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因子逻辑
收盘价减vwap，除以过去30日最高收盘价出现位置排名的2日衰减均值后取负，值越大表示收盘低于成交均价越多，幅度受近期高点出现时点调节。
因子公式
(0 - (1 * ((close - vwap) / decay_linear(rank(ts_argmax(close, 30)), 2))))BigQuant SQL
WITHwindows AS( SELECT date, instrument, close - amount/volume AS factor_1, close, m_max(close, 30) AS max_close, ROW_NUMBER() OVER (PARTITION BY instrument ORDER BY date DESC) AS rn FROM cn_stock_bar1dbq examples new strategies/multi_factor.py bqf_10057_strategy.py --name 'Alpha#57 选股' \ --set 'TABLES=["cn_stock_factors_alpha_101"]' --set 'FACTORS=["alpha_057"]' --set 'HOLD=30' \ --set 'EVERY=20' --set 'BENCHMARK="000300.SH"' --set 'START="2021-01-01"' \ --set 'END="2026-09-22"' \ && python bqf_10057_strategy.pySELECT date, instrument, alpha_057 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_10057"], "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()