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Robust forecasting with exponential and Holt-Winters smoothing


  • Sarah Gelper

    (Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, the Netherlands)

  • Roland Fried

    (Department of Statistics, University of Dortmund, Dortmund, Germany)

  • Christophe Croux

    (Faculty of Business and Economics, Katholieke Universiteit Leuven, Leuven, Belgium)


Robust versions of the exponential and Holt-Winters smoothing method for forecasting are presented. They are suitable for forecasting univariate time series in the presence of outliers. The robust exponential and Holt-Winters smoothing methods are presented as recursive updating schemes that apply the standard technique to pre-cleaned data. Both the update equation and the selection of the smoothing parameters are robustified. A simulation study compares the robust and classical forecasts. The presented method is found to have good forecast performance for time series with and without outliers, as well as for fat-tailed time series and under model misspecification. The method is illustrated using real data incorporating trend and seasonal effects. Copyright © 2009 John Wiley & Sons, Ltd.

Suggested Citation

  • Sarah Gelper & Roland Fried & Christophe Croux, 2010. "Robust forecasting with exponential and Holt-Winters smoothing," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(3), pages 285-300.
  • Handle: RePEc:jof:jforec:v:29:y:2010:i:3:p:285-300
    DOI: 10.1002/for.1125

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    References listed on IDEAS

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