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因子逻辑
10日累计收益与短期滚动收益和之比的排名，乘以收益乘市值的排名后取负，值越大表示该收益结构与市值加权当日收益的组合越低。
因子公式
(0 - (1 * (rank((sum(returns, 10) / sum(sum(returns, 2), 3))) * rank((returns * cap)))))BigQuant SQL
WITHdataframe AS ( SELECT d.date, d.instrument, d.close, v.total_market_cap FROM cn_stock_bar1d d JOIN cn_stock_valuation v ON d.instrument = v.instrument AND d.date = v.date)SELECT date, instrument, 0 - (pct_rank_by(date, m_sum(close/m_lag(close, 1)-1, 10)/m_sum(m_sum(close/m_lag(close, 1)-1, 2), 3)) * pct_rank_by(date, (close/m_lag(close, 1)-1) * total_market_cap)) AS _factor_temp, 1 * _factor_temp AS factor,FROM dataframeORDER BY date, instrumentbq examples new strategies/multi_factor.py bqf_10056_strategy.py --name 'Alpha#56 选股' \ --set 'TABLES=["cn_stock_factors_alpha_101"]' --set 'FACTORS=["alpha_056"]' --set 'HOLD=30' \ --set 'EVERY=20' --set 'BENCHMARK="000300.SH"' --set 'START="2021-01-01"' \ --set 'END="2026-09-22"' \ && python bqf_10056_strategy.pySELECT date, instrument, alpha_056 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_10056"], "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()