IDEAS home Printed from https://ideas.repec.org/p/bca/bocawp/10-36.html
   My bibliography  Save this paper

Bank Testing Linear Factor Pricing Models with Large Cross-Sections: A Distribution-Free Approach

Author

Listed:
  • Sermin Gungor
  • Richard Luger

Abstract

We develop a finite-sample procedure to test the beta-pricing representation of linear factor pricing models that is applicable even if the number of test assets is greater than the length of the time series. Our distribution-free framework leaves open the possibility of unknown forms of non-normalities, heteroskedasticity, time-varying correlations, and even outliers in the asset returns. The power of the proposed test procedure increases as the time-series lengthens and/or the cross-section becomes larger. This stands in sharp contrast to the usual tests that lose power or may not even be computable if the cross-section is too large. Finally, we revisit the CAPM and the Fama-French three factor model. Our results strongly support the mean-variance efficiency of the market portfolio.

Suggested Citation

  • Sermin Gungor & Richard Luger, 2010. "Bank Testing Linear Factor Pricing Models with Large Cross-Sections: A Distribution-Free Approach," Staff Working Papers 10-36, Bank of Canada.
  • Handle: RePEc:bca:bocawp:10-36
    as

    Download full text from publisher

    File URL: https://www.bankofcanada.ca/wp-content/uploads/2010/12/wp10-36.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Affleck-Graves, John & McDonald, Bill, 1989. " Nonnormalities and Tests of Asset Pricing Theories," Journal of Finance, American Finance Association, vol. 44(4), pages 889-908, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bao, Te & Diks, Cees & Li, Hao, 2018. "A generalized CAPM model with asymmetric power distributed errors with an application to portfolio construction," Economic Modelling, Elsevier, vol. 68(C), pages 611-621.
    2. Pesaran, M. Hashem & Yamagata, Takashi, 2012. "Testing CAPM with a Large Number of Assets," IZA Discussion Papers 6469, Institute of Labor Economics (IZA).
    3. Gungor, Sermin & Luger, Richard, 2015. "Bootstrap Tests Of Mean-Variance Efficiency With Multiple Portfolio Groupings," L'Actualité Economique, Société Canadienne de Science Economique, vol. 91(1-2), pages 35-65, Mars-Juin.
    4. Jean-Marie Dufour & Lynda Khalaf & Marie-Claude Beaulieu, 2010. "Multivariate residual-based finite-sample tests for serial dependence and ARCH effects with applications to asset pricing models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(2), pages 263-285.
    5. Mohan D. Pant & Todd C. Headrick, 2017. "Simulating Uniform- and Triangular- Based Double Power Method Distributions," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 6(1), pages 1-1.
    6. Jean‐Marie Dufour & Lynda Khalaf & Marie‐Claude Beaulieu, 2003. "Exact Skewness–Kurtosis Tests for Multivariate Normality and Goodness‐of‐Fit in Multivariate Regressions with Application to Asset Pricing Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(s1), pages 891-906, December.
    7. Marie-Claude BEAULIEU & Jean-Marie DUFOUR & Lynda KHALAF, 2002. "Testing Mean-Variance Efficiency In Capm With Possibly Non-Gaussian Errors : An Exact Simulation-Based Approach," Cahiers de recherche 17-2002, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    8. Ravikumar, B. & Ray, Surajit & Savin, N.E., 1999. "CAPM Reconsidered: A Robust Finite Sample Evaluation," Working Papers 99-04, University of Iowa, Department of Economics.
    9. Sermin Gungor & Richard Luger, 2016. "Multivariate Tests of Mean-Variance Efficiency and Spanning With a Large Number of Assets and Time-Varying Covariances," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(2), pages 161-175, April.
    10. Fama, Eugene F. & French, Kenneth R., 1997. "Industry costs of equity," Journal of Financial Economics, Elsevier, vol. 43(2), pages 153-193, February.
    11. Xin Ling, 2017. "Normality of stock returns with event time clocks," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 57, pages 277-298, April.
    12. Stergios B. Fotopoulos & Venkata K. Jandhyala & Alex Paparas, 2021. "Some Properties of the Multivariate Generalized Hyperbolic Laws," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(1), pages 187-205, February.
    13. David Wozabal, 2012. "A framework for optimization under ambiguity," Annals of Operations Research, Springer, vol. 193(1), pages 21-47, March.
    14. Qiao, Zhuo & Wang, Yan & Lam, Keith S.K., 2022. "New evidence on Bayesian tests of global factor pricing models," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 160-172.
    15. Harvey, Campbell R. & Zhou, Guofu, 1993. "International asset pricing with alternative distributional specifications," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 107-131, June.
    16. Andrei ANGHEL & Dalina DUMITRESCU & Cristiana TUDOR, 2015. "Modeling Portfolio Returns On Bucharest Stock Exchange Using The Fama-French Multifactor Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 22-46, March.
    17. Pin-Huang Chou, 1996. "Using Bootstrap to Test Mean-Variance Efficiency of a Given Portfolio," Finance 9609002, University Library of Munich, Germany.
    18. Tu, Jun & Zhou, Guofu, 2004. "Data-generating process uncertainty: What difference does it make in portfolio decisions?," Journal of Financial Economics, Elsevier, vol. 72(2), pages 385-421, May.
    19. Jarrow, Robert & Teo, Melvyn & Tse, Yiu Kuen & Warachka, Mitch, 2012. "An improved test for statistical arbitrage," Journal of Financial Markets, Elsevier, vol. 15(1), pages 47-80.
    20. N. Groenewold & P. Fraser, 1999. "Violation of the IID-Normal Assumption: Effects on tests of asset-pricing models using Australian data," Economics Discussion / Working Papers 99-12, The University of Western Australia, Department of Economics.

    More about this item

    Keywords

    Econometric and statistical methods; Financial markets;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • 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:bca:bocawp:10-36. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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/bocgvca.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.