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因子逻辑
用成交量对数的2日变化排名与当日收盘相对开盘涨幅排名做6日相关后取反，值越大表示放量与日内上涨越不同步，即量价背离越明显。
因子公式
(-1 * correlation(rank(delta(log(volume), 2)), rank(((close - open) / open)), 6))BigQuant SQL
WITHvolume_change AS ( SELECT date, instrument, LOG(IF(volume=0,0.000001,volume))-LOG(IF(m_lag(volume,2)=0,0.000001,m_lag(volume,2))) AS volume_change FROM cn_stock_bar1d),price_change AS ( SELECTbq examples new strategies/multi_factor.py bqf_10002_strategy.py --name 'Alpha#2 选股' \ --set 'TABLES=["cn_stock_factors_alpha_101"]' --set 'FACTORS=["alpha_002"]' --set 'HOLD=30' \ --set 'EVERY=20' --set 'BENCHMARK="000300.SH"' --set 'START="2021-01-01"' \ --set 'END="2026-09-21"' \ && python bqf_10002_strategy.pySELECT date, instrument, alpha_002 FROM cn_stock_factors_alpha_101带入当前因子，在 Cowork 中继续研究。
from bigquant import factor
values = factor.values(["BQF_10002"], "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()