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因子逻辑
用成交量对数的日变化与日内收益率（收盘相对开盘）两者的截面排名，计算二者过去6日的时序相关系数后取反。值越大，表示放量与日内上涨越呈反向关系，即量价背离越明显。
因子公式
(-1 * CORR(RANK(DELTA(LOG(VOLUME), 1)), RANK(((CLOSE -OPEN) / OPEN)), 6))BigQuant SQL
SELECT date, instrument, if(volume=0, 0.000001, volume) AS _volume2, -1*m_corr(pct_rank_by(date, LOG(_volume2)-m_lag(LOG(_volume2), 1)), pct_rank_by(date, (close-open)/open), 6) AS _factor_temp, 1 * _factor_temp AS factorFROM cn_stock_bar1dORDER BY date, instrumentbq examples new strategies/multi_factor.py bqf_10101_strategy.py --name 'Alpha191 #1 选股' \ --set 'TABLES=["cn_stock_factors_alpha_191"]' --set 'FACTORS=["alpha_001"]' --set 'HOLD=30' \ --set 'EVERY=20' --set 'BENCHMARK="000300.SH"' --set 'START="2021-01-01"' \ --set 'END="2026-09-21"' \ && python bqf_10101_strategy.pySELECT date, instrument, alpha_001 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_10101"], "2021-01-01", "2026-09-21")report = factor.analyze( values, start_date="2021-01-01", end_date="2026-09-21", universe=("all", "hs300"), neutralize=(None, "size+industry"), depth="deep",)report.render()