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因子逻辑
取两项较小者：中价加收盘低于最低加开盘这一事件的衰减时序排名，与最低价和30日平均成交额排名相关的衰减时序排名；值越大表示两项都处于近期较高水平。
因子公式
min(Ts_Rank(decay_linear(((((high + low) / 2) + close) < (low + open)), 14.7221), 18.8683), Ts_Rank(decay_linear(correlation(rank(low), rank(adv30), 7.58555), 6.94024), 6.80584))BigQuant SQL
WITHfactor_data AS ( SELECT date, instrument, m_rank(m_decay_linear(IF((high+low)/2 + close < low + open, 1, 0), 14.7221), 18.8683) AS factor_1, m_rank(m_decay_linear(m_corr(pct_rank_by(date, low), pct_rank_by(date, m_avg(amount, 30)), 7.58555), 6.94024), 6.80584) AS factor_2 FROM cn_stock_bar1d)SELECT date, instrument, IF(factor_2 IS NULL, NULL, IF(factor_1 < factor_2, factor_1, factor_2)) AS _factor_temp, 1 * _factor_temp AS factor,FROM factor_dataORDER BY date, instrumentbq examples new strategies/multi_factor.py bqf_10091_strategy.py --name 'Alpha#92 选股' \ --set 'TABLES=["cn_stock_factors_alpha_101"]' --set 'FACTORS=["alpha_092"]' --set 'HOLD=30' \ --set 'EVERY=20' --set 'BENCHMARK="000300.SH"' --set 'START="2021-01-01"' \ --set 'END="2026-09-17"' \ && python bqf_10091_strategy.pySELECT date, instrument, alpha_092 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_10091"], "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()