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

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Author Info

  • Abdou Kâ Diongue

    ()
    (Université Gaston Berger de Saint-Louis)

  • Dominique Guégan

    ()
    (Centre d'Economie de la Sorbonne)

  • Bertrand Vignal

    ()
    (EDF)

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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File URL: ftp://mse.univ-paris1.fr/pub/mse/CES2007/B07058.pdf
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Bibliographic Info

Paper provided by Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne in its series Documents de travail du Centre d'Economie de la Sorbonne with number b07058.

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Length: 21 pages
Date of creation: Nov 2007
Date of revision: Nov 2009
Handle: RePEc:mse:cesdoc:b07058

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

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References

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  1. Abdou Kâ Diongue & Dominique Guegan, 2008. "The k-factor Gegenbauer asymmetric Power GARCH approach for modelling electricity spot price dynamics," Documents de travail du Centre d'Economie de la Sorbonne b08013, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
  2. Ferrara, Laurent & Guegan, Dominique, 2001. "Forecasting with k-Factor Gegenbauer Processes: Theory and Applications," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(8), pages 581-601, December.
  3. Dominique Guegan, 2005. "How can we Define the Concept of Long Memory? An Econometric Survey," Econometric Reviews, Taylor & Francis Journals, vol. 24(2), pages 113-149.
  4. 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, vol. 10(3), pages 1-36, September.
  5. 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.
  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, vol. 102, pages 16-27, March.
  7. Dominique Guegan, 2004. "How Can We Define the Long Memory Concept? An Econometric Survey," Econometric Society 2004 Australasian Meetings 361, Econometric Society.
  8. 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.
  9. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
  10. 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, vol. 21(3), pages 435-462.
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Cited by:
  1. Erdogdu, Erkan, 2010. "A paper on the unsettled question of Turkish electricity market: Balancing and settlement system (Part I)," MPRA Paper 19090, University Library of Munich, Germany.
  2. Amjady, Nima & Keynia, Farshid, 2010. "A new spinning reserve requirement forecast method for deregulated electricity markets," Applied Energy, Elsevier, vol. 87(6), pages 1870-1879, June.
  3. repec:hal:journl:halshs-00185370 is not listed on IDEAS
  4. repec:hal:journl:halshs-00375531 is not listed on IDEAS
  5. repec:hal:journl:halshs-00259193 is not listed on IDEAS
  6. Foued Saâdaoui, 2013. "The Price and Trading Volume Dynamics Relationship in the EEX Power Market: A Wavelet Modeling," Computational Economics, Society for Computational Economics, vol. 42(1), pages 47-69, June.
  7. 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, vol. 87(11), pages 3606-3610, November.
  8. Rahimiyan, Morteza & Morales, Juan M. & Conejo, Antonio J., 2011. "Evaluating alternative offering strategies for wind producers in a pool," Applied Energy, Elsevier, vol. 88(12), pages 4918-4926.
  9. Angelica Gianfreda & Luigi Grossi, 2011. "Forecasting Italian Electricity Zonal Prices with Exogenous Variables," Working Papers 01/2011, University of Verona, Department of Economics.
  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, vol. 87(10), pages 3226-3234, October.
  11. Liu, Heping & Shi, Jing, 2013. "Applying ARMA–GARCH approaches to forecasting short-term electricity prices," Energy Economics, Elsevier, vol. 37(C), pages 152-166.

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