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因子逻辑
收盘价截面排名与成交量截面排名的5日协方差，再取截面排名的负值；值越大表示近期价格与成交量的同向变动越弱，或越呈背离。
因子公式
(-1 * RANK(COVIANCE(RANK(CLOSE), RANK(VOLUME), 5)))BigQuant SQL
SELECT date, instrument, -1 * pct_rank_by(date, m_covar_samp(pct_rank_by(date, close), pct_rank_by(date, volume), 5)) AS _factor_temp, 1 * _factor_temp AS factorFROM cn_stock_bar1dORDER BY date, instrumentbq examples new strategies/multi_factor.py bqf_10264_strategy.py --name 'Alpha191 #99 选股' \ --set 'TABLES=["cn_stock_factors_alpha_191"]' --set 'FACTORS=["alpha_099"]' --set 'HOLD=30' \ --set 'EVERY=20' --set 'BENCHMARK="000300.SH"' --set 'START="2021-01-01"' \ --set 'END="2026-09-18"' \ && python bqf_10264_strategy.pySELECT date, instrument, alpha_099 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_10264"], "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()