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因子逻辑
20日内下跌日的绝对收益与成交额之比的平均，类似Amihud非流动性指标的下跌版；值越大表示下跌时单位成交额对应的价格变动越大。
因子公式
SUMIF(ABS(CLOSE/DELAY(CLOSE,1)-1)/AMOUNT,20,CLOSE<DELAY(CLOSE,1))/COUNT(CLOSE<DELAY(CLOSE,1),20)BigQuant SQL
SELECT date, instrument, IF(close < m_lag(close,1), 1, 0) AS _a, IF(close < m_lag(close,1), 1, 0) AS _b, ABS(close / m_lag(close,1) - 1) / (amount / m_avg(amount,60)) AS _c, SUM(_c*_a) OVER (PARTITION BY instrument ORDER BY date ROWS BETWEEN 19 PRECEDING AND CURRENT ROW) AS _d, IF(SUM(_b) OVER (PARTITION BY instrument ORDER BY date ROWS BETWEEN 19 PRECEDING AND CURRENT ROW)=0, 0, SUM(_b) OVER (PARTITION BY instrument ORDER BY date ROWS BETWEEN 19 PRECEDING AND CURRENT ROW)) AS _e, _d / _e * 100 AS _factor_temp, -1 * _factor_temp AS factor,FROM cn_stock_bar1dORDER BY date, instrumentbq examples new strategies/multi_factor.py bqf_10353_strategy.py --name 'Alpha191 #144 选股' \ --set 'TABLES=["cn_stock_factors_alpha_191"]' --set 'FACTORS=["alpha_144"]' --set 'HOLD=30' \ --set 'EVERY=20' --set 'BENCHMARK="000300.SH"' --set 'START="2021-01-01"' \ --set 'END="2026-09-18"' \ && python bqf_10353_strategy.pySELECT date, instrument, alpha_144 FROM cn_stock_factors_alpha_191带入当前因子，在 Cowork 中继续研究。
from bigquant import factor
values = factor.values(["BQF_10353"], "2021-01-01", "2026-09-18")report = factor.analyze( values, start_date="2021-01-01", end_date="2026-09-18", universe=("all", "hs300"), neutralize=(None, "size+industry"), depth="deep",)report.render()