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.
- Electricity auctions,
- Periodic time series,
- Conditional heteroskedasticity,
- Multiple seasonalities
Available at: http://works.bepress.com/matteo_pelagatti/2/