The Virtue of Complexity in Return Prediction

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 exce...

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Bibliographic Details
Published in:The Journal of finance (New York) 2024-02, Vol.79 (1), p.459-503
Main Authors: KELLY, BRYAN, MALAMUD, SEMYON, ZHOU, KANGYING
Format: Article
Language:English
Subjects:
Economic models
Morality
Rates of return
Securities trading
Wisdom
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Summary: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.
ISSN:0022-1082
1540-6261
DOI:10.1111/jofi.13298