Deregulated Wholesale Electricity Prices in Italy: An Empirical Analysis
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In this paper we analyze a time series of daily average prices in the Italian electricity market, which started to operate as a Pool in April 2004. Our objective is to model the high degree of autocorrelation and the multiple seasonalities in electricity prices. We use periodic time series models with GARCH disturbances and leptokurtic distributions and compare their performance with more classical ARMA-GARCH processes. The within-year seasonal variation is modelled using the low-frequency components of physical quantities, which are very regular throughout the sample. Our results reveal that much of the variability in the price series is explained by the interactions between deterministic multiple seasonalities. Periodic AR-GARCH models seem to perform quite well in mimicking the features of the stochastic part of the price process.
KeywordsElectricity auctions Periodic time series Conditional heteroskedasticity Multiple seasonalities
JEL ClassificationC22 D44 L94 Q40
This paper is part of a research program on the regulation of the electricity sector in Italy. We would like to thank the University of MilanBicocca for financing the research with a FAR 2003 (ex 60%) grant and MURST for a PRIN 2004 grant.
We thank REF (Researches in Economics and Finance, Milan, www.refonline.it/eng/) for providing us with the Italian data, and particularly Pia Saraceno, Claudia Checchi, Edoardo Settimio and Mara Zanini for comments and suggestions. All other data discussed in the paper have been obtained from electronic publications downloaded from the web site of the International Energy Agency (www.iea.org/Textbase/stats/rd.asp).
An earlier version of this paper was presented at the SixtyFirst International Atlantic Economic Conference. We thank Peter van der Hoek, Kinga Mazur, Martin McGuire and Michael Ye for useful comments.
- Bhanot, K. (2000). Behaviour of power prices: Implications for the valuation and hedging of financial contracts. Journal of Risk, 2(3), 43–62, Spring.Google Scholar
- Bollerslev, T., & Ghysels, E. (1994). On periodic autoregressive conditional heteroskedasticity. September 1994, CIRANO Scientific Series No. 94s-3, Montreal.Google Scholar
- Deidersen, J., & Trück, S. (2002). Energy price dynamics. Quantitative studies and stochastic processes. Technical Report TR-ISWM-12/2002, University of Karlsruhe.Google Scholar
- Doornik, J. A., & Hansen, H. (1994). A practical test for univariate and multivariate normality. Working Paper, Nuffield College, Oxford, November.Google Scholar
- Escribano, A., Peña, J. I., & Villaplana, P. (2002). Modelling electricity prices: international evidence. Economic Series 08, Working Paper 02-27, Universidad Carlos III de Madrid, June.Google Scholar
- Franses, P. H., & Paap, R. (2004). Periodic Time Series Models. Oxford, UK: Oxford University Press.Google Scholar
- Hamilton, J. D. (1994). Time Series Analysis. Princeton, NJ: Princeton University Press.Google Scholar
- Jones, R. H., & Brelsford, W. M. (1967). Time series with periodic structure. Biometrika, 54(3–4), 403–408, December.Google Scholar
- Koopman, S. J., Ooms, M., & Carnero, M. A. (2007). Periodic seasonal reg-ARFIMA-GARCH models for daily electricity spot prices. Journal of the American Statistical Association, 102(477), 16–27(12), March.Google Scholar
- Pagano, M. (1978) On periodic and multiple autoregressions. Annals of Statistics, 6(6), 1310–1317, November.Google Scholar
- Tiao, G. C., & Grupe, M. R. (1980). Hidden periodic autoregressive-moving average models in time series data. Biometrika, 67(2), 365–373, August.Google Scholar