper
+from longport import openapi  # 现在 openapi 实际是 helper
+
+# 剩余代码跟原版一致
+config = {}
+with open(os.path.expanduser('~/.bashrc'), 'r') as f:
+    for line in f:
+        if line.startswith('export LONGPORT_'):
+            key, value = line.strip().split('=', 1)
+            config[key.replace('export ', '')] = value
+
+os.environ['LONGPORT_APP_KEY'] = config.get('LONGPORT_APP_KEY', '')
+os.environ['LONGPORT_APP_SECRET'] = config.get('LONGPORT_APP_SECRET', '')
+os.environ['LONGPORT_ACCESS_TOKEN'] = config.get('LONGPORT_ACCESS_TOKEN', '')
+
+ctx = openapi.QuoteContext(config=None)
+
+# === 余额 + 持仓 ===
+bals = openapi.account_balance()
+# 分离 HKD / USD cash (不能用 buy_power,要用 cash)
+hkd_cash = 0
+usd_cash = 0
+if bals:
+    for b in bals:
+        cur = str(b.currency).upper()
+        # 优先用 cash_available, fallback 用 buy_power
+        cash = float(getattr(b, 'cash_available', 0) or 0)
+        if cash <= 0:
+            cash = float(getattr(b, 'buy_power', 0) or 0)
+        if 'USD' in cur:
+            usd_cash += cash
+        elif 'HKD' in cur:
+            hkd_cash += cash
+        print(f"  [{cur}] cash: {cash:.0f}")
+print(f"\n💰 HKD cash: {hkd_cash:.0f} | USD cash: {usd_cash:.2f}")
+print(f"💰 单笔仓位 (HKD): {hkd_cash*0.25:.0f} | (USD): {usd_cash*0.25:.2f}")
+
+# 持仓
+held_symbols = set()
+positions = openapi.stock_positions()
+for ch in positions.channels:
+    for p in ch.positions:
+        held_symbols.add(p.symbol)
+        print(f"  持仓: {p.symbol} {p.quantity}股 @ {p.cost_price}")
+
+# === 读取盘前候选 ===
+screen_file = os.path.expanduser('~/.hermes/skills/trading/quant-factor-mining/artifacts/us_intraday_latest.json')
+if not os.path.exists(screen_file):
+    print("❌ 未找到盘前筛选结果")
+    sys.exit(1)
+
+with open(screen_file) as f:
+    screen = json.load(f)
+
+# 取 TOP 3
+candidates = [r for r in screen.get('results', [])[:3]]
+print(f"\n🎯 监控标的:")
+for c in candidates:
+    print(f"  {c['ticker']}: 评分 {c['score']:.1f} | ADR {c['avg_adr']:.2f}%")
+
+# === 读取入场记录 ===
+entry_file = os.path.expanduser('~/.hermes/trading/us_intraday_entries.json')
+entries = {}
+if os.path.exists(entry_file):
+    try:
+        entries = json.load(open(entry_file))
+    except:
+        entries = {}
+
+# === 遍历每个候选, 检查入场/出场信号 ===
+for c in candidates:
+    ticker = c['ticker']
+    try:
+        q = ctx.quote([ticker])[0]
+        current = float(q.last_done)
+    except Exception as e:
+        print(f"⏳ {ticker}: 行情获取失败: {e}")
+        continue
+
+    # 简化版信号: 价格突破 SMA5 且 SMA5 > SMA10 → 入场
+    try:
+        cs = ctx.candlesticks(ticker, openapi.Period.Day, 30, openapi.AdjustType.ForwardAdjust)
+        closes = [float(c2.close) for c2 in cs]
+        sma5 = sum(closes[-5:]) / 5
+        sma10 = sum(closes[-10:]) / 10
+    except Exception as e:
+        print(f"⏳ {ticker}: K线失败: {e}")
+        continue
+
+    if ticker in held_symbols:
+        print(f"⏳ {ticker}: 已有持仓,跳过入场检查 | 现价 {current:.2f}")
+        continue
+
+    # 如果已有日内入场记录, 也跳过(防止重复下单)
+    if ticker in entries:
+        # 检查出场信号
+        entry = entries[ticker]
+        e_shares = entry.get('shares', 0)
+        e_order_id = entry.get('order_id', '')
+
+        if not e_order_id:
+            print(f"⚠️ {ticker}: 有入场记录但无订单ID, 跳过")
+            continue
+
+        if current <= entry['stop_loss']:
+            print(f"\n🛑 {ticker} 触发止损! {current:.2f} <= {entry['stop_loss']}")
+            try:
+                openapi.submit_order(
+                    symbol=ticker, order_type=openapi.OrderType.MO,
+                    side=openapi.OrderSide.Sell,
+                    submitted_quantity=e_shares,
+                    time_in_force=openapi.TimeInForceType.Day,
+                )
+                print(f"  ✅ 止损平仓: 卖 {e_shares}股 @ 市价")
+                del entries[ticker]
+                with open(entry_file, 'w') as f:
+                    json.dump(entries, f, indent=2)
+            except Exception as e:
+                print(f"  ❌ 平仓失败: {e}")
+        elif current >= entry['take_profit']:
+            print(f"\n🎯 {ticker} 触发止盈! {current:.2f} >= {entry['take_profit']}")
+            try:
+                openapi.submit_order(
+                    symbol=ticker, order_type=openapi.OrderType.MO,
+                    side=openapi.OrderSide.Sell,
+                    submitted_quantity=e_shares,
+                    time_in_force=openapi.TimeInForceType.Day,
+                )
+                print(f"  ✅ 止盈平仓: 卖 {e_shares}股 @ 市价")
+                del entries[ticker]
+                with open(entry_file, 'w') as f:
+                    json.dump(entries, f, indent=2)
+            except Exception as e:
+                print(f"  ❌ 平仓失败: {e}")
+        else:
+            print(f"⏳ {ticker}: 已入场,持仓中 | 现价 {current:.2f} | 止损 {entry['stop_loss']} | 止盈 {entry['take_profit']}")
+        continue
+
+    # === 入场信号 ===
+    if current > sma5 > sma10 and current > closes[-2]:
+        # 计算仓位: 20% cash (按标的货币), 按 lot_size 取整
+        price = round(current, 2)
+        # 美股 lot_size=1, 港股=100/200/500/1000/2000
+        lot_size = 1 if ticker.endswith('.US') else 100
+        # 选对应货币的 cash
+        if ticker.endswith('.US'):
+            cash = usd_cash
+        else:
+            cash = hkd_cash
+        target_value = cash * 0.20  # 20% 现金
+        shares = int(target_value / price / lot_size) * lot_size
+        if shares < lot_size:
+            print(f"⏳ {ticker}: 信号但余额不足 (需要{lot_size}股 @ {price})")
+            continue
+
+        stop_loss = round(price * 0.985, 2)
+        take_profit = round(price * 1.025, 2)
+
+        print(f"\n🔔 {ticker} 入场信号!")
+        print(f"  方向: 做多 | 现价 {current:.2f} | SMA5 {sma5:.2f}")
+        print(f"  止损: {stop_loss} | 止盈: {take_profit} | 股数: {shares}")
+
+        # 自动下单
+        try:
+            resp = openapi.submit_order(
+                symbol=ticker, order_type=openapi.OrderType.LO,
+                side=openapi.OrderSide.Buy,
+                submitted_quantity=shares,
+                time_in_force=openapi.TimeInForceType.Day,
+                submitted_price=price,
+            )
+            order_id = resp.order_id
+            print(f"  ⏳ 已提交: {order_id}")
+
+            # 反查 status (700 RMB 教训: order_id ≠ 成交)
+            import time as _t
+            status = 'Unknown'
+            for retry in range(3):
+                _t.sleep(0.5)
+                try:
+                    detail = openapi.order_detail(order_id)
+                    status = str(detail.status).split('.')[-1] if detail else 'Unknown'
+                    if status not in ('New', 'NotReported'):
+                        break
+                except Exception:
+                    continue
+
+            if status == 'Filled':
+                print(f"  ✅ 成交: {order_id}")
+                exec_price = float(detail.executed_price or price)
+                exec_qty = int(detail.executed_quantity or shares)
+            elif status == 'Rejected':
+                print(f"  ❌ 被拒: {order_id} | status={status} | 跳过")
+                continue
+            elif status == 'Canceled':
+                print(f"  🚫 已撤: {order_id}")
+                continue
+            else:  # New / NotReported (港股日单未成交)
+                print(f"  ⚠️ 已挂单未成交: {order_id} (status={status})")
+                exec_price = price
+                exec_qty = shares
+
+            # 记录
+            entries[ticker] = {
+                'side': 'buy',
+                'entry_price': price,
+                'stop_loss': stop_loss,
+                'take_profit': take_profit,
+                'shares': shares,
+                'order_id': order_id,
+                'time': datetime.now().isoformat(),
+            }
+            os.makedirs(os.path.dirname(entry_file), exist_ok=True)
+            with open(entry_file, 'w') as f:
+                json.dump(entries, f, indent=2)
+        except Exception as e:
+            print(f"  ❌ 下单失败: {e}")
+
+    elif ticker in entries:
+        # === 出场信号 ===
+        entry = entries[ticker]
+        e_shares = entry.get('shares', 0)
+        e_order_id = entry.get('order_id', '')
+
+        if not e_order_id:
+            print(f"⚠️ {ticker}: 无订单ID, 跳过")
+            continue
+
+        if current <= entry['stop_loss']:
+            print(f"🛑 {ticker} 止损! {current:.2f} <= {entry['stop_loss']}")
+            try:
+                openapi.submit_order(
+                    symbol=ticker, order_type=openapi.OrderType.MO,
+                    side=openapi.OrderSide.Sell,
+                    submitted_quantity=e_shares,
+                    time_in_force=openapi.TimeInForceType.Day,
+                )
+                print(f"  ✅ 止损平仓: 卖 {e_shares}股")
+                del entries[ticker]
+                with open(entry_file, 'w') as f:
+                    json.dump(entries, f, indent=2)
+            except Exception as e:
+                print(f"  ❌ 平仓失败: {e}")
+
+        elif current >= entry['take_profit']:
+            print(f"🎯 {ticker} 止盈! {current:.2f} >= {entry['take_profit']}")
+            try:
+                openapi.submit_order(
+                    symbol=ticker, order_type=openapi.OrderType.MO,
+                    side=openapi.OrderSide.Sell,
+                    submitted_quantity=e_shares,
+                    time_in_force=openapi.TimeInForceType.Day,
+                )
+                print(f"  ✅ 止盈平仓: 卖 {e_shares}股")
+                del entries[ticker]
+                with open(entry_file, 'w') as f:
+                    json.dump(entries, f, indent=2)
+            except Exception as e:
+                print(f"  ❌ 平仓失败: {e}")
+    else:
+        print(f"⏳ {ticker}: 等待信号 | 现价 {current:.2f} | SMA5 {sma5:.2f} | SMA10 {sma10:.2f}")
+
+print("\n=== 完成 ===")

strategy-management/scripts/backtest.py

@@ -0,0 +1,509 @@
+"""
+backtest.py - 通用策略回测工具
+支持 4 个策略:
+  - rsi2_revert: RSI(2) < 10 做多, RSI(2) > 90 做空, MA50 趋势过滤
+  - vwap_revert: 价格偏离 VWAP > 1.5σ 回归
+  - early_bird: 开盘 30 min 涨跌幅 + 量 > 1.5× → 顺势
+  - turtle_breakout: 20 周期突破 + 10 周期反向出场
+  - sma_breakout: SMA5 > SMA10 + 价格突破前高 (现有默认)
+
+用法:
+  python3 backtest.py --strategy rsi2_revert --symbol NVDA
+  python3 backtest.py --strategy turtle_breakout --symbol 0700.HK --days 60
+
+默认 K 线 = 1h, Yahoo Finance 数据源 (美股 NVDA/AAPL 等, 港股 0700.HK 等)
+"""
+
+import argparse
+import json
+import os
+import sys
+from datetime import datetime, timedelta
+from typing import List, Dict, Optional, Tuple
+
+# 本地依赖
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+from strategy_registry import get_strategy, list_strategies
+from indicators import sma, ema, rsi, atr, vwap, vwap_std, donchian_breakout
+
+
+# ============== K 线获取 ==============
+
+def fetch_klines_longbridge(symbol: str, days: int = 30, interval: str = '1h') -> Optional[Dict]:
+    """LongPort CLI 数据源 (通过 proxychains4 + Clash 香港出口).
+    支持美股/港股. Yahoo Finance 国内 VPS 经常 rate limit, 长桥更稳.
+    """
+    # 港股 ticker Yahoo 是 4 位数字带前导 0, 长桥是 0700.HK
+    # 长桥 K 线是 period 内全部, 倒序. 我们重新排序为时间正序.
+    bar_map = {
+        '1m': '1m', '5m': '5m', '15m': '15m', '30m': '30m',
+        '60m': '60m', '1h': '60m', 'day': 'day', '1d': 'day', 'week': 'week',
+    }
+    bar = bar_map.get(interval, '60m')
+
+    env = os.environ.copy()
+    env['LONGBRIDGE_HTTP_URL'] = 'https://openapi.longbridge.com'
+    env['LONGBRIDGE_REGION'] = 'ap'
+    env['LONGBRIDGE_TRADE_ENABLED'] = 'true'
+    cmd = [
+        'proxychains4', '-f', os.path.expanduser('~/.proxychains/proxychains.conf'),
+        '/home/openclaw/.local/bin/longbridge', '--profile', 'lb_real',
+        'candlesticks', symbol, bar, '--json',
+    ]
+    try:
+        r = subprocess.run(cmd, capture_output=True, text=True, timeout=30, env=env)
+        if r.returncode != 0:
+            return None
+        import re
+        # 找 JSON 起止位置
+        json_match = re.search(r'\[\s*\{', r.stdout)
+        if not json_match:
+            return None
+        json_text = '[' + r.stdout[json_match.start()+1:]
+        data = json.loads(json_text)
+        if not data:
+            return None
+        # 倒序 → 正序
+        data = list(reversed(data))
+        return {
+            'opens': [k['open'] for k in data],
+            'highs': [k['high'] for k in data],
+            'lows':  [k['low']  for k in data],
+            'closes':[k['close'] for k in data],
+            'volumes':[k.get('volume', 0) or 0 for k in data],
+            'timestamps':[k.get('timestamp', '') for k in data],
+        }
+    except Exception as e:
+        print(f"⚠️ {symbol} 长桥 K线拉取失败: {e}")
+        return None
+
+
+import subprocess  # 在 fetch_klines_longbridge 后 import
+
+def fetch_klines_yahoo(symbol: str, days: int = 30, interval: str = '1h') -> Optional[Dict]:
+    """Yahoo Finance fallback (国内 VPS 可能 rate limit)."""
+    try:
+        import yfinance as yf
+        yahoo_sym = symbol.replace('.US', '').replace('.HK', '.HK')
+        df = yf.download(tickers=yahoo_sym, period=f'{days}d',
+                          interval=interval, progress=False, auto_adjust=True)
+        if df is None or len(df) < 10:
+            return None
+        if hasattr(df.columns, 'names') and len(df.columns.names) > 1:
+            df.columns = df.columns.droplevel(0)
+        expected = ['Open', 'High', 'Low', 'Close', 'Volume']
+        if not all(col in df.columns for col in expected):
+            return None
+        return {
+            'opens': df['Open'].tolist(),
+            'highs': df['High'].tolist(),
+            'lows': df['Low'].tolist(),
+            'closes': df['Close'].tolist(),
+            'volumes': df['Volume'].fillna(0).tolist(),
+            'timestamps': df.index.tolist(),
+        }
+    except Exception as e:
+        print(f"⚠️ yahoo {symbol} fallback 失败: {e}")
+        return None
+
+
+def fetch_klines(symbol: str, days: int = 30, interval: str = '1h') -> Optional[Dict]:
+    """统一入口: 长桥 → Yahoo fallback."""
+    klines = fetch_klines_longbridge(symbol, days, interval)
+    if klines:
+        return klines
+    print("⚠️ 长桥拉数据失败, fallback Yahoo...")
+    return fetch_klines_yahoo(symbol, days, interval)
+
+
+# ============== 策略信号生成 ==============
+
+def signal_rsi2_revert(klines: Dict, params) -> List[Dict]:
+    """RSI(2) 超卖反弹信号"""
+    closes = klines['closes']
+    opens = klines['opens']
+    atr_vals = atr(klines['highs'], klines['lows'], closes, 14)
+    rsi2 = rsi(closes, params.rsi_period)
+    ma50 = sma(closes, params.rsi2_ma_filter)
+
+    signals = []
+    cooldown = 0
+    # 跳过前面 (50 = MA50 + ATR14 + RSI2 都需要预热)
+    start = max(50, params.rsi2_ma_filter + 1)
+    for i in range(start, len(closes)):
+        cooldown -= 1
+        if cooldown > 0:
+            continue
+        if rsi2[i] is None or ma50[i] is None or atr_vals[i] is None:
+            continue
+
+        # 入场
+        side = None
+        if rsi2[i] < params.rsi_buy_threshold and closes[i] > ma50[i] and opens[i] > closes[i-1]:
+            side = 'long'
+        elif rsi2[i] > params.rsi_sell_threshold and closes[i] < ma50[i] and opens[i] < closes[i-1]:
+            side = 'short'
+
+        if not side:
+            continue
+
+        entry = closes[i]
+        sl_price = entry - atr_vals[i] * params.sl_atr_multi if side == 'long' else entry + atr_vals[i] * params.sl_atr_multi
+        tp_price = entry + atr_vals[i] * params.tp_atr_multi if side == 'long' else entry - atr_vals[i] * params.tp_atr_multi
+
+        signals.append({
+            'i': i, 'ts': klines['timestamps'][i], 'side': side,
+            'entry': entry, 'sl': sl_price, 'tp': tp_price,
+            'atr': atr_vals[i],
+        })
+        cooldown = params.cooldown_bars
+    return signals
+
+
+def signal_sma_breakout(klines: Dict, params) -> List[Dict]:
+    """SMA 突破 (现有默认, 用来对比)"""
+    closes = klines['closes']
+    opens = klines['opens']
+    highs = klines['highs']
+    lows = klines['lows']
+    atr_vals = atr(highs, lows, closes, 14)
+
+    sma5 = sma(closes, 5)
+    sma10 = sma(closes, 10)
+
+    signals = []
+    cooldown = 0
+    for i in range(15, len(closes)):
+        cooldown -= 1
+        if cooldown > 0:
+            continue
+        # SMA 突破: SMA5 > SMA10 + 突破前高
+        if sma5[i] is None or sma10[i] is None or atr_vals[i] is None:
+            continue
+        if sma5[i] > sma10[i] and closes[i] > closes[i-1] and closes[i] > opens[i]:
+            entry = closes[i]
+            side = 'long'
+            sl_price = entry - atr_vals[i] * params.sl_atr_multi
+            tp_price = entry + atr_vals[i] * params.tp_atr_multi
+
+            signals.append({
+                'i': i, 'ts': klines['timestamps'][i], 'side': side,
+                'entry': entry, 'sl': sl_price, 'tp': tp_price,
+                'atr': atr_vals[i],
+            })
+            cooldown = params.cooldown_bars
+    return signals
+
+
+def signal_vwap_revert(klines: Dict, params) -> List[Dict]:
+    """VWAP 回归"""
+    closes = klines['closes']
+    highs = klines['highs']
+    lows = klines['lows']
+    volumes = klines['volumes']
+    atr_vals = atr(highs, lows, closes, 14)
+    vwaps = vwap(closes, volumes)
+    vwap_stds = vwap_std(closes, volumes, 20)
+
+    signals = []
+    cooldown = 0
+    for i in range(30, len(closes)):
+        cooldown -= 1
+        if cooldown > 0:
+            continue
+        if vwaps[i] is None or vwap_stds[i] is None or atr_vals[i] is None:
+            continue
+
+        deviation = closes[i] - vwaps[i]
+        std_dev = vwap_stds[i]
+
+        # 量需 > 5日均量 × 1.2 (用前 120 bar 作 5日)
+        if i < 121:
+            continue
+        avg_vol = sum(volumes[i-119:i+1]) / 120
+        if volumes[i] < avg_vol * params.require_volume_multi:
+            continue
+
+        side = None
+        if deviation < -std_dev * params.vwap_deviation_std:
+            side = 'long'
+        elif deviation > std_dev * params.vwap_deviation_std:
+            side = 'short'
+        if not side:
+            continue
+
+        entry = closes[i]
+        # SL = entry ± 1σ (基于 VWAP std)
+        sl_dist = std_dev * params.vwap_sl_std_multi
+        sl_price = entry - sl_dist if side == 'long' else entry + sl_dist
+        tp_price = vwaps[i] * (1 - params.vwap_tp_touch_pct/100) if side == 'long' else vwaps[i] * (1 + params.vwap_tp_touch_pct/100)
+
+        signals.append({
+            'i': i, 'ts': klines['timestamps'][i], 'side': side,
+            'entry': entry, 'sl': sl_price, 'tp': tp_price,
+            'atr': atr_vals[i],
+        })
+        cooldown = params.cooldown_bars
+    return signals
+
+
+def signal_turtle_breakout(klines: Dict, params) -> List[Dict]:
+    """海龟通道突破"""
+    closes = klines['closes']
+    highs = klines['highs']
+    lows = klines['lows']
+    atr_vals = atr(highs, lows, closes, 14)
+
+    hh, ll = donchian_breakout(highs, lows, params.turtle_channel_period)
+    hh_exit, ll_exit = donchian_breakout(highs, lows, params.turtle_exit_channel_period)
+
+    signals = []
+    cooldown = 0
+    for i in range(params.turtle_channel_period, len(closes)):
+        cooldown -= 1
+        if cooldown > 0:
+            continue
+        if hh[i-1] is None or ll[i-1] is None or atr_vals[i] is None:
+            continue
+
+        side = None
+        if closes[i] > hh[i-1]:
+            side = 'long'
+        elif closes[i] < ll[i-1]:
+            side = 'short'
+        if not side:
+            continue
+
+        entry = closes[i]
+        sl_price = entry - atr_vals[i] * params.sl_atr_multi if side == 'long' else entry + atr_vals[i] * params.sl_atr_multi
+        tp_price = entry + atr_vals[i] * params.tp_atr_multi if side == 'long' else entry - atr_vals[i] * params.tp_atr_multi
+
+        signals.append({
+            'i': i, 'ts': klines['timestamps'][i], 'side': side,
+            'entry': entry, 'sl': sl_price, 'tp': tp_price,
+            'atr': atr_vals[i],
+        })
+        cooldown = params.cooldown_bars
+    return signals
+
+
+def signal_early_bird(klines: Dict, params) -> List[Dict]:
+    """早盘动量: 假设 K 线是 5min, 开盘 30 min = 6 根 K 线
+    看开盘 6 根 K 线的累计涨跌幅 + 量能
+    """
+    closes = klines['closes']
+    opens = klines['opens']
+    highs = klines['highs']
+    lows = klines['lows']
+    volumes = klines['volumes']
+    atr_vals = atr(highs, lows, closes, 14)
+
+    signals = []
+    cooldown = 0
+    # 简化: 找每根 K 线, 看 close vs 开盘 (5 bar 前) 的涨跌幅
+    for i in range(20, len(closes) - params.max_hold_bars - 6):
+        cooldown -= 1
+        if cooldown > 0:
+            continue
+
+        # 取开盘 6 根 (5min × 6 = 30 min) 的累计涨跌
+        open_price = opens[i - 5]  # 6 根前开 (第 1 根的开)
+        window_high = max(highs[i-5:i+1])
+        window_low = min(lows[i-5:i+1])
+        window_vol = sum(volumes[i-5:i+1])
+
+        # 跳空
+        gap_pct = abs(opens[i] - closes[i-6]) / closes[i-6] * 100
+        if gap_pct < params.early_bird_min_move_pct:
+            continue
+
+        # 量能
+        if i < 121:
+            continue
+        avg_vol = sum(volumes[i-119:i+1]) / 120
+        if window_vol < avg_vol * params.early_bird_volume_multi:
+            continue
+
+        # 顺势
+        side = 'long' if closes[i] > opens[i] else 'short'
+        entry = closes[i]
+        sl_price = entry - atr_vals[i] * params.sl_atr_multi if side == 'long' else entry + atr_vals[i] * params.sl_atr_multi
+        tp_price = entry + atr_vals[i] * params.tp_atr_multi if side == 'long' else entry - atr_vals[i] * params.tp_atr_multi
+
+        signals.append({
+            'i': i, 'ts': klines['timestamps'][i], 'side': side,
+            'entry': entry, 'sl': sl_price, 'tp': tp_price,
+            'atr': atr_vals[i],
+        })
+        cooldown = params.cooldown_bars
+    return signals
+
+
+SIGNAL_FNS = {
+    'rsi2_revert': signal_rsi2_revert,
+    'vwap_revert': signal_vwap_revert,
+    'early_bird': signal_early_bird,
+    'turtle_breakout': signal_turtle_breakout,
+    'sma_breakout': signal_sma_breakout,
+}
+
+
+# ============== 回测执行 ==============
+
+def run_backtest(klines: Dict, signals: List[Dict], symbol: str, strategy_name: str) -> Dict:
+    """根据信号做回测.
+    入场: 信号触发 (i 时刻 close)
+    出场: SL / TP / max_hold_bars 三选一先到
+    """
+    closes = klines['closes']
+    highs = klines['highs']
+    lows = klines['lows']
+    trades = []
+    in_position = None  # {i_entry, side, entry, sl, tp}
+
+    # 简化: 同时只能持 1 仓 (同向多仓不重入)
+    for i in range(50, len(closes)):
+        # 1) 平仓检查
+        if in_position is not None:
+            exit_price = None
+            exit_reason = None
+            i_entry = in_position['i_entry']
+            side = in_position['side']
+            sl = in_position['sl']
+            tp = in_position['tp']
+
+            # SL hit (用 high/low 检查)
+            if side == 'long' and lows[i] <= sl:
+                exit_price = sl
+                exit_reason = 'SL'
+            elif side == 'short' and highs[i] >= sl:
+                exit_price = sl
+                exit_reason = 'SL'
+            elif side == 'long' and highs[i] >= tp:
+                exit_price = tp
+                exit_reason = 'TP'
+            elif side == 'short' and lows[i] <= tp:
+                exit_price = tp
+                exit_reason = 'TP'
+            elif i - i_entry >= 78:  # 默认 max_hold_bars
+                exit_price = closes[i]
+                exit_reason = 'EXPIRE'
+
+            if exit_price is not None:
+                pnl_pct = (exit_price - in_position['entry']) / in_position['entry'] * 100
+                if side == 'short':
+                    pnl_pct = -pnl_pct
+                trades.append({
+                    'side': side, 'entry': in_position['entry'], 'exit': exit_price,
+                    'pnl_pct': pnl_pct, 'reason': exit_reason,
+                    'i_entry': i_entry, 'i_exit': i,
+                })
+                in_position = None
+
+        # 2) 入场检查
+        for sig in signals:
+            if sig['i'] == i and in_position is None:
+                in_position = {
+                    'i_entry': i, 'side': sig['side'],
+                    'entry': sig['entry'], 'sl': sig['sl'], 'tp': sig['tp'],
+                }
+                break
+
+    # 计算统计
+    if not trades:
+        return {
+            'strategy': strategy_name, 'symbol': symbol,
+            'signals': len(signals), 'trades': 0,
+            'win_rate': 0, 'avg_pnl': 0, 'total_pnl': 0,
+            'max_drawdown': 0, 'sharpe': 0,
+        }
+
+    wins = [t for t in trades if t['pnl_pct'] > 0]
+    losses = [t for t in trades if t['pnl_pct'] <= 0]
+    pnls = [t['pnl_pct'] for t in trades]
+    win_rate = len(wins) / len(trades) * 100
+
+    # 最大回撤 (累计收益曲线的 max drawdown)
+    cum = [0]
+    for p in pnls:
+        cum.append(cum[-1] + p)
+    peak = cum[0]
+    max_dd = 0
+    for v in cum:
+        if v > peak:
+            peak = v
+        max_dd = min(max_dd, v - peak)
+
+    # Sharpe 简化: 平均 / std
+    avg = sum(pnls) / len(pnls)
+    var = sum((x - avg)**2 for x in pnls) / len(pnls)
+    std = var ** 0.5
+    sharpe = avg / std if std > 0 else 0
+
+    return {
+        'strategy': strategy_name, 'symbol': symbol,
+        'signals': len(signals), 'trades': len(trades),
+        'wins': len(wins), 'losses': len(losses),
+        'win_rate': round(win_rate, 1),
+        'avg_pnl': round(avg, 3),
+        'best': round(max(pnls), 2),
+        'worst': round(min(pnls), 2),
+        'total_pnl': round(sum(pnls), 2),
+        'max_drawdown': round(max_dd, 2),
+        'sharpe': round(sharpe, 2),
+        'trades_detail': trades[:10],
+    }
+
+
+def fmt(result: Dict) -> str:
+    """格式化回测报告"""
+    lines = []
+    lines.append(f"📊 {result['strategy']} {result['symbol']}")
+    lines.append(f"  信号: {result['signals']} | 成交: {result['trades']} (W={result.get('wins',0)}, L={result.get('losses',0)})")
+    if result['trades'] == 0:
+        lines.append(f"  ⚠️ 无成交 (参数过严或市场平静)")
+        return '\n'.join(lines)
+    lines.append(f"  胜率: {result['win_rate']}%")
+    lines.append(f"  平均盈亏: {result['avg_pnl']:+.3f}% | 最大盈: {result['best']:+.2f}% / 最大亏: {result['worst']:+.2f}%")
+    lines.append(f"  累计盈亏: {result['total_pnl']:+.2f}% | 最大回撤: {result['max_drawdown']:+.2f}%")
+    lines.append(f"  Sharpe: {result['sharpe']}")
+    if result['trades'] > 0:
+        lines.append(f"  最近 5 笔: {result['trades_detail'][:5]}")
+    return '\n'.join(lines)
+
+
+# ============== 主入口 ==============
+
+def main():
+    parser = argparse.ArgumentParser(description='策略回测 - v0.1')
+    parser.add_argument('--strategy', choices=list(SIGNAL_FNS.keys()), required=True)
+    parser.add_argument('--symbol', default='NVDA', help='Yahoo Finance ticker, e.g. NVDA / 0700.HK')
+    parser.add_argument('--days', type=int, default=30)
+    parser.add_argument('--interval', default='1h', help='K 线周期: 1h / 30m / 15m / 5m')
+    args = parser.parse_args()
+
+    print(f"⏳ 拉 {args.symbol} 最近 {args.days} 天 {args.interval} K线...")
+    klines = fetch_klines(args.symbol, days=args.days, interval=args.interval)
+    if not klines:
+        print(f"❌ {args.symbol} 数据拉取失败")
+        sys.exit(1)
+    n = len(klines['closes'])
+    print(f"✅ {n} 根 K 线")
+
+    params = get_strategy(args.strategy)
+    print(f"\n🎯 策略: {args.strategy}")
+    print(f"📋 {params.name} (sl_atr={params.sl_atr_multi}, tp_atr={params.tp_atr_multi}, position={params.position_pct}%)")
+
+    signals = SIGNAL_FNS[args.strategy](klines, params)
+    print(f"🔍 信号数: {len(signals)}")
+
+    result = run_backtest(klines, signals, args.symbol, args.strategy)
+    print("\n" + fmt(result))
+
+    # 输出 JSON
+    result.pop('trades_detail', None)
+    print(f"\n📊 JSON: {json.dumps(result, default=str, ensure_ascii=False)}")
+
+
+if __name__ == '__main__':
+    main()