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A Forty Year Assessment of Forecasting the Boat Race

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  • Geert Mesters

    (VU University Amsterdam)

  • Siem Jan Koopman

    (VU University Amsterdam)

Abstract

We study the forecasting of the yearly outcome of the Boat Race between Cambridge and Oxford. We compare the relative performance of different dynamic models for forty years of forecasting. Each model is defined by a binary density conditional on a latent signal that is specified as a dynamic stochastic process with fixed predictors. The out-of-sample predictive ability of the models is compared between each other by using a variety of loss functions and predictive ability tests. We find that the model with its latent signal specified as an autoregressive process cannot be outperformed by the other specifications. This model is able to correctly forecast 30 out of 40 outcomes of the Boat Race.

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Bibliographic Info

Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 12-110/III.

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Date of creation: 23 Oct 2012
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Handle: RePEc:dgr:uvatin:20120110

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Web page: http://www.tinbergen.nl

Related research

Keywords: Binary time series; Predictive ability; Non-Gaussian state space model;

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  1. Todd E. Clark & Michael W. McCracken, 1999. "Tests of equal forecast accuracy and encompassing for nested models," Research Working Paper, Federal Reserve Bank of Kansas City 99-11, Federal Reserve Bank of Kansas City.
  2. Barbara Rossi & Atsushi Inoue, 2012. "Out-of-sample forecast tests robust to the choice of window size," Economics Working Papers, Department of Economics and Business, Universitat Pompeu Fabra 1404, Department of Economics and Business, Universitat Pompeu Fabra.
  3. Francis X. Diebold & Jose A. Lopez, 1995. "Forecast evaluation and combination," Research Paper, Federal Reserve Bank of New York 9525, Federal Reserve Bank of New York.
  4. Koopman, Siem Jan & Shephard, Neil & Creal, Drew, 2009. "Testing the assumptions behind importance sampling," Journal of Econometrics, Elsevier, Elsevier, vol. 149(1), pages 2-11, April.
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