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

  • Dominique Guegan

    ()

    (IDHE - Institutions et Dynamiques Historiques de l'Economie - CNRS : UMR8533 - Université Panthéon-Sorbonne - Paris I - Université Paris VIII Vincennes-Saint Denis - Université de Paris X - Nanterre - École normale supérieure de Cachan - ENS Cachan)

  • Abdou Kâ Diongue

    ()

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

  • Bertrand Vignal

    (EDF R&D - EDF)

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.

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Paper provided by HAL in its series Post-Print with number halshs-00188533.

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Date of creation: 2004
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Publication status: Published - Presented, Probabilistic methods applied to power systems, 2004, United States
Handle: RePEc:hal:journl:halshs-00188533
Note: View the original document on HAL open archive server: http://halshs.archives-ouvertes.fr/halshs-00188533/en/
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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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