Periodic seasonal Reg-ARFIMA-GARCH models for daily electricity spot prices

Speaker:  Siem Jan Koopman - VU University Amsterdam
  Friday, June 19, 2009 at 1:00 PM Biblioteca DSE - Palazzina 32, ex Caserma Passalacqua

Novel periodic extensions of dynamic long memory regression models with autoregressive

conditional heteroskedastic errors are considered for the analysis of daily electricity spot

prices. The parameters of the model with mean and variance specifications are estimated

simultaneously by the method of approximate maximum likelihood. The methods are

implemented for time series of 1

, 200 to 4, 400 daily price observations. Apart from persistence,

heteroskedasticity and extreme observations in prices, a novel empirical finding is

the importance of day-of-the-week periodicity in the autocovariance function of electricity

spot prices. In particular, daily log prices from the Nord Pool power exchange of Norway

are modeled effectively by our framework, which is also extended with explanatory

variables. For the daily log prices of three European emerging electricity markets (EEX

in Germany, Powernext in France, APX in The Netherlands), which are less persistent,

periodicity is also highly significant.

Documents
Title Format  (Language, Size, Publication date)
paper  pdfpdf (it, 445 KB, 18/05/09)

Programme Director
Angelo Zago

Publication date
May 18, 2009

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