IDEAS home Printed from https://ideas.repec.org/a/eee/ecofin/v68y2023ics1062940823001031.html
   My bibliography  Save this article

Evaluating asset pricing models with non-traded factors using the method of maximum-correlated portfolios

Author

Listed:
  • Yang, Ge
  • Yin, Ximing
  • Kimmel, Robert L.

Abstract

This paper examines the performance of several important asset pricing models with non-traded factors. We propose to test the asset pricing models using the method of Maximum-Correlated (MC) Portfolios. This method is particularly useful when evaluating models with non-traded factors, where the models are potentially mis-specified and factors are possibly noisy. The Q-statistics and Sharpe ratios, derived from MC portfolio method, are used as the goodness-of-fit measures. Smaller Q-stats and higher Sharpe ratios indicate better model performance. We find that Campbell (1996) and Jagannathan and Wang (1996) models are among the best models to price the test assets. These results differ significantly from the existing methods which may be biased by noisy factors.

Suggested Citation

  • Yang, Ge & Yin, Ximing & Kimmel, Robert L., 2023. "Evaluating asset pricing models with non-traded factors using the method of maximum-correlated portfolios," The North American Journal of Economics and Finance, Elsevier, vol. 68(C).
    • Handle: RePEc:eee:ecofin:v:68:y:2023:i:c:s1062940823001031
    DOI: 10.1016/j.najef.2023.101980
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1062940823001031
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.najef.2023.101980?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Yin, Ximing & Yang, Ge, 2024. "Instantaneous volatility of the yield curve, variance risk premium and bond return predictability," Journal of Empirical Finance, Elsevier, vol. 77(C).

    More about this item

    Keywords

    Maximum-correlated portfolios; Non-traded factor models; Sharpe ratios;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    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:eee:ecofin:v:68:y:2023:i:c:s1062940823001031. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620163 .

    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.