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因子逻辑
收益率3日变化的排名取负，再乘以开盘价与成交量的10日相关系数；收益加速上升越明显取值越负，方向与幅度受开盘价与成交量相关性调节。
因子公式
((-1 * rank(delta(returns, 3))) * correlation(open, volume, 10))BigQuant SQL
WITHt AS( SELECT date, instrument, close / m_lag(close, 1) - 1 AS return, return - m_lag(return, 3) AS delta_return, m_corr(open, volume, 10) AS open_volume_corr, (-1 * pct_rank_by(date, delta_return)) * open_volume_corr AS factor1 FROM cn_stock_bar1d)SELECT date, instrument, factor1 AS _factor_temp, 1 * _factor_temp AS factor,FROM tORDER BY date, instrumentbq examples new strategies/multi_factor.py bqf_10014_strategy.py --name 'Alpha#14 选股' \ --set 'TABLES=["cn_stock_factors_alpha_101"]' --set 'FACTORS=["alpha_014"]' --set 'HOLD=30' \ --set 'EVERY=20' --set 'BENCHMARK="000300.SH"' --set 'START="2021-01-01"' \ --set 'END="2026-09-21"' \ && python bqf_10014_strategy.pySELECT date, instrument, alpha_014 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_10014"], "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()