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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
近5日开盘价之和乘近5日收益之和，与10日前同一乘积相比的变化做截面排名后取反，值越大表示这一价格与短期动量的组合较10日前下降越多。
因子公式
(-1 * rank(((sum(open, 5) * sum(returns, 5)) - delay((sum(open, 5) * sum(returns, 5)), 10))))BigQuant SQL
WITHdaily_returns AS ( SELECT date, instrument, open, close / m_lag(close, 1) - 1 AS returns FROM cn_stock_bar1d)SELECT date, instrument, pct_rank_by(date, (m_sum(open, 5) * m_sum(returns, 5) - m_lag(m_sum(open, 5) * m_sum(returns, 5), 10))) AS _factor_temp, -1 * _factor_temp AS factor,FROM daily_returnsORDER BY date, instrumentbq examples new strategies/multi_factor.py bqf_10008_strategy.py --name 'Alpha#8 选股' \ --set 'TABLES=["cn_stock_factors_alpha_101"]' --set 'FACTORS=["alpha_008"]' --set 'HOLD=30' \ --set 'EVERY=20' --set 'BENCHMARK="000300.SH"' --set 'START="2021-01-01"' \ --set 'END="2026-09-21"' \ && python bqf_10008_strategy.pySELECT date, instrument, alpha_008 FROM cn_stock_factors_alpha_101带入当前因子，在 Cowork 中继续研究。
from bigquant import factor
values = factor.values(["BQF_10008"], "2021-01-01", "2026-09-21")report = factor.analyze( values, start_date="2021-01-01", end_date="2026-09-21", universe=("all", "hs300"), neutralize=(None, "size+industry"), depth="deep",)report.render()