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因子逻辑
开盘与最低加权价累计和与120日平均成交额累计和的相关排名，若小于中价与vwap加权价3日变化的排名则取-1，表示近期价格变化的相对水平超过价格与成交额的相关性。
因子公式
((rank(correlation(sum(((open * 0.178404) + (low * (1 - 0.178404))), 12.7054), sum(adv120, 12.7054), 16.6208)) < rank(delta(((((high + low) / 2) * 0.178404) + (vwap * (1 - 0.178404))), 3.69741))) * -1)BigQuant SQL
SELECT date, instrument, -1 * IF(m_sum(m_avg(amount, 120), 12.7054) IS NULL, NULL, IF(pct_rank_by(date, m_corr(m_sum(open * 0.178404 + low * (1-0.178404), 12.7054), m_sum(m_avg(amount, 120), 12.7054), 16.6208)) < pct_rank_by(date, (high+low)/2*0.178408+amount/volume*(1-0.178404)-m_lag((high+low)/2*0.178404+amount/volume*(1-0.178404), 3.69741)), 1, 0)) AS _factor_temp, 1 * CAST(_factor_temp AS DOUBLE) AS factor,FROM cn_stock_bar1dORDER BY date, instrumentbq examples new strategies/multi_factor.py bqf_10064_strategy.py --name 'Alpha#64 选股' \ --set 'TABLES=["cn_stock_factors_alpha_101"]' --set 'FACTORS=["alpha_064"]' --set 'HOLD=30' \ --set 'EVERY=20' --set 'BENCHMARK="000300.SH"' --set 'START="2021-01-01"' \ --set 'END="2026-09-22"' \ && python bqf_10064_strategy.pySELECT date, instrument, alpha_064 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_10064"], "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()