hmo
2af2e93408
- mr_scanner.py: v_mr 6条件筛选(bias60<-10%/RSI<42/ret60<-15%/mom20<5%/额<1500万/rsi_delta>=2) - 股票池=stock_daily distinct code,与回测run_mr_backtest完全同口径(含ST,不含退市/301新创业板) - 数据源腾讯qfq日K: 因子与回测零偏差(实测bias60/ret60/mom20 Δ=0.000000) - regime门控: trend_down/choppy才扫; 幂等保护: 当天已有候选则跳过 - market_watch.py: 接入mr_scanner调用(每30分钟调度,幂等防重复) - 首轮实盘验证: 2026-07-31 trend_down市命中3只(*ST四通/*ST冀凯/*ST椰岛),全为回测验证过的ST股
366 lines
14 KiB
Python
366 lines
14 KiB
Python
#!/usr/bin/env python3
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"""mr_scanner.py — v_mr 均值回复策略实盘扫描器
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回测侧 v_mr（strategy_lab.run_mr_backtest / mr_engine_v2.py）已 10y 全市场验证
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（21690笔 / WR 53.6% / avg +3.34%），但实盘此前没有该策略的扫描机制 ——
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本脚本把 v_mr 的入场筛选原样搬到实盘，按日扫描全市场深超跌小盘票。
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与回测完全一致的入场条件（mr_cfg v2 定稿）：
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1. bias60 < -10% : 收盘价在 MA60 下方超 10%（单边，无下限）
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2. RSI14 < 42 : 超卖
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3. ret60 < -15% : 60 日跌幅超 15%（单边，无下限）
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4. mom20 < 5% : 20 日低动量（还没启动反弹）
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5. amount20 < 1500万 : 小盘（20 日均成交额，百万元）
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6. rsi_delta >= 2 : RSI 5 日回升 ≥2（止跌回升确认）
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出场建议（exit_cfg v2）：tp=+18% / sl=-8% / max_hold=25 交易日
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市场门控（2026-08-02 新增）：
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- 只读 market_regime 表，regime 为 trend_down 或 choppy 时启用扫描
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（v_mr 主战场：下跌趋势 + 震荡市；趋势市让位 v_next4）
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- trend_up 时跳过（v_next4 追涨主战场，不扫超跌）
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数据源：Sina 240 分钟线（日K），datalen=120（覆盖 MA60 + 60日回看 + RSI 收敛）
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指标算法：与 backtest_framework.py 完全一致（内联，零偏差）
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输出：candidates 表（sector='v_mr'），与 accumulation_scanner 同 UPSERT 模式
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用法：
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python3 mr_scanner.py # 完整扫描（regime 门控）
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python3 mr_scanner.py --force # 忽略 regime 门控强制扫描
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python3 mr_scanner.py --top N # 输出前 N 只（默认 10）
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"""
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import sys, json, urllib.request, re, time, sqlite3
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from pathlib import Path
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from datetime import datetime
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DB_PATH = Path("/home/hmo/MoFin/data/mofin.db")
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UA = "Mozilla/5.0"
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# ── v_mr 参数（与 mr_engine_v2.py 注册的 mr_cfg/exit_cfg 完全一致）──
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MR_CFG = {
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"bias_max": -10, # MA60 下方超 10%（单边无下限）
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"rsi_max": 42, # RSI 超卖
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"ret_max": -15, # 60 日跌超 15%（单边无下限）
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"mom20_max": 5, # 20 日低动量
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"amount_max": 15, # 百万元 = 1500 万日成交额
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"rsi_delta_min": 2, # RSI 5 日回升 ≥2
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"mkt_mode": "any", # 实盘由 regime 门控替代（trend_down/choppy 才扫）
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}
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EXIT_CFG = {"tp_pct": 0.18, "sl_pct": 0.08, "max_hold_days": 25}
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TOP_N = 10
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# ── 技术指标（与 backtest_framework.py 完全同算法）──
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def calc_ma(series, n):
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result = []
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for i in range(len(series)):
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if i < n - 1:
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result.append(None)
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else:
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result.append(sum(series[i - n + 1:i + 1]) / n)
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return result
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def calc_rsi(series, n=14):
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deltas = [series[i] - series[i - 1] for i in range(1, len(series))]
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gains = [d if d > 0 else 0 for d in deltas]
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losses = [-d if d < 0 else 0 for d in deltas]
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result = [None] * (n + 1)
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avg_gain = sum(gains[:n]) / n
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avg_loss = sum(losses[:n]) / n
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if avg_loss == 0:
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result.append(100)
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else:
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rs = avg_gain / avg_loss
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result.append(100 - 100 / (1 + rs))
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for i in range(n, len(gains)):
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avg_gain = (avg_gain * (n - 1) + gains[i]) / n
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avg_loss = (avg_loss * (n - 1) + losses[i]) / n
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if avg_loss == 0:
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result.append(100)
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else:
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rs = avg_gain / avg_loss
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result.append(100 - 100 / (1 + rs))
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while len(result) < len(series):
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result.insert(0, None)
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return result[:len(series)]
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# ── 数据获取 ──
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def fetch_tx_klines(code, datalen=120):
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"""腾讯前复权日K（qfq），与 stock_daily 数据零偏差，返回 [{date,open,close,high,low,volume}]"""
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raw = str(code).strip()
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if raw.startswith(("6", "9")):
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prefix = "sh"
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elif raw.startswith(("0", "3")):
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prefix = "sz"
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else:
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return None
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url = f"http://ifzq.gtimg.cn/appstock/app/fqkline/get?param={prefix}{raw},day,,,{datalen},qfq"
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try:
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req = urllib.request.Request(url, headers={"User-Agent": UA})
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opener = urllib.request.build_opener(urllib.request.ProxyHandler({}))
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with opener.open(req, timeout=8) as r:
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text = r.read().decode("utf-8", errors="replace").strip()
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data = json.loads(text)
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node = data.get("data", {}).get(f"{prefix}{raw}", {})
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bars = node.get("qfqday") or node.get("day") or []
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if not bars or len(bars) < 70:
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return None
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result = []
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for b in bars:
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if len(b) < 6:
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continue
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result.append({
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"date": b[0][:10],
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"open": float(b[1]),
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"close": float(b[2]),
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"high": float(b[3]),
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"low": float(b[4]),
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"volume": float(b[5]), # 手
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})
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return result
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except Exception:
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return None
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# 兼容别名（供外部引用）
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fetch_sina_klines = fetch_tx_klines
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def get_stock_pool():
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"""待扫描股票池：stock_daily 的 distinct code（与回测 run_mr_backtest 完全同口径）
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回测股票池 = SELECT DISTINCT sd.code FROM stock_daily（4266只，含300/688，
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不含301新创业板——数据源未收录）。实盘扫描用同一口径，保证 v_mr
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信号覆盖的股票都是回测验证过的。
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"""
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conn = sqlite3.connect(str(DB_PATH), timeout=5)
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try:
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existing = set()
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for r in conn.execute("SELECT code FROM holding_strategies WHERE status='active'"):
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existing.add(str(r[0]))
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for r in conn.execute("SELECT code FROM holdings WHERE is_active=1"):
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existing.add(str(r[0]))
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# 与回测完全一致：stock_daily 有K线的股票（回测 universe='a' 排除5位港股）
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all_stocks = [str(r[0]) for r in
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conn.execute("SELECT DISTINCT code FROM stock_daily").fetchall()]
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finally:
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conn.close()
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# 只留 A 股（6位数字），排除港股（5位0开头）—— 与回测 is_hk_code 逻辑一致
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a_stocks = [c for c in all_stocks if len(c) == 6 and c.isdigit()]
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return a_stocks, existing
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def load_regime():
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"""读取 market_regime 最新状态"""
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try:
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conn = sqlite3.connect(str(DB_PATH), timeout=5)
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row = conn.execute(
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"SELECT date, above_ma20, adx, regime FROM market_regime "
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"ORDER BY date DESC LIMIT 1").fetchone()
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conn.close()
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if row:
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return {"date": row[0], "above_ma20": bool(row[1]), "adx": row[2], "regime": row[3]}
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except Exception:
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pass
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return None
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# ── v_mr 筛选（与回测 run_mr_backtest 的 6 条件一致）──
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def check_vmr(klines):
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"""对单只股票做 v_mr 入场筛选。命中返回信号 dict，否则 None。
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klines 为升序日K（Sina 返回顺序）。"""
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if not klines or len(klines) < 70:
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return None
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closes = [k["close"] for k in klines]
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highs = [k["high"] for k in klines]
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lows = [k["low"] for k in klines]
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i = len(klines) - 1 # 最新一日
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close = closes[i]
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if close <= 0:
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return None
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ma60 = calc_ma(closes, 60)
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rsi_all = calc_rsi(closes)
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rsi = rsi_all[i] if i < len(rsi_all) else None
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m60 = ma60[i]
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if not m60 or m60 <= 0 or rsi is None:
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return None
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# 1. MA60 下方超跌（单边）
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bias60 = (close - m60) / m60 * 100
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if bias60 > MR_CFG["bias_max"]: # 只拦上沿（-10%），无下限
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return None
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# 2. RSI 超卖
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if rsi > MR_CFG["rsi_max"]:
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return None
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# 3. 60 日跌幅（单边）
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prev60 = closes[i - 60] if i >= 60 else 0
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prev_ret60 = (close - prev60) / prev60 * 100 if prev60 > 0 else 0
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if prev_ret60 > MR_CFG["ret_max"]: # 只拦上沿（-15%），无下限
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return None
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# 4. 20 日低动量
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prev20 = closes[i - 20] if i >= 20 else 0
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mom20 = (close - prev20) / prev20 * 100 if prev20 > 0 else 0
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if mom20 > MR_CFG["mom20_max"]:
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return None
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# 5. 小盘（20 日均成交额，百万元）
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# 腾讯日K volume 单位=手（×100股），成交额=手×100×均价
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amt20 = []
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for k in klines[max(0, i - 19):i + 1]:
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avg_px = (k["high"] + k["low"] + k["close"]) / 3
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amt20.append(k["volume"] * 100 * avg_px) # 元
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amt_valid = [a for a in amt20 if a and a > 0]
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amount_ma20 = sum(amt_valid) / len(amt_valid) if amt_valid else 0
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amount_ma20_m = amount_ma20 / 1e6 # 元 → 百万元
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if MR_CFG["amount_max"] is not None and amount_ma20_m > MR_CFG["amount_max"]:
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return None
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# 6. RSI 5 日回升（止跌确认）
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rsi0 = rsi_all[i - 5] if i >= 5 else None
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rsi_delta = (rsi - rsi0) if rsi0 is not None else 0
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if rsi_delta < MR_CFG["rsi_delta_min"]:
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return None
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# 命中 → 出场建议（与回测 exit_cfg 一致）
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tp_pct = EXIT_CFG["tp_pct"]
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sl_pct = EXIT_CFG["sl_pct"]
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target = round(close * (1 + tp_pct), 2)
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stop = round(close * (1 - sl_pct), 2)
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return {
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"price": close,
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"bias60": round(bias60, 2),
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"rsi": round(rsi, 2),
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"prev_ret60": round(prev_ret60, 2),
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"mom20": round(mom20, 2),
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"amount_ma20": round(amount_ma20_m, 2),
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"rsi_delta": round(rsi_delta, 2),
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"target": target,
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"stop_loss": stop,
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"date": klines[i]["date"],
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}
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def main():
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force = "--force" in sys.argv
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top_n = TOP_N
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if "--top" in sys.argv:
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try:
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top_n = int(sys.argv[sys.argv.index("--top") + 1])
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except (ValueError, IndexError):
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pass
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print(f"[MR] {datetime.now().strftime('%H:%M')} v_mr 实盘扫描开始", flush=True)
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# ── regime 门控 ──
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regime = load_regime()
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if regime:
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rg = regime["regime"]
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print(f" 市场阶段: {regime['date']} → {rg} (adx={regime['adx']})", flush=True)
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if rg not in ("trend_down", "choppy") and not force:
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print(f" ⏭ {rg} 非 v_mr 主战场（trend_down/choppy 才扫），跳过", flush=True)
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return
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if rg not in ("trend_down", "choppy"):
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print(f" ⚠ --force 强制扫描（当前 {rg}）", flush=True)
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else:
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print(" ⚠ market_regime 不可用，默认执行扫描（v_mr 全市场可用）", flush=True)
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# ── 幂等检查：当天已扫过 v_mr 则跳过（避免 30 分钟调度重复全扫描）──
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import sqlite3 as _sq
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_conn = _sq.connect(str(DB_PATH), timeout=5)
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try:
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_today = datetime.now().strftime("%Y-%m-%d")
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_n = _conn.execute(
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"SELECT COUNT(*) FROM candidates WHERE sector='v_mr' AND substr(created_at,1,10)=?",
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(_today,)).fetchone()[0]
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except Exception:
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_n = 0
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_conn.close()
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if _n > 0 and not force:
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print(f" 已有 {_n} 条今日 v_mr 候选，跳过重复扫描（--force 可强制）", flush=True)
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return
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# ── 股票池 ──
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all_stocks, existing = get_stock_pool()
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print(f" 股票池: {len(all_stocks)}只A股, 已有策略: {len(existing)}只", flush=True)
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if not all_stocks:
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print(" ⚠ stocks 表为空", flush=True)
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return
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# 并发拉日K（ThreadPool 8 并发，Sina 单只逐个拉）
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from concurrent.futures import ThreadPoolExecutor, as_completed
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pool = [c for c in all_stocks if c not in existing]
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found = []
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done = 0
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with ThreadPoolExecutor(max_workers=8) as ex:
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fut_map = {ex.submit(fetch_sina_klines, c): c for c in pool}
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for fut in as_completed(fut_map):
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code = fut_map[fut]
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done += 1
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klines = fut.result()
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if klines:
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sig = check_vmr(klines)
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if sig:
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found.append((code, sig))
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if done % 400 == 0:
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print(f" 已扫描 {done}/{len(pool)}", flush=True)
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print(f" 命中 v_mr 条件: {len(found)} 只", flush=True)
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# 排序：超跌越深越优先（bias60 越小越靠前）
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found.sort(key=lambda x: x[1]["bias60"])
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# ── 写 candidates 表（UPSERT，保留计算列）──
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conn = sqlite3.connect(str(DB_PATH), timeout=5)
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inserted = 0
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for code, sig in found[:top_n]:
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name = code
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try:
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r = conn.execute("SELECT name FROM stocks WHERE code=?", (code,)).fetchone()
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if r and r[0]:
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name = r[0]
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except Exception:
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pass
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price = sig["price"]
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entry_low = round(price * 0.97, 2)
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entry_high = round(price * 1.02, 2)
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sl = sig["stop_loss"]
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tp = sig["target"]
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reasons = (f"v_mr超跌(bias60={sig['bias60']}% rsi={sig['rsi']} "
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f"ret60={sig['prev_ret60']}% mom20={sig['mom20']}% "
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f"额{sig['amount_ma20']}M rsi_delta={sig['rsi_delta']})")
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# 检查是否已在 candidates 且未 promoted
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exists = conn.execute(
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"SELECT code FROM candidates WHERE code=? AND (promoted IS NULL OR promoted=0)",
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(code,)).fetchone()
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if exists:
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continue
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conn.execute(
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"INSERT INTO candidates (code, name, sector, reason, "
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"entry_range, stop_loss, target, created_at) "
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"VALUES (?,?,?,?,?,?,?,datetime('now','localtime')) "
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"ON CONFLICT(code) DO UPDATE SET "
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"name=excluded.name, sector=excluded.sector, reason=excluded.reason, "
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"entry_range=excluded.entry_range, stop_loss=excluded.stop_loss, target=excluded.target",
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(code, name, "v_mr", reasons,
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f"{entry_low}~{entry_high}", sl, tp))
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inserted += 1
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print(f" 🟢 {code} {name} 价{price} bias60={sig['bias60']}% "
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f"rsi={sig['rsi']} ret60={sig['prev_ret60']}% {reasons}", flush=True)
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conn.commit()
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conn.close()
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print(f" ✅ 新增 {inserted} 只 v_mr 候选（前 {top_n}）", flush=True)
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if __name__ == "__main__":
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main()
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