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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 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)

  • Bertrand Vignal

    ()
    (EDF - EDF - Recherche et Développement)

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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Bibliographic Info

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

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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

Note: View the original document on HAL open archive server: http://halshs.archives-ouvertes.fr/halshs-00307606
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Keywords: Conditional mean - conditional variance - forecast - electricity prices - GIGARCH process;

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References

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  1. Dominique Guegan, 2005. "How can we Define the Concept of Long Memory? An Econometric Survey," Econometric Reviews, Taylor & Francis Journals, Taylor & Francis Journals, vol. 24(2), pages 113-149.
  2. Dominique Guegan, 2003. "A prospective study of the k-factor Gegenbauer processes with heteroscedastic errors and an application to inflation rates," Post-Print, HAL halshs-00201314, HAL.
  3. Dominique Guegan, 2004. "How Can We Define the Long Memory Concept? An Econometric Survey," Econometric Society 2004 Australasian Meetings, Econometric Society 361, Econometric Society.
  4. Ferrara, Laurent & Guegan, Dominique, 2001. "Forecasting with k-Factor Gegenbauer Processes: Theory and Applications," Journal of Forecasting, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 20(8), pages 581-601, December.
  5. Dominique Guegan & Abdou Kâ Diongue & Bertrand Vignal, 2004. "A k- factor GIGARCH process : estimation and application to electricity market spot prices," Post-Print, HAL halshs-00188533, HAL.
  6. 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, American Statistical Association, vol. 102, pages 16-27, March.
  7. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 20(1), pages 134-44, January.
  8. Misiorek Adam & Trueck Stefan & Weron Rafal, 2006. "Point and Interval Forecasting of Spot Electricity Prices: Linear vs. Non-Linear Time Series Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, De Gruyter, vol. 10(3), pages 1-36, September.
  9. Conejo, Antonio J. & Contreras, Javier & Espinola, Rosa & Plazas, Miguel A., 2005. "Forecasting electricity prices for a day-ahead pool-based electric energy market," International Journal of Forecasting, Elsevier, Elsevier, vol. 21(3), pages 435-462.
  10. Abdou Kâ Diongue & Dominique Guegan, 2008. "The k-factor Gegenbauer asymmetric Power GARCH approach for modelling electricity spot price dynamics," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers), HAL halshs-00259225, HAL.
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Citations

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Cited by:
  1. Foued Saâdaoui, 2013. "The Price and Trading Volume Dynamics Relationship in the EEX Power Market: A Wavelet Modeling," Computational Economics, Society for Computational Economics, Society for Computational Economics, vol. 42(1), pages 47-69, June.
  2. repec:hal:journl:halshs-00259193 is not listed on IDEAS
  3. Liu, Heping & Shi, Jing, 2013. "Applying ARMA–GARCH approaches to forecasting short-term electricity prices," Energy Economics, Elsevier, Elsevier, vol. 37(C), pages 152-166.
  4. Rahimiyan, Morteza & Morales, Juan M. & Conejo, Antonio J., 2011. "Evaluating alternative offering strategies for wind producers in a pool," Applied Energy, Elsevier, Elsevier, vol. 88(12), pages 4918-4926.
  5. Gianfreda, Angelica & Grossi, Luigi, 2012. "Forecasting Italian electricity zonal prices with exogenous variables," Energy Economics, Elsevier, Elsevier, vol. 34(6), pages 2228-2239.
  6. repec:hal:journl:halshs-00185370 is not listed on IDEAS
  7. Amjady, Nima & Keynia, Farshid, 2010. "A new spinning reserve requirement forecast method for deregulated electricity markets," Applied Energy, Elsevier, Elsevier, vol. 87(6), pages 1870-1879, June.
  8. Tryggvi Jónsson & Pierre Pinson & Henrik Madsen & Henrik Aalborg Nielsen, 2014. "Predictive Densities for Day-Ahead Electricity Prices Using Time-Adaptive Quantile Regression," Energies, MDPI, Open Access Journal, vol. 7(9), pages 5523-5547, August.
  9. Erdogdu, Erkan, 2010. "A paper on the unsettled question of Turkish electricity market: Balancing and settlement system (Part I)," Applied Energy, Elsevier, Elsevier, vol. 87(1), pages 251-258, January.
  10. Lin, Whei-Min & Gow, Hong-Jey & Tsai, Ming-Tang, 2010. "An enhanced radial basis function network for short-term electricity price forecasting," Applied Energy, Elsevier, Elsevier, vol. 87(10), pages 3226-3234, October.
  11. repec:hal:journl:halshs-00375531 is not listed on IDEAS
  12. Tan, Zhongfu & Zhang, Jinliang & Wang, Jianhui & Xu, Jun, 2010. "Day-ahead electricity price forecasting using wavelet transform combined with ARIMA and GARCH models," Applied Energy, Elsevier, Elsevier, vol. 87(11), pages 3606-3610, November.

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