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Forecasting electricity spot market prices with a k-factor GIGARCH process

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Author Info
Abdou Kâ Diongue () (UFR SAT - Université Gaston Berger - Université Gaston Berger de Saint-Louis)
Dominique Guegan () (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I, EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris)
Bertrand Vignal () (EDF - EDF - Recherche et Développement)

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Abstract

In this article, we investigate conditional mean and variance forecasts using a dynamic model following a k-factor GIGARCH process. We are particularly interested in calculating the conditional variance of the prediction error. We apply this method to electricity prices and test spot prices forecasts until one month ahead forecast. We conclude that the k-factor GIGARCH process is a suitable tool to forecast spot prices, using the classical RMSE criteria.

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Paper provided by HAL in its series Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) with number halshs-00307606_v1.

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Date of creation: Apr 2009
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Publication status: Published, Applied Energy, 2009, 86, 4, 505-510
Handle: RePEc:hal:cesptp:halshs-00307606_v1

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Keywords: Conditional mean - conditional variance - forecast - electricity prices - GIGARCH process;

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  1. Koopman, Siem Jan & Ooms, Marius & Carnero, M. Angeles, 2007. "Periodic Seasonal Reg-ARFIMAGARCH Models for Daily Electricity Spot Prices," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 16-27, March. [Downloadable!] (restricted)
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This page was last updated on 2009-11-27.

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