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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
最高价与成交量5日相关系数的5日变化，乘以20日收盘价波动率的截面排名后取负；值越大表示量价相关性下降越多，且高波动股票权重更大。
因子公式
(-1 * (DELTA(CORR(HIGH, VOLUME, 5), 5) * RANK(STD(CLOSE, 20))))BigQuant SQL
SELECT date, instrument, m_corr(high, volume, 5) AS _front, -1*(_front-m_lag(_front, 5))*pct_rank_by(date, m_stddev(close, 20)) AS _factor_temp, 1 * _factor_temp AS factorFROM cn_stock_bar1dORDER BY date, instrumentbq examples new strategies/multi_factor.py bqf_10275_strategy.py --name 'Alpha191 #104 选股' \ --set 'TABLES=["cn_stock_factors_alpha_191"]' --set 'FACTORS=["alpha_104"]' --set 'HOLD=30' \ --set 'EVERY=20' --set 'BENCHMARK="000300.SH"' --set 'START="2021-01-01"' \ --set 'END="2026-09-18"' \ && python bqf_10275_strategy.pySELECT date, instrument, alpha_104 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_10275"], "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()