Real-time Machine Learning for the Cross-Section of Stock Returns

Speaker：Li Bin（ Professor, School of Economics and Management of Wuhan University）

Host：Liu Yanchu, Associate Professor, Lingnan College

Time and Date：14:30-16:30, Jun. 24, 2022

Venue：Third floor, Lingnan hall 

Language: English + Chinese

Abstract：

Recent studies document strong performance of machine learning based investment strategies. These strategies use anomaly variables discovered ex-post as predictors of stock returns and cannot be implemented in real time. We construct machine learning strategies from a “universe” of fundamental signals identified ex-ante and find that their out-of-sample performance is considerably weaker than those documented by previous studies. In addition, we find significant degradation from in-sample performance to out-of-sample performance, supporting the predictions of Martin and Nagel (2020). Overall, our results offer a more tempered view of the practical value of machine learning strategies relative to prior literature