VSUMD60 VSUMD
Difference of volume contributions
Formula
(Sum(Greater($volume-Ref($volume, 1), 0), 60)-Sum(Greater(Ref($volume, 1)-$volume, 0), 60))/(Sum(Abs($volume-Ref($volume, 1)), 60)+1e-12)
The expression above is verbatim from qlib Alpha158/360 feature engineering (qlib/contrib/data/loader.py, Apache-2.0). The platform qlib-compatible expression engine evaluates it on the deterministic research panel.
Cross-section statistics & information coefficient
IC mean (60M)
0.0017
ICIR
0.029
Cross-section mean
0.0016
Cross-section std
0.0237
Min
-0.0730
Max
0.0952
IC = Spearman-style rank correlation between the factor cross-section and next-month returns, computed over the last 60 months on the deterministic research panel.
Data export
Related factors · VSUMD
VSUMD5
(Sum(Greater($volume-Ref($volume, 1), 0), 5)-Sum(Greater(Ref($volume, 1)-$volume, 0), 5))/(Sum(Abs($volume-Ref($volume, 1)), 5)+1e-12)
VSUMD10(Sum(Greater($volume-Ref($volume, 1), 0), 10)-Sum(Greater(Ref($volume, 1)-$volume, 0), 10))/(Sum(Abs($volume-Ref($volume, 1)), 10)+1e-12)
VSUMD20(Sum(Greater($volume-Ref($volume, 1), 0), 20)-Sum(Greater(Ref($volume, 1)-$volume, 0), 20))/(Sum(Abs($volume-Ref($volume, 1)), 20)+1e-12)
VSUMD30(Sum(Greater($volume-Ref($volume, 1), 0), 30)-Sum(Greater(Ref($volume, 1)-$volume, 0), 30))/(Sum(Abs($volume-Ref($volume, 1)), 30)+1e-12)