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backend/app/backtest/events.py

@@ -135,12 +135,16 @@ def _scan_batch(
     if not candle_rows:
         return trades
     bars = pd.DataFrame(
-        candle_rows, columns=["symbol", "ts", "open", "high", "low", "close"]
+        candle_rows, columns=["symbol", "ts", "open", "high", "low", "close", "volume", "turnover"]
     )
     for symbol, g in bars.groupby("symbol", sort=False):
         if len(g) < 30:
             continue
         g = g.reset_index(drop=True)
+        # pct_chg / amplitude 是派生列（candles 无现成涨跌幅/振幅）：按股内环比补算，
+        # 与选股引擎 _load_bars 同口径——否则「日涨跌幅/当日振幅」条件进事件回测直接 KeyError
+        g["pct_chg"] = g["close"].pct_change() * 100
+        g["amplitude"] = (g["high"] - g["low"]) / g["close"].shift(1) * 100
         ts_code_l = code_by_symbol[symbol]
         cache: dict = {"_families": set()}
         mask = _signal_mask(g, spec, cache)
@@ -243,7 +247,7 @@ async def run_event_backtest(
         code_by_symbol = {sym: code for code, sym in batch}
         candle_rows = (await session.execute(
             select(Candle.symbol, Candle.ts, Candle.open, Candle.high,
-                   Candle.low, Candle.close)
+                   Candle.low, Candle.close, Candle.volume, Candle.turnover)
             .where(and_(Candle.timeframe == "1d",
                         Candle.symbol.in_(symbols),
                         Candle.ts >= buffer_ts, Candle.ts <= end_ts))