125 lines
4.3 KiB
Python
125 lines
4.3 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""backfill_hk_regime.py — 港股温区历史回填（一次性脚本）
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背景（阶段3 港股接入）：market_regime 表刚加 market 维度，港股温区只有今天
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1 条，regime_tracker 的 K=5 滞回平滑需要足够历史。本脚本对 stock_daily 的
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hkHSI 全历史（2014 起，约 3000 条）逐日计算温区，写入 market_regime(market='hk')。
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算法：完全复用 market_regime.compute_regime 的判定逻辑（ma20/adx/roc → 三态），
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只是按日期逐日循环（compute_regime 只算最新一天）。
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用法：
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python3 backfill_hk_regime.py # 回填港股温区全历史
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python3 backfill_hk_regime.py --days 500 # 只回填最近 500 个交易日
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幂等：INSERT OR REPLACE（同日同市场覆盖），可重复执行。
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"""
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import sqlite3
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import sys
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from pathlib import Path
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_SCRIPT_DIR = Path(__file__).resolve().parent
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import sys as _sys
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_sys.path.insert(0, str(_SCRIPT_DIR))
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from market_regime import calc_ma, calc_trend_strength, calc_roc, ADX_TREND_MIN
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DB_PATH = Path("/home/hmo/MoFin/data/mofin.db")
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INDEX_HK = "hkHSI"
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LOOKBACK = 120 # 与 compute_regime 的 lookback_days 一致
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def classify(above_ma20, adx):
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"""与 market_regime.compute_regime 的 regime 分类完全一致"""
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if above_ma20 is True and adx is not None and adx >= ADX_TREND_MIN:
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return "trend_up"
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elif adx is not None and adx < ADX_TREND_MIN:
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return "choppy"
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else:
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return "trend_down"
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def main():
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days = None
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for a in sys.argv[1:]:
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if a.startswith("--days"):
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days = int(a.split("=")[-1] if "=" in a else sys.argv[sys.argv.index(a) + 1])
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conn = sqlite3.connect(str(DB_PATH), timeout=30)
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rows = conn.execute(
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"SELECT date, close, high, low FROM stock_daily WHERE code=? ORDER BY date ASC",
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(INDEX_HK,)
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).fetchall()
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if not rows or len(rows) < 30:
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print(f"{INDEX_HK} 数据不足（{len(rows)} 条），无法回填")
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return 1
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dates = [r[0] for r in rows]
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closes = [r[1] for r in rows]
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highs = [r[2] for r in rows]
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lows = [r[3] for r in rows]
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n = len(rows)
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if days:
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n = min(n, days)
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print(f"{INDEX_HK} 共 {len(rows)} 条（{dates[0]} ~ {dates[-1]}），回填最近 {n} 个交易日温区")
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# 逐日计算（i 从第 30 天起，窗口用前 LOOKBACK 天）
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written = 0
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start_i = max(30, n - days) if days else 30
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for i in range(start_i, n):
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# 取截至 i 的最近 LOOKBACK 天
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j0 = max(0, i - LOOKBACK + 1)
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c = closes[j0:i + 1]
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h = highs[j0:i + 1]
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l = lows[j0:i + 1]
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if len(c) < 30:
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continue
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ma20 = calc_ma(c, 20)
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trend = calc_trend_strength(h, l, c)
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roc = calc_roc(c)
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k = len(c) - 1
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close = c[k]
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m20 = ma20[k]
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above = (close > m20) if m20 else None
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slope = None
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if k >= 5 and ma20[k - 5] and ma20[k - 5] > 0 and m20:
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slope = round((m20 - ma20[k - 5]) / ma20[k - 5] * 100, 3)
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adx = trend[k] if k < len(trend) else None
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roc_v = roc[k] if k < len(roc) else None
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regime = classify(above, adx)
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conn.execute("""
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INSERT OR REPLACE INTO market_regime
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(date, market, above_ma20, ma20_slope, roc, adx, regime, close, created_at)
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VALUES (?, 'hk', ?, ?, ?, ?, ?, ?, CURRENT_TIMESTAMP)
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""", (
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dates[i],
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1 if above else 0,
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slope,
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round(roc_v, 3) if roc_v is not None else None,
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round(adx, 2) if adx is not None else None,
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regime,
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close,
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))
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written += 1
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if written % 500 == 0:
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conn.commit()
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print(f" 已回填 {written} 条（至 {dates[i]}）...")
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conn.commit()
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# 验证
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total = conn.execute(
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"SELECT COUNT(*), MIN(date), MAX(date) FROM market_regime WHERE market='hk'"
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).fetchone()
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dist = conn.execute(
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"SELECT regime, COUNT(*) FROM market_regime WHERE market='hk' GROUP BY regime"
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).fetchall()
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conn.close()
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print(f"\n回填完成：写入 {written} 条")
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print(f"market_regime 港股温区：共 {total[0]} 条，{total[1]} ~ {total[2]}")
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print(f"温区分布: {dict(dist)}")
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return 0
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if __name__ == "__main__":
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sys.exit(main())
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