Periodic Seasonal REG-ARFIMA-GARCH Models for Daily Electricity Spot Prices

Journal of the American Statistical Association, Vol. 102, No. 477, pp. 16-27, March 2007

Posted: 9 Jul 2007

See all articles by Siem Jan Koopman

Siem Jan Koopman

Vrije Universiteit Amsterdam - School of Business and Economics; Tinbergen Institute; Aarhus University - CREATES

Marius Ooms

VU University Amsterdam - Department of Econometrics

M. Angeles Carnero

Universidad de Alicante - Department of Economic Analysis

Abstract

Povel 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.

Keywords: Autoregressive fractionally integrated moving average model, Generalised autoregressive conditional heteroskedasticity model, Long memory process, Periodic autoregressive model, Volatility

JEL Classification: C22, C51, G10

Suggested Citation

Koopman, Siem Jan and Ooms, Marius and Carnero, M. Angeles, Periodic Seasonal REG-ARFIMA-GARCH Models for Daily Electricity Spot Prices. Journal of the American Statistical Association, Vol. 102, No. 477, pp. 16-27, March 2007, Available at SSRN: https://ssrn.com/abstract=999301

Siem Jan Koopman (Contact Author)

Vrije Universiteit Amsterdam - School of Business and Economics ( email )

De Boelelaan 1105
Amsterdam, 1081 HV
Netherlands
+31205986019 (Phone)

HOME PAGE: http://sjkoopman.net

Tinbergen Institute ( email )

Gustav Mahlerplein 117
1082 MS Amsterdam
Netherlands

HOME PAGE: http://personal.vu.nl/s.j.koopman

Aarhus University - CREATES ( email )

School of Economics and Management
Building 1322, Bartholins Alle 10
DK-8000 Aarhus C
Denmark

Marius Ooms

VU University Amsterdam - Department of Econometrics ( email )

De Boelelaan 1105
1081 HV Amsterdam
Netherlands
+31 20 4446023 (Phone)
+31 20 4446020 (Fax)

HOME PAGE: http://econometriclinks.com

M. Angeles Carnero

Universidad de Alicante - Department of Economic Analysis ( email )

03080 Alicante
Spain

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