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A k- factor GIGARCH process : estimation and application to electricity market spot prices

Author

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  • Dominique Guegan

    () (IDHE - Institutions et Dynamiques Historiques de l'Economie - ENS Cachan - École normale supérieure - Cachan - UP1 - Université Panthéon-Sorbonne - UP8 - Université Paris 8, Vincennes-Saint-Denis - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique)

  • Abdou Kâ Diongue

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

  • Bertrand Vignal

    (EDF - EDF)

Abstract

Some crucial time series of market data, such as electricity spot prices, exhibit long memory, in the sense of slowly-decaying correlations combined with heteroscedasticity. To e able to model such a behaviour, we consider the k-factor GIGARCH process and we propose two methods to address the related parameter estimation problem. For each method, we develop the asymptotic theory for this estimation.

Suggested Citation

  • Dominique Guegan & Abdou Kâ Diongue & Bertrand Vignal, 2004. "A k- factor GIGARCH process : estimation and application to electricity market spot prices," Post-Print halshs-00188533, HAL.
  • Handle: RePEc:hal:journl:halshs-00188533
    Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-00188533
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    File URL: https://halshs.archives-ouvertes.fr/halshs-00188533/document
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    References listed on IDEAS

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    1. Cheung, Yin-Wong & Diebold, Francis X., 1994. "On maximum likelihood estimation of the differencing parameter of fractionally-integrated noise with unknown mean," Journal of Econometrics, Elsevier, vol. 62(2), pages 301-316, June.
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    Cited by:

    1. Diongue, Abdou Kâ & Guégan, Dominique & Vignal, Bertrand, 2009. "Forecasting electricity spot market prices with a k-factor GIGARCH process," Applied Energy, Elsevier, vol. 86(4), pages 505-510, April.

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