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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
5日价格变化率,下跌时以5日前收盘价为分母、上涨时以当前收盘价为分母,平盘为0。该处理使上涨幅度被略微压缩,值越大表示5日涨幅越大。
因子公式
(CLOSE<DELAY(CLOSE,5)?(CLOSE-DELAY(CLOSE,5))/DELAY(CLOSE,5):(CLOSE=DELAY(CLOSE,5)?0:(CLOSE-DELAY(CLOSE,5))/CLOSE))BigQuant SQL
SELECT date, instrument, -1 * if(m_lag(close, 5) IS NULL, NULL, if(close<m_lag(close, 5), close/m_lag(close, 5)-1, if(close=m_lag(close, 5), 0, 1-m_lag(close, 5)/close))) AS _factor_temp, 1 * _factor_temp AS factorFROM cn_stock_bar1dORDER BY date, instrumentbq examples new strategies/multi_factor.py bqf_10118_strategy.py --name 'Alpha191 #19 选股' \ --set 'TABLES=["cn_stock_factors_alpha_191"]' --set 'FACTORS=["alpha_019"]' --set 'HOLD=30' \ --set 'EVERY=20' --set 'BENCHMARK="000300.SH"' --set 'START="2021-01-01"' \ --set 'END="2026-09-22"' \ && python bqf_10118_strategy.pySELECT date, instrument, alpha_019 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_10118"], "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()