VSUMD20 VSUMD

Difference of volume contributions

Formula

(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)

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)
-0.0033
ICIR
-0.056
Cross-section mean
0.0082
Cross-section std
0.0719
Min
-0.2706
Max
0.2590

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

alpha158.json

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)
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)
VSUMD60
(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)