IDEAS home Printed from https://ideas.repec.org/p/chf/rpseri/rp1878.html
   My bibliography  Save this paper

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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Amit Goyal & Zhongzhi Lawrence He & Sahn-Wook Huh, 2018. "Distance-Based Metrics: A Bayesian Solution to the Power and Extreme-Error Problems in Asset-Pricing Tests," Swiss Finance Institute Research Paper Series 18-78, Swiss Finance Institute.
    • Handle: RePEc:chf:rpseri:rp1878
    as

    Download full text from publisher

    File URL: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3286327
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ali, Fahad & Ülkü, Numan, 2021. "Quest for a parsimonious factor model in the wake of quality-minus-junk, misvaluation and Fama-French-six factors," Finance Research Letters, Elsevier, vol. 41(C).
    2. Svetlana Bryzgalova & Jiantao Huang & Christian Julliard, 2023. "Bayesian Solutions for the Factor Zoo: We Just Ran Two Quadrillion Models," Journal of Finance, American Finance Association, vol. 78(1), pages 487-557, February.

    More about this item

    Keywords

    Asset-Pricing Tests; Power Problem; Extreme-Error Problem; Distance-Based Metrics; Optimal Transport Theory; Bayesian Interpretations; Model Comparisons and Rankings;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:chf:rpseri:rp1878. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ridima Mittal (email available below). General contact details of provider: https://edirc.repec.org/data/fameech.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.