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因子逻辑
12日内上涨幅度之和减下跌幅度之和，再除以二者之和乘100，类似钱德动量摆动指标CMO；值越大表示近期上涨力量越占优。
因子公式
(SUM((CLOSE-DELAY(CLOSE,1)>0?CLOSE-DELAY(CLOSE,1):0),12)-SUM((CLOSE-DELAY(CLOSE,1)<0?ABS(CLOSE-DELAY(CLOSE,1)):0),12))/(SUM((CLOSE-DELAY(CLOSE,1)>0?CLOSE-DELAY(CLOSE,1):0),12)+SUM((CLOSE-DELAY(CLOSE,1)<0?ABS(CLOSE-DELAY(CLOSE,1)):0),12))*100BigQuant SQL
SELECT date, instrument, close-m_lag(close, 1) AS _front, (m_sum(if(m_lag(close, 1) IS NULL, NULL, if(_front>0, _front, 0)), 12)-m_sum(if(m_lag(close, 1) IS NULL, NULL, if(_front<0, ABS(_front), 0)), 12))/(m_sum(if(_front>0, _front, 0), 12)+m_sum(if(_front<0, ABS(_front), 0), 12))*100 AS _factor_temp, -1 * _factor_temp AS factor,FROM cn_stock_bar1dORDER BY date, instrumentbq examples new strategies/multi_factor.py bqf_10291_strategy.py --name 'Alpha191 #112 选股' \ --set 'TABLES=["cn_stock_factors_alpha_191"]' --set 'FACTORS=["alpha_112"]' --set 'HOLD=30' \ --set 'EVERY=20' --set 'BENCHMARK="000300.SH"' --set 'START="2021-01-01"' \ --set 'END="2026-09-18"' \ && python bqf_10291_strategy.pySELECT date, instrument, alpha_112 FROM cn_stock_factors_alpha_191带入当前因子，在 Cowork 中继续研究。
from bigquant import factor
values = factor.values(["BQF_10291"], "2021-01-01", "2026-09-18")report = factor.analyze( values, start_date="2021-01-01", end_date="2026-09-18", universe=("all", "hs300"), neutralize=(None, "size+industry"), depth="deep",)report.render()