Bayesian solutions for the factor zoo: we just ran two quadrillion models

Bryzgalova, Svetlana, Huang, Jiantao and Julliard, Christian ORCID: 0000-0001-8177-7441 (2023) Bayesian solutions for the factor zoo: we just ran two quadrillion models. Journal of Finance, 78 (1). pp. 487-557. ISSN 0022-1082

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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 nontradable factors, and detects those weakly identified. For competing factors and (possibly nonnested) models, the method automatically selects the best specification—if a dominant one exists—or provides a Bayesian model averaging–stochastic discount factor (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.

Item Type:	Article
Additional Information:	© 2022 The Author(s)
Divisions:	Finance
Subjects:	H Social Sciences > HF Commerce > HF5601 Accounting H Social Sciences > HG Finance H Social Sciences > HB Economic Theory
JEL classification:	C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C11 - Bayesian Analysis C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C52 - Model Evaluation and Selection G - Financial Economics > G1 - General Financial Markets > G12 - Asset Pricing; Trading volume; Bond Interest Rates C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C50 - General
Date Deposited:	22 Nov 2024 12:57
Last Modified:	12 Dec 2024 04:35
URI:	http://eprints.lse.ac.uk/id/eprint/126151

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