IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-540-77958-2_8.html
   My bibliography  Save this book chapter

Robust Prediction of Beta

In: Computational Methods in Financial Engineering

Author

Listed:
  • Marc G. Genton

    (University of Geneva)

  • Elvezio Ronchetti

    (University of Geneva)

Abstract

The estimation of β plays a basic role in the evaluation of expected return and market risk. Typically this is performed by ordinary least squares (OLS). To cope with the high sensitivity of OLS to outlying observations and to deviations from the normality assumptions, several methods suggest to use robust estimators. It is argued that, from a predictive point of view, the simple use of either OLS or robust estimators is not sufficient but that some shrinking of the robust estimators toward OLS is necessary to reduce the mean squared error. The performance of the proposed shrinkage robust estimator is shown by means of a small simulation study and on a real data set.

Suggested Citation

  • Marc G. Genton & Elvezio Ronchetti, 2008. "Robust Prediction of Beta," Springer Books, in: Erricos J. Kontoghiorghes & Berç Rustem & Peter Winker (ed.), Computational Methods in Financial Engineering, pages 147-161, Springer.
    • Handle: RePEc:spr:sprchp:978-3-540-77958-2_8
    DOI: 10.1007/978-3-540-77958-2_8
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. Manfred Gilli & Enrico Schumann, 2012. "Heuristic optimisation in financial modelling," Annals of Operations Research, Springer, vol. 193(1), pages 129-158, March.
    2. Björn Fastrich & Peter Winker, 2012. "Robust portfolio optimization with a hybrid heuristic algorithm," Computational Management Science, Springer, vol. 9(1), pages 63-88, February.
    3. Omar Gharaibeh & Graham Bornholt & Michael Dempsey, 2014. "Evidence on Industry Cost of Equity Estimators," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 8(4), pages 1-15.
    4. Peter Winker & Marianna Lyra & Chris Sharpe, 2011. "Least median of squares estimation by optimization heuristics with an application to the CAPM and a multi-factor model," Computational Management Science, Springer, vol. 8(1), pages 103-123, April.
    5. R. Douglas Martin & Daniel Z. Xia, 2022. "Efficient bias robust regression for time series factor models," Journal of Asset Management, Palgrave Macmillan, vol. 23(3), pages 215-234, May.
    6. Theodossiou, Alexandra K. & Theodossiou, Panayiotis, 2014. "Stock return outliers and beta estimation: The case of U.S. pharmaceutical companies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 30(C), pages 153-171.
    7. Marianna Lyra, 2010. "Heuristic Strategies in Finance – An Overview," Working Papers 045, COMISEF.
    8. Juan Carlos Gutierrez Betancur, 2017. "Robust Estimation of beta and the hedging ratio in Stock Index Futures In the Integrated Latin American Market," Revista Ecos de Economía, Universidad EAFIT, vol. 21(44), pages 37-71, June.
    9. Insana, Alessandra, 2022. "Does systematic risk change when markets close? An analysis using stocks’ beta," Economic Modelling, Elsevier, vol. 109(C).
    10. Chochola, Ondřej & Hušková, Marie & Prášková, Zuzana & Steinebach, Josef G., 2013. "Robust monitoring of CAPM portfolio betas," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 374-395.

    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:spr:sprchp:978-3-540-77958-2_8. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.