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AI 原生量化投研平台AI-native quantitative research platform
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因子逻辑
当成交量超过20日平均成交额时，取7日价格变化幅度在过去60日的时序排名并乘以其方向后取反，否则取-1；放量时近7日跌得越多值越大，体现放量下的反转。
因子公式
((adv20 < volume) ? ((-1 * ts_rank(abs(delta(close, 7)), 60)) * sign(delta(close, 7))) : (-1 * 1))BigQuant SQL
SELECT date, instrument, IF((m_avg(volume, 20) < volume), ((-1 * m_rank(abs(m_lag(close, 7)), 60)) * sign(m_lag(close, 7))), (-1 * 1)) AS _factor_temp, 1 * _factor_temp AS factor,FROM cn_stock_bar1dORDER BY date, instrumentbq examples new strategies/multi_factor.py bqf_10007_strategy.py --name 'Alpha#7 选股' \ --set 'TABLES=["cn_stock_factors_alpha_101"]' --set 'FACTORS=["alpha_007"]' --set 'HOLD=30' \ --set 'EVERY=20' --set 'BENCHMARK="000300.SH"' --set 'START="2021-01-01"' \ --set 'END="2026-09-21"' \ && python bqf_10007_strategy.pySELECT date, instrument, alpha_007 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_10007"], "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()