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AI 原生量化投研平台AI-native quantitative research platform
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因子逻辑
vwap与成交量4日相关的排名，乘以最低价排名与50日均量排名12日相关的排名；值越大表示短期与中期两种量价相关同时越高。
因子公式
(RANK(CORR(VWAP, VOLUME, 4)) *RANK(CORR(RANK(LOW),RANK(MEAN(VOLUME,50)), 12)))BigQuant SQL
SELECT date, instrument, -1 * ( pct_rank_by(date, m_corr(amount/volume, volume, 4))*pct_rank_by(date, m_corr(pct_rank_by(date, low), pct_rank_by(date, m_avg(volume, 50)), 12)) ) AS _factor_temp, 1 * _factor_temp AS factorFROM cn_stock_bar1dORDER BY date, instrumentbq examples new strategies/multi_factor.py bqf_10423_strategy.py --name 'Alpha191 #179 选股' \ --set 'TABLES=["cn_stock_factors_alpha_191"]' --set 'FACTORS=["alpha_179"]' --set 'HOLD=30' \ --set 'EVERY=20' --set 'BENCHMARK="000300.SH"' --set 'START="2021-01-01"' \ --set 'END="2026-09-18"' \ && python bqf_10423_strategy.pySELECT date, instrument, alpha_179 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_10423"], "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()