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因子逻辑
布尔信号，比较开盘价距12日最低开盘价的排名与中价和40日平均成交额累计和相关排名五次方的时序排名；为1表示开盘离近期低点较近而价额相关处于近期相对高位。
因子公式
(rank((open - ts_min(open, 12.4105))) < Ts_Rank((rank(correlation(sum(((high + low) / 2), 19.1351), sum(adv40, 19.1351), 12.8742))^5), 11.7584))BigQuant SQL
WITHfactor_data AS ( SELECT date, instrument, pct_rank_by(date, open - m_min(open, 12.4105)) AS factor_1, m_rank((pct_rank_by(date, m_corr(m_sum((high + low)/2, 19.1351), m_sum(m_avg(amount, 40), 19.1351), 12.8742)) ^ 5), 11.7584)/11.7584 AS factor_2 FROM cn_stock_bar1d)SELECT date, instrument, IF(factor_2 IS NULL, NULL, IF(factor_1 < factor_2, 1, 0)) AS _factor_temp, 1 * CAST(_factor_temp AS DOUBLE) AS factor,FROM factor_dataORDER BY date, instrumentbq examples new strategies/multi_factor.py bqf_10094_strategy.py --name 'Alpha#95 选股' \ --set 'TABLES=["cn_stock_factors_alpha_101"]' --set 'FACTORS=["alpha_095"]' --set 'HOLD=30' \ --set 'EVERY=20' --set 'BENCHMARK="000300.SH"' --set 'START="2021-01-01"' \ --set 'END="2026-09-17"' \ && python bqf_10094_strategy.pySELECT date, instrument, alpha_095 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_10094"], "2021-01-01", "2026-09-17")report = factor.analyze( values, start_date="2021-01-01", end_date="2026-09-17", universe=("all", "hs300"), neutralize=(None, "size+industry"), depth="deep",)report.render()