加载中...
AI 原生量化投研平台AI-native quantitative research platform
正在加载…Loading…
页面仍在加载，可以继续等待，或重新加载。The page is still loading. You can keep waiting or reload.
部分页面资源未能加载，请重新加载。Some page resources could not load. Please reload.
设备当前处于离线状态，恢复连接后可以继续等待或重新加载。Your device is offline. Once connected, you can keep waiting or reload.
因子逻辑
由收盘价到最低、最高价的距离以及开盘与收盘价之比的5次幂组合而成，取值不大于0；值越大（越接近0）表示收盘越靠近最低价，且开盘相对收盘越低。
因子公式
((-1 * ((LOW -CLOSE) * (OPEN^5))) / ((CLOSE -HIGH) * (CLOSE^5)))BigQuant SQL
SELECT date, instrument, (-1*(low-close)*(open^5))/((close-high)*(close^5)) AS _factor_temp, 1 * _factor_temp AS factorFROM cn_stock_bar1dORDER BY date, instrumentbq examples new strategies/multi_factor.py bqf_10407_strategy.py --name 'Alpha191 #171 选股' \ --set 'TABLES=["cn_stock_factors_alpha_191"]' --set 'FACTORS=["alpha_171"]' --set 'HOLD=30' \ --set 'EVERY=20' --set 'BENCHMARK="000300.SH"' --set 'START="2021-01-01"' \ --set 'END="2026-09-18"' \ && python bqf_10407_strategy.pySELECT date, instrument, alpha_171 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_10407"], "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()