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

Bryzgalova, S, Huang, J and Julliard, C (2023) Bayesian Solutions for the Factor Zoo: We Just Ran Two Quadrillion Models. Journal of Finance, 78 (1). pp. 487-557. ISSN 0022-1082 OPEN ACCESS

Abstract

We propose a novel framework for analyzing linear asset pricing models: simple, robust, and applicable to high-dimensional problems. For a (potentially misspecified) stand-alone model, it provides reliable price of risk estimates for 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 Bayesian model averaging, BMA-SDF, if there is no clear winner. We analyze 2.25 quadrillion models generated by a large set of factors and find that the BMA-SDF outperforms existing models in- and out-of-sample.

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Item Type: Article
Subject Areas: Finance
Additional Information:

© 2022 The Authors. The Journal of Finance published by Wiley Periodicals LLC on behalf of American Finance Association.

Funder Name: Economic and Social Research Council
Date Deposited: 13 Dec 2022 15:02
Date of first compliant deposit: 03 Jan 2023
Subjects: Pricing
Assets
Mathematical models
Last Modified: 25 Sep 2023 00:40
URI: https://lbsresearch.london.edu/id/eprint/2743
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