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因子逻辑
成交量32日时序排名，乘以1减价格（收盘加最高减最低）16日时序排名，再乘以1减收益32日时序排名；值越大表示成交量处于近期高位而价格与收益处于近期低位。
因子公式
((Ts_Rank(volume, 32) * (1 - Ts_Rank(((close + high) - low), 16))) * (1 - Ts_Rank(returns, 32)))BigQuant SQL
SELECT date, instrument, (m_rank(volume, 32)/32) * (1 - (m_rank(close+high-low, 16)/16)) * (1 - (m_rank(close/m_lag(close, 1)-1, 32)/32)) AS _factor_temp, 1 * _factor_temp AS factor,FROM cn_stock_bar1dORDER BY date, instrumentbq examples new strategies/multi_factor.py bqf_10035_strategy.py --name 'Alpha#35 选股' \ --set 'TABLES=["cn_stock_factors_alpha_101"]' --set 'FACTORS=["alpha_035"]' --set 'HOLD=30' \ --set 'EVERY=20' --set 'BENCHMARK="000300.SH"' --set 'START="2021-01-01"' \ --set 'END="2026-09-22"' \ && python bqf_10035_strategy.pySELECT date, instrument, alpha_035 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_10035"], "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()