Bryzgalova, S, Huang, J and Julliard, C (2020) Bayesian Solutions for the Factor Zoo: We Just Ran Two Quadrillion Models. Working Paper. Social Sciences Research Network.
Abstract
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.
More Details
Item Type: | Monograph (Working Paper) |
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Subject Areas: | Finance |
Date Deposited: | 03 Nov 2020 15:44 |
Last Modified: | 01 Oct 2024 12:19 |
URI: | https://lbsresearch.london.edu/id/eprint/1532 |