IDEAS home Printed from https://ideas.repec.org/p/ysm/wpaper/amz2523.html
   My bibliography  Save this paper

Multifactor Efficiency and Bayesian Inference

Author

Listed:
  • Martijn Cremers

Abstract

This paper reinvestigates the performance of risk-based multifactor models. In particular, we generalize the Bayesian methodology of Shanken (1987b) and Kandel, McCulloch and Stambaugh (1995) from mean-variance efficiency to the ICAPM notion of multifactor efficiency. This methodology uses informative priors and provides a flexible framework to deal with the severe small sample problems that arise when estimating performance measures. We also introduce and theoretically justify a new inefficiency metric that measures the maximum correlation between the market portfolio and any multifactor efficient portfolio, which is used in conjunction with three other existing inefficiency measures. Finally, we present new empirical evidence that neither the two additional Fama-French (1992) factors nor the momentum factor move the market portfolio robustly closer to being multifactor efficient or robustly decrease pricing errors relative to the CAPM.

Suggested Citation

  • Martijn Cremers, 2006. "Multifactor Efficiency and Bayesian Inference," Yale School of Management Working Papers amz2523, Yale School of Management.
    • Handle: RePEc:ysm:wpaper:amz2523
    as

    Download full text from publisher

    File URL: https://repec.som.yale.edu/icfpub/publications/2523.pdf
    Download Restriction: no
    ---><---

    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:ysm:wpaper:amz2523. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/smyalus.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.