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Semiparametric (Distribution-Free) Testing of the Expectations Hypothesis in a Parimutuel Gambling Market

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  • Goodwin, Barry K

Abstract

The expectations hypothesis maintains that a current forward or futures price should be an unbiased forecast of the expected future price. This paper tests the expectations hypothesis in the parimutuel gambling market for greyhound racing parametric and semiparametric estimators. Parimutuel gambling markets are similar to speculative asset markets in many regards. Conventional maximum likelihood tests of asset pricing require a priori specification of the statistical distribution governing agents' expectations. Distributional misspecification may bias conventional tests. The semiparametric estimators applied in this paper overcome these problems and, in addition, maintain consistency under heteroscedasticity. The results reject the expectations hypothesis.

Suggested Citation

  • Goodwin, Barry K, 1996. "Semiparametric (Distribution-Free) Testing of the Expectations Hypothesis in a Parimutuel Gambling Market," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(4), pages 487-496, October.
  • Handle: RePEc:bes:jnlbes:v:14:y:1996:i:4:p:487-96
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    Cited by:

    1. Ji, Yonggang & Lin, Nan & Zhang, Baoxue, 2012. "Model selection in binary and tobit quantile regression using the Gibbs sampler," Computational Statistics & Data Analysis, Elsevier, vol. 56(4), pages 827-839.

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