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Misspecification testing and robust estimation of the market model: estimating betas for the FT-SE industry baskets

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  • Terence Mills
  • J. Andrew Coutts
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    Abstract

    Using daily data on the London Stock Exchange's FT-SE industry baskets, this paper subjects the market model to a set of rigorous specification tests designed to assess its statistical adequacy in the face of possible model non-linearity and autocorrelation, heteroscedasticity and, in particular, non-normality of residuals. It then utilizes robust methods of estimation to provide valid estimates of the model's parameters in the face of such misspecification. It is found that robust estimation usually provides betas that are lower than those estimated by conventional ordinary least squares.

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    File URL: http://www.tandfonline.com/doi/abs/10.1080/13518479600000012
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    Bibliographic Info

    Article provided by Taylor & Francis Journals in its journal The European Journal of Finance.

    Volume (Year): 2 (1996)
    Issue (Month): 4 ()
    Pages: 319-331

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    Handle: RePEc:taf:eurjfi:v:2:y:1996:i:4:p:319-331

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    Related research

    Keywords: industry baskets; market model; misspecification; robust estimation;

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    Cited by:
    1. Raphael Markellos & Terence Mills, 2003. "Asset pricing dynamics," The European Journal of Finance, Taylor & Francis Journals, vol. 9(6), pages 533-556.
    2. Groenewold, Nicolaas & Fraser, Patricia, 2001. "Tests of asset-pricing models: how important is the iid-normal assumption?," Journal of Empirical Finance, Elsevier, vol. 8(4), pages 427-449, September.
    3. J. Andrew Coutts & Terence Mills & Jennifer Roberts, 1997. "Time series and cross-section parameter stability in the market model: the implications for event studies," The European Journal of Finance, Taylor & Francis Journals, vol. 3(3), pages 243-259.
    4. Groenewold, Nicolaas & Fraser, Patricia, 2002. "Violation of the iid-normal assumption: Effects on tests of asset-pricing models using Australian data," International Review of Financial Analysis, Elsevier, vol. 11(4), pages 491-510.

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