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Forecasting wholesale electricity prices: A review of time series models

  • Weron, Rafal

In this paper we assess the short-term forecasting power of different time series models in the electricity spot market. We calibrate autoregression (AR) models, including specifications with a fundamental (exogenous) variable - system load, to California Power Exchange (CalPX) system spot prices. Then we evaluate their point and interval forecasting performance in relatively calm and extremely volatile periods preceding the market crash in winter 2000/2001. In particular, we test which innovations distributions/processes - Gaussian, GARCH, heavy-tailed (NIG, alpha-stable) or non-parametric - lead to best predictions.

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File URL: http://mpra.ub.uni-muenchen.de/21299/1/MPRA_paper_21299.pdf
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 21299.

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Date of creation: 2009
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Handle: RePEc:pra:mprapa:21299
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  1. Peter F. Christoffersen & Francis X. Diebold, 1997. "How Relevant is Volatility Forecasting for Financial Risk Management?," Center for Financial Institutions Working Papers 97-45, Wharton School Center for Financial Institutions, University of Pennsylvania.
  2. 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.
  3. 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.
  4. Giulio Bottazzi & Sandro Sapio & Angelo Secchi, 2004. "Some Statistical Investigations on the Nature and Dynamics of Electricity Prices," LEM Papers Series 2004/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  5. Peter Carr & Helyette Geman, 2002. "The Fine Structure of Asset Returns: An Empirical Investigation," The Journal of Business, University of Chicago Press, vol. 75(2), pages 305-332, April.
  6. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
  7. Weron, Rafał, 2004. "Computationally intensive Value at Risk calculations," Papers 2004,32, Humboldt-Universität Berlin, Center for Applied Statistics and Economics (CASE).
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