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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
今日开盘价相对昨日最高、收盘、最低价的跳空幅度分别做截面排名，三者相乘并取负；值越大表示开盘相对前一日价格的向上跳空越弱。
因子公式
(((-1 * RANK((OPEN -DELAY(HIGH, 1)))) * RANK((OPEN -DELAY(CLOSE, 1)))) *RANK((OPEN -DELAY(LOW, 1))))BigQuant SQL
SELECT date, instrument, pct_rank_by(date, open-m_lag(high, 1))*pct_rank_by(date, open-m_lag(close, 1))*pct_rank_by(date, open-m_lag(low, 1)) AS _factor_temp, 1 * _factor_temp AS factorFROM cn_stock_bar1dORDER BY date, instrumentbq examples new strategies/multi_factor.py bqf_10281_strategy.py --name 'Alpha191 #107 选股' \ --set 'TABLES=["cn_stock_factors_alpha_191"]' --set 'FACTORS=["alpha_107"]' --set 'HOLD=30' \ --set 'EVERY=20' --set 'BENCHMARK="000300.SH"' --set 'START="2021-01-01"' \ --set 'END="2026-09-18"' \ && python bqf_10281_strategy.pySELECT date, instrument, alpha_107 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_10281"], "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()