import full eventflow project

backend/fastapi_app/services/market_moves_qfr.py

@@ -0,0 +1,108 @@
+import json
+import os
+from dataclasses import asdict, dataclass
+from typing import Any
+
+import pandas as pd
+
+
+@dataclass
+class Move:
+    symbol: str
+    trade_date: str
+    prev_trade_date: str
+    close: float
+    prev_close: float
+    ret_1d: float
+    vol_20d: float
+    z_1d: float
+
+
+def _read_one(rawdir: str, symbol: str) -> pd.DataFrame:
+    # QFR stores parquet as e.g. 510300SH.parquet / 159915SZ.parquet
+    fn = symbol.replace(".", "") + ".parquet"
+    p = os.path.join(rawdir, fn)
+    df = pd.read_parquet(p)
+    # Standardize
+    if "trade_date" not in df.columns or "close" not in df.columns:
+        raise RuntimeError(f"unexpected parquet schema for {symbol}: {df.columns.tolist()}")
+    df = df.sort_values("trade_date").reset_index(drop=True)
+    return df
+
+
+def _calc_move(df: pd.DataFrame, symbol: str, trade_date: str | None) -> Move | None:
+    if df.empty:
+        return None
+    # pick last available <= trade_date if given
+    if trade_date:
+        df2 = df[df["trade_date"] <= trade_date]
+        if df2.empty:
+            return None
+        df = df2
+
+    if len(df) < 2:
+        return None
+
+    # compute returns
+    close = df["close"].astype(float)
+    ret = close.pct_change()
+
+    i = len(df) - 1
+    prev_i = i - 1
+
+    td = str(df.iloc[i]["trade_date"])
+    ptd = str(df.iloc[prev_i]["trade_date"])
+
+    close_i = float(close.iloc[i])
+    prev_close_i = float(close.iloc[prev_i])
+    ret_1d = float(ret.iloc[i])
+
+    # vol over last 20 returns (excluding NaN)
+    vol_20 = float(ret.iloc[max(0, i - 20 + 1) : i + 1].std(skipna=True))
+    if not (vol_20 > 0):
+        vol_20 = 0.0
+    z = float(ret_1d / vol_20) if vol_20 > 0 else 0.0
+
+    return Move(
+        symbol=symbol,
+        trade_date=td,
+        prev_trade_date=ptd,
+        close=close_i,
+        prev_close=prev_close_i,
+        ret_1d=ret_1d,
+        vol_20d=vol_20,
+        z_1d=z,
+    )
+
+
+def main() -> None:
+    rawdir = os.environ.get("QFR_RAWDIR") or "/home/openclaw/projects/quant-factor-research/data/raw"
+    symbols = (os.environ.get("QFR_SYMBOLS") or "").strip()
+    trade_date = (os.environ.get("QFR_TRADE_DATE") or "").strip() or None
+
+    if not symbols:
+        raise SystemExit("QFR_SYMBOLS is required")
+
+    out: dict[str, Any] = {
+        "rawdir": rawdir,
+        "trade_date": trade_date,
+        "moves": [],
+        "errors": [],
+    }
+
+    for sym in [s.strip() for s in symbols.split(",") if s.strip()]:
+        try:
+            df = _read_one(rawdir, sym)
+            mv = _calc_move(df, sym, trade_date)
+            if mv is None:
+                out["errors"].append({"symbol": sym, "error": "no_data"})
+                continue
+            out["moves"].append(asdict(mv))
+        except Exception as e:
+            out["errors"].append({"symbol": sym, "error": str(e)})
+
+    print(json.dumps(out, ensure_ascii=True))
+
+
+if __name__ == "__main__":
+    main()