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因子逻辑
计算成交量与 vwap 截面排名之间的5日相关系数，做截面排名后取近5日最大值再取反。值越大，表示近期量价同步变化的程度在截面上越低。
因子公式
(-1 * TSMAX(RANK(CORR(RANK(VOLUME), RANK(VWAP), 5)), 5))BigQuant SQL
SELECT date, instrument, -1*m_max(pct_rank_by(date, m_corr(pct_rank_by(date, volume), pct_rank_by(date, amount/volume), 5)), 5) AS _factor_temp, 1 * _factor_temp AS factorFROM cn_stock_bar1dORDER BY date, instrumentbq examples new strategies/multi_factor.py bqf_10116_strategy.py --name 'Alpha191 #16 选股' \ --set 'TABLES=["cn_stock_factors_alpha_191"]' --set 'FACTORS=["alpha_016"]' --set 'HOLD=30' \ --set 'EVERY=20' --set 'BENCHMARK="000300.SH"' --set 'START="2021-01-01"' \ --set 'END="2026-09-22"' \ && python bqf_10116_strategy.pySELECT date, instrument, alpha_016 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_10116"], "2021-01-01", "2026-09-22")report = factor.analyze( values, start_date="2021-01-01", end_date="2026-09-22", universe=("all", "hs300"), neutralize=(None, "size+industry"), depth="deep",)report.render()