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Estimation of k-factor GIGARCH process : a Monte Carlo study


  • Abdou Kâ Diongue

    () (UFR SAT - Université Gaston Berger de Saint-Louis Sénégal, School of Economics and Finance - QUT - Queensland University of Technology [Brisbane])

  • Dominique Guegan

    () (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics)


In this paper, we discuss the parameter estimation for a k-factor generalized long memory process with conditionally heteroskedastic noise. Two estimation methods are proposed. The first method is based on the conditional distribution of the process and the second is obtained as an extension of Whittle's estimation approach. For comparison purposes, Monte Carlo simulations are used to evaluate the finite sample performance of these estimation techniques.

Suggested Citation

  • Abdou Kâ Diongue & Dominique Guegan, 2008. "Estimation of k-factor GIGARCH process : a Monte Carlo study," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00235179, HAL.
  • Handle: RePEc:hal:cesptp:halshs-00235179
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    References listed on IDEAS

    1. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    2. Abdou Kâ Diongue & Dominique Guegan, 2004. "Estimating parameters for a k-GIGARCH process," Post-Print halshs-00188531, HAL.
    3. Granger, C. W. J., 1980. "Long memory relationships and the aggregation of dynamic models," Journal of Econometrics, Elsevier, vol. 14(2), pages 227-238, October.
    4. M. C. Jones & M. J. Faddy, 2003. "A skew extension of the "t"-distribution, with applications," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(1), pages 159-174.
    5. Dominique Guegan, 2003. "A prospective study of the k-factor Gegenbauer processes with heteroscedastic errors and an application to inflation rates," Post-Print halshs-00201314, HAL.
    6. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    7. Giraitis, Liudas & Robinson, Peter M., 2001. "Whittle Estimation Of Arch Models," Econometric Theory, Cambridge University Press, vol. 17(03), pages 608-631, June.
    8. 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.
    9. Peiro, Amado, 1999. "Skewness in financial returns," Journal of Banking & Finance, Elsevier, vol. 23(6), pages 847-862, June.
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    Cited by:

    1. Heni Boubaker, 2015. "Wavelet Estimation of Gegenbauer Processes: Simulation and Empirical Application," Computational Economics, Springer;Society for Computational Economics, vol. 46(4), pages 551-574, December.

    More about this item


    Whittle estimation; Long memory; Gegenbauer polynomial; heteeroskedasticity; conditional sum of squares; Whittle estimation.; Processus longue mémoire; hétéroscédasticité; estimation; Whittle.;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods


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