Distance-Based Metrics: A Bayesian Solution to the Power and Extreme-Error Problems in Asset-Pricing Tests

56 Pages Posted: 11 Dec 2018 Last revised: 9 Jan 2019

See all articles by Amit Goyal

Amit Goyal

University of Lausanne

Zhongzhi Lawrence He

Brock University, Goodman School of Business

Sahn-Wook Huh

State University of New York (SUNY) - Department of Finance

Date Written: November 17, 2018

Abstract

We propose a unified set of distance-based performance metrics that address the power and extreme-error problems inherent in traditional measures for asset-pricing tests. From a Bayesian perspective, the distance metrics coherently incorporate both pricing errors and their standard errors. Measured in units of return, they have an economic interpretation as the minimum cost of holding a dogmatic belief in a model. Our metrics identify Fama and French (2015) factor model (augmented with the momentum factor and/or without the value factor) as the best model and thus highlight the importance of the momentum factor. In contrast, the traditional alpha-based statistics often lead to inconsistent and counter-intuitive model rankings.

Keywords: Asset-Pricing Tests, Power Problem, Extreme-Error Problem, Distance-Based Metrics, Optimal Transport Theory, Bayesian Interpretations, Model Comparisons and Rankings

JEL Classification: C11, G11, G12

Suggested Citation

Goyal, Amit and He, Zhongzhi Lawrence and Huh, Sahn-Wook, Distance-Based Metrics: A Bayesian Solution to the Power and Extreme-Error Problems in Asset-Pricing Tests (November 17, 2018). Swiss Finance Institute Research Paper No. 18-78. Available at SSRN: https://ssrn.com/abstract=3286327 or http://dx.doi.org/10.2139/ssrn.3286327

Amit Goyal (Contact Author)

University of Lausanne ( email )

Lausanne, Vaud CH-1015
Switzerland

Zhongzhi Lawrence He

Brock University, Goodman School of Business ( email )

500 Glenridge Avenue
Finance
St. Catherine's, Ontario L2S 3A1
Canada

Sahn-Wook Huh

State University of New York (SUNY) - Department of Finance ( email )

347 Jacobs Management Center
Buffalo, 14260-4000
United States
716-645-5435 (Phone)
716-645-3823 (Fax)

HOME PAGE: http://www.acsu.buffalo.edu/~swhuh/

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