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Estimation of k-Factor Gigarch Process: A Monte Carlo Study

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  • Diongue Abdou Ka

    (UFR SAT - Université Gaston Berger de Saint-Louis Sénégal - Université Gaston Berger de Saint-Louis)

  • Dominique Guegan

    ()
    (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris I - Panthéon-Sorbonne, EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris)

Abstract

In this paper, we discuss the parameter estimation for a k-factor generalized long memory processwith 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, using four different conditional distribution functions.

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Bibliographic Info

Paper provided by HAL in its series Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) with number halshs-00375758.

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Date of creation: 2008
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Publication status: Published, Communications in Statistics - Simulations and Computations, 2008, 37, 10, 2037-2049
Handle: RePEc:hal:cesptp:halshs-00375758

Note: View the original document on HAL open archive server: http://halshs.archives-ouvertes.fr/halshs-00375758
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Keywords: Long memory ; Gegenbauer polynomial ; heteroskedasticity ; Conditional Sum of Squares ; Whittle estimation;

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  1. Abdou Kâ Diongue & Dominique Guegan, 2004. "Estimating parameters for a k-GIGARCH process," Post-Print halshs-00188531, HAL.
  2. Granger, C. W. J., 1980. "Long memory relationships and the aggregation of dynamic models," Journal of Econometrics, Elsevier, Elsevier, vol. 14(2), pages 227-238, October.
  3. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, Econometric Society, vol. 59(2), pages 347-70, March.
  4. Liudas Giraitis & Peter M Robinson, 2000. "Whittle Estimation of ARCH Models," STICERD - Econometrics Paper Series, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE /2000/406, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  5. Fernández, C. & Steel, M.F.J., 1996. "On Bayesian Modelling of Fat Tails and Skewness," Discussion Paper, Tilburg University, Center for Economic Research 1996-58, Tilburg University, Center for Economic Research.
  6. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
  7. 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.
  8. Hansen, B.E., 1992. "Autoregressive Conditional Density Estimation," RCER Working Papers 322, University of Rochester - Center for Economic Research (RCER).
  9. 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.
  10. Peiro, Amado, 1999. "Skewness in financial returns," Journal of Banking & Finance, Elsevier, Elsevier, vol. 23(6), pages 847-862, June.
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