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因子逻辑
最低价与10日平均成交额7日相关衰减后的时序排名，减去行业中性化vwap 3日变化衰减后的15日时序排名；值越大表示低价与成交额相关处于近期高位而行业内相对均价变化处于近期低位。
因子公式
(Ts_Rank(decay_linear(correlation(((low * 0.967285) + (low * (1 - 0.967285))), adv10, 6.94279), 5.51607), 3.79744) - Ts_Rank(decay_linear(delta(IndNeutralize(vwap, IndClass.industry), 3.48158), 10.1466), 15.3012))BigQuant SQL
WITHindustry_data AS ( SELECT date, instrument, industry_level1_code FROM cn_stock_industry_component WHERE industry = 'sw2021'),factor_data AS (bq examples new strategies/multi_factor.py bqf_10088_strategy.py --name 'Alpha#89 选股' \ --set 'TABLES=["cn_stock_factors_alpha_101"]' --set 'FACTORS=["alpha_089"]' --set 'HOLD=30' \ --set 'EVERY=20' --set 'BENCHMARK="000300.SH"' --set 'START="2021-01-01"' \ --set 'END="2026-09-17"' \ && python bqf_10088_strategy.pySELECT date, instrument, alpha_089 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_10088"], "2021-01-01", "2026-09-17")report = factor.analyze( values, start_date="2021-01-01", end_date="2026-09-17", universe=("all", "hs300"), neutralize=(None, "size+industry"), depth="deep",)report.render()