Return prediction: A tree-based conditional sort approach with firm characteristics

Abstract

This paper proposes the Augmented Tree-Based Conditional Sort approach to investigate the return prediction problems. We find a momentum effect in the Chinese stock market using monthly data over 5000 stocks from January 2005 to December 2022. The corresponding momentum strategy robustly outperforms the market portfolio and earns an excess return of 10.60 % annually. Besides a full-period momentum effect, we find a sub-period reversal effect before year 2018 and locate year 2018 as a turning point from the reversal effect to the momentum effect. We attribute this phenomenon to the rapid increase of institutional investors since then.