The Virtue of Complexity in Return Prediction
Swiss Finance Institute Research Paper No. 21-90
Journal of Finance, forthcoming
141 Pages Posted: 15 Dec 2021 Last revised: 20 Oct 2023
There are 3 versions of this paper
The Virtue of Complexity in Return Prediction
The Virtue of Complexity in Return Prediction
The Virtue of Complexity in Return Prediction
Date Written: December 13, 2021
Abstract
Much of the extant literature predicts market returns with “simple” models that use only a few parameters. Contrary to conventional wisdom, we theoretically prove that simple models severely understate return predictability compared to “complex” models in which the number of parameters exceeds the number of observations. We empirically document the virtue of complexity in U.S. equity market return prediction. Our findings establish the rationale for modeling expected returns through machine learning.
Keywords: Portfolio choice, machine learning, random matrix theory, benign overfit, overparameterization
JEL Classification: C3, C58, C61, G11, G12, G14
Suggested Citation: Suggested Citation