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Order series method for forecasting non-Gaussian time series


  • Ming-De Chuang

    (Endemic Species Research Institute, Nantou, Taiwan, ROC)

  • Gwo-Hsing Yu

    (Tamkang University, Taipei, Taiwan, ROC)


A new forecasting non-Gaussian time series method based on order series transformation properties has been proposed. The proposed method improves Yu's method without using Hermite polynomial expansion to process nonlinear instantaneous transformations and provides acceptable forecasting accuracy. Copyright © 2007 John Wiley & Sons, Ltd.

Suggested Citation

  • Ming-De Chuang & Gwo-Hsing Yu, 2007. "Order series method for forecasting non-Gaussian time series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(4), pages 239-250.
  • Handle: RePEc:jof:jforec:v:26:y:2007:i:4:p:239-250 DOI: 10.1002/for.1024

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    References listed on IDEAS

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    7. Hansen, Bruce E, 1994. "Autoregressive Conditional Density Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(3), pages 705-730, August.
    8. Christoffersen, Peter F & Diebold, Francis X, 1996. "Further Results on Forecasting and Model Selection under Asymmetric Loss," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(5), pages 561-571, Sept.-Oct.
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    10. Anthony Tay & Kenneth F. Wallis, 2000. "Density Forecasting: A Survey," Econometric Society World Congress 2000 Contributed Papers 0370, Econometric Society.
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