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Forecasting with k-Factor Gegenbauer Processes: Theory and Applications

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  • Ferrara, Laurent
  • Guegan, Dominique

Abstract

This paper deals with the k-factor extension of the long memory Gegenbauer process proposed by Gray et al. (1989). We give the analytic expression of the prediction function derived from this long memory process and provide the h-step-ahead prediction error when parameters are either known or estimated. We investigate the predictive ability of the k-factor Gegenbauer model on real data of urban transport traffic in the Paris area, in comparison with other short- and long-memory models. Copyright © 2001 by John Wiley & Sons, Ltd.

Suggested Citation

  • Ferrara, Laurent & Guegan, Dominique, 2001. "Forecasting with k-Factor Gegenbauer Processes: Theory and Applications," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(8), pages 581-601, December.
  • Handle: RePEc:jof:jforec:v:20:y:2001:i:8:p:581-601
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    1. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
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