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因子逻辑
以收盘价在日内区间中的位置乘成交量作为资金流向强度，取其11日与4日SMA之差，类似蔡金振荡器；值越大表示短期资金流向相对较长期走弱。
因子公式
SMA(VOL*((CLOSE-LOW)-(HIGH-CLOSE))/(HIGH-LOW),11,2)-SMA(VOL*((CLOSE-LOW)-(HIGH-CLOSE))/(HIGH-LOW),4,2)BigQuant SQL
SELECT date, instrument, high-m_lag(close, 1) AS _front, m_lag(close, 1)-low AS _front2, -1 * m_sum(greatest(0, _front), 20)/m_sum(greatest(0, _front2), 20)*100 AS _factor_temp, 1 * _factor_temp AS factorFROM cn_stock_bar1dORDER BY date, instrumentbq examples new strategies/multi_factor.py bqf_10289_strategy.py --name 'Alpha191 #111 选股' \ --set 'TABLES=["cn_stock_factors_alpha_191"]' --set 'FACTORS=["alpha_111"]' --set 'HOLD=30' \ --set 'EVERY=20' --set 'BENCHMARK="000300.SH"' --set 'START="2021-01-01"' \ --set 'END="2026-09-18"' \ && python bqf_10289_strategy.pySELECT date, instrument, alpha_111 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_10289"], "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()