Understanding The Virtue of Complexity

Bryan T. Kelly and Semyon Malamud
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Bryan T. Kelly: Yale SOM; AQR Capital Management, LLC; National Bureau of Economic Research (NBER)
Semyon Malamud: Ecole Polytechnique Federale de Lausanne; Centre for Economic Policy Research (CEPR); Swiss Finance Institute

No 25-96, Swiss Finance Institute Research Paper Series from Swiss Finance Institute

Abstract: Recent papers have challenged certain aspects of the "virtue of complexity" described by Kelly et al. (2024b) (KMZ) and related work. These challenges ultimately have little bearing on the theoretical arguments or empirical findings of KMZ. They do, however, provide a valuable opportunity to better understand the nuanced behavior of complex models. In addition to responding to recent challenges, we provide detailed discussions of how complex models learn in small samples, the roles of "nominal" and "effective" complexity, the unique effects of implicit regularization, and the importance of limits to learning. We then present new empirical and theoretical analyses that expand on KMZ. Finally, we introduce and demonstrate the virtue of ensemble complexity.

Keywords: Portfolio choice; machine learning; random matrix theory; benign overfit (search for similar items in EconPapers)
JEL-codes: C58 C61 G11 G12 G14 (search for similar items in EconPapers)
Pages: 101 pages
Date: 2025-07
New Economics Papers: this item is included in nep-cmp and nep-hme
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:chf:rpseri:rp2596

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