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因子逻辑
按 Wilder 振动升降指标的方式，以开高低收与前一日价格计算每日摆动值，累加20日，类似 ASI 指标。值越大，表示近期价格在真实波幅框架下的累积上行越强。
因子公式
SUM(16*(CLOSE-DELAY(CLOSE,1)+(CLOSE-OPEN)/2+DELAY(CLOSE,1)-DELAY(OPEN,1))/((ABS(HIGH-DELAY(CLOSE,1))>ABS(LOW-DELAY(CLOSE,1))&ABS(HIGH-DELAY(CLOSE,1))>ABS(HIGH-DELAY(LOW,1))?ABS(HIGH-DELAY(CLOSE,1))+ABS(LOW-DELAY(CLOSE,1))/2+ABS(DELAY(CLOSE,1)-DELAY(OPEN,1))/4:(ABS(LOW-DELAY(CLOSE,1))>ABS(HIGH-DELAY(LOW,1))&ABS(LOW-DELAY(CLOSE,1))>ABS(HIGH-DELAY(CLOSE,1))?ABS(LOW-DELAY(CLOSE,1))+ABS(HIGH-DELAY(CLOSE,1))/2+ABS(DELAY(CLOSE,1)-DELAY(OPEN,1))/4:ABS(HIGH-DELAY(LOW,1))+ABS(DELAY(CLOSE,1)-DELAY(OPEN,1))/4)))*MAX(ABS(HIGH-DELAY(CLOSE,1)),ABS(LOW-DELAY(CLOSE,1))),20)BigQuant SQL
SELECT date, instrument, close+(close-open)/2-m_lag(open, 1) AS _front, ABS(high-m_lag(close, 1)) AS _front2, ABS(low-m_lag(close, 1)) AS _front3, ABS(high-m_lag(low, 1)) AS _front4, ABS(m_lag(close, 1)-m_lag(open, 1)) AS _front5, if(m_lag(close, 1) IS NULL, NULL, if(_front2>_front3 AND _front2>_front4, _front2+_front3/2+_front5/4, if(_front3>_front4 AND _front3>_front2, _front3+_front2/2+_front5/4, _front4+_front5/4))) AS _front6, -1 * ( m_sum(16*_front/_front6*greatest(_front2, _front3), 20)) AS _factor_temp, 1 * _factor_temp AS factorFROM cn_stock_bar1dORDER BY date, instrumentbq examples new strategies/multi_factor.py bqf_10175_strategy.py --name 'Alpha191 #55 选股' \ --set 'TABLES=["cn_stock_factors_alpha_191"]' --set 'FACTORS=["alpha_055"]' --set 'HOLD=30' \ --set 'EVERY=20' --set 'BENCHMARK="000300.SH"' --set 'START="2021-01-01"' \ --set 'END="2026-09-22"' \ && python bqf_10175_strategy.pySELECT date, instrument, alpha_055 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_10175"], "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()