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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
在过去252日中基准指数下跌的交易日上，个股日收益对指数日收益回归的系数，即下行贝塔；值越大表示指数下跌时个股跟随下跌越敏感。
因子公式
REGBETA(FILTER(CLOSE/DELAY(CLOSE,1)-1,BANCHMARKINDEXCLOSE<DELAY(BANCHMARKINDEXCLOSE,1)),FILTER(BANCHMARKINDEXCLOSE/DELAY(BANCHMARKINDEXCLOSE,1)-1,BANCHMARKINDEXCLOSE<DELAY(BANCHMARKINDEXCLOSE,1)),252)BigQuant SQL
WITHdata1 AS ( SELECT date, instrument, close / m_lag(close, 1) -1 AS RET, FROM cn_stock_bar1d),data2 AS ( SELECTbq examples new strategies/multi_factor.py bqf_10363_strategy.py --name 'Alpha191 #149 选股' \ --set 'TABLES=["cn_stock_factors_alpha_191"]' --set 'FACTORS=["alpha_149"]' --set 'HOLD=30' \ --set 'EVERY=20' --set 'BENCHMARK="000300.SH"' --set 'START="2021-01-01"' \ --set 'END="2026-09-18"' \ && python bqf_10363_strategy.pySELECT date, instrument, alpha_149 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_10363"], "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()