A Self-supervised Approach to Hierarchical Forecasting with Applications to Groupwise Synthetic Controls

Konstantin Mishchenko, Mallory Montgomery, Federico Vaggi

When forecasting time series with a hierarchical structure, the existing state of the art is to forecast each time series independently, and, in a post-treatment step, to reconcile…