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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按板块中性化后与成交量的3日相关，经7日线性衰减后在过去5日做时序排名并取反，值越大表示剔除板块影响后的量价相关处于自身近期低位。
因子公式
(-1 * Ts_Rank(decay_linear(correlation(IndNeutralize(vwap, IndClass.sector), volume, 3.92795), 7.89291), 5.50322))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_10058_strategy.py --name 'Alpha#58 选股' \ --set 'TABLES=["cn_stock_factors_alpha_101"]' --set 'FACTORS=["alpha_058"]' --set 'HOLD=30' \ --set 'EVERY=20' --set 'BENCHMARK="000300.SH"' --set 'START="2021-01-01"' \ --set 'END="2026-09-22"' \ && python bqf_10058_strategy.pySELECT date, instrument, alpha_058 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_10058"], "2021-01-01", "2026-09-22")report = factor.analyze( values, start_date="2021-01-01", end_date="2026-09-22", universe=("all", "hs300"), neutralize=(None, "size+industry"), depth="deep",)report.render()