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因子逻辑
高价加权价与30日均量10日相关的排名，以中间价与成交量时序排名7日相关的排名为指数；刻画两种尺度下的量价同步性，底数正向、指数反向影响取值。
因子公式
(RANK(CORR(((HIGH * 0.9) + (CLOSE * 0.1)), MEAN(VOLUME,30), 10))^RANK(CORR(TSRANK(((HIGH + LOW) /2), 4), TSRANK(VOLUME, 10), 7)))BigQuant SQL
SELECT date, instrument, -1 * (pct_rank_by(date, m_corr(high*0.9+close*0.1, m_avg(volume, 30), 10))^pct_rank_by(date, m_corr(m_rank((high+low)/2, 4), m_rank(volume, 10), 7))) AS _factor_temp, 1 * _factor_temp AS factorFROM cn_stock_bar1dORDER BY date, instrumentbq examples new strategies/multi_factor.py bqf_10297_strategy.py --name 'Alpha191 #115 选股' \ --set 'TABLES=["cn_stock_factors_alpha_191"]' --set 'FACTORS=["alpha_115"]' --set 'HOLD=30' \ --set 'EVERY=20' --set 'BENCHMARK="000300.SH"' --set 'START="2021-01-01"' \ --set 'END="2026-09-18"' \ && python bqf_10297_strategy.pySELECT date, instrument, alpha_115 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_10297"], "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()