The Limited Virtue of Complexity in a Noisy World

Mon, 07 Jul 2025 00:00:00 +0000

Cartea, Álvaro and Jin, Qi and Shi, Yuantao, The Limited Virtue of Complexity in a Noisy World (April 02, 2025). Available at SSRN here or here.

Summary: In this paper, the authors analyse the role of model complexity in the context of predicting asset returns and portfolio construction. In particular, they aim to address the significant question of whether adding a large number of predictive features ultimately harms performance. Their work aims to bridge two views: the traditional econometric one, favoring parsimonious models (i.e. Occam’s razor), and the more modern machine learning findings that highly the fact that so-called “overparameterized” models can perform well under proper regularization ( double descent phenomenon).

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The Limited Virtue of Complexity in a Noisy World