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Robust Estimation and Forecasting of the Capital Asset Pricing Model

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  • Guorui Bian

    (Department of Statistics, East China Normal University)

  • Michael McAleer

    (Erasmus University Rotterdam, Tinbergen Institute, The Netherlands, and Institute of Economic Research, Kyoto University)

  • Wing-Keung Wong

    (Department of Economics, Hong Kong Baptist University)

Abstract

In this paper, we develop a modified maximum likelihood (MML) estimator for the multiple linear regression model with underlying student t distribution. We obtain the closed form of the estimators, derive the asymptotic properties, and demonstrate that the MML estimator is more appropriate for estimating the parameters of the Capital Asset Pricing Model by comparing its performance with least squares estimators (LSE) on the monthly returns of US portfolios. The empirical results reveal that the MML estimators are more efficient than LSE in terms of the relative efficiency of one-step-ahead forecast mean square error in small samples.

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Bibliographic Info

Paper provided by Kyoto University, Institute of Economic Research in its series KIER Working Papers with number 735.

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Length: 24pages
Date of creation: Oct 2010
Date of revision:
Handle: RePEc:kyo:wpaper:735

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Keywords: Maximum likelihood estimators; Modified maximum likelihood estimators; Student t family; Capital asset pricing model; Robustness.;

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