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Bayesian Solutions for the Factor Zoo: We Just Ran Two Quadrillion Models



Publishing details

Social Sciences Research Network

Authors / Editors

Bryzgalova S;Huang J;Julliard C

Publication Year



We propose a novel framework for analyzing linear asset pricing models: simple, robust, and applicable to high dimensional problems. For a (potentially misspecified) standalone model, it provides reliable risk premia estimates of both tradable and non-tradable factors, and detects those weakly identified. For competing factors and (possibly non-nested) models, the method automatically selects the best specification – if a dominant one exists – or provides a model averaging, if there is no clear winner given the data. We analyze 2.25 quadrillion models generated by a large set of existing factors, and gain novel insights on the empirical drivers of asset returns.


Cross-Sectional Asset Pricing; Factor Models; Model Evaluation; Multiple Testing; Data Mining; P-Hacking; Bayesian Methods; shrinkage; SDF


Social Sciences Research Network

Available on ECCH


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