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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
前一日开盘减收盘与收盘价200日相关的排名，加上当日开盘减收盘的排名；值越大表示当日阴线实体越大，且前日K线实体与价格的长期相关越高。
因子公式
(RANK(CORR(DELAY((OPEN -CLOSE), 1), CLOSE, 200)) + RANK((OPEN -CLOSE)))BigQuant SQL
SELECT date, instrument, pct_rank_by(date, m_corr((open-close)-m_lag((open-close), 1), close, 200))+pct_rank_by(date, open-close) AS _factor_temp, 1 * _factor_temp AS factorFROM cn_stock_bar1dORDER BY date, instrumentbq examples new strategies/multi_factor.py bqf_10433_strategy.py --name 'Alpha191 #184 选股' \ --set 'TABLES=["cn_stock_factors_alpha_191"]' --set 'FACTORS=["alpha_184"]' --set 'HOLD=30' \ --set 'EVERY=20' --set 'BENCHMARK="000300.SH"' --set 'START="2021-01-01"' \ --set 'END="2026-09-18"' \ && python bqf_10433_strategy.pySELECT date, instrument, alpha_184 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_10433"], "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()