Analysis of French electric market using heteroscedastic models of time series

Author

López, Damián ; Juan, Jesus

Author_Institution

Escuela Tec. Super. de Ing. Ind., Univ. Politec. de Madrid, Madrid

fYear

2008

fDate

28-30 May 2008

Firstpage

1

Lastpage

6

Abstract

A dynamic long memory regression model with autoregressive errors is considered for the analysis of hourly electricity spot prices. The method provides reliable and accurate forecasts of hourly prices in the electricity market of France, Powernext day-ahead. The presence of significant autocorrelation in squared residual recommends to fit a conditional heteroscedastic time series model. These models together have appealing economic and statistical implications.

Keywords

autoregressive processes; power markets; regression analysis; Powernext Day-Ahead; autoregressive errors; dynamic long memory regression model; economic implications; electricity spot prices; french electric market; heteroscedastic models; statistical implications; time series; Autocorrelation; Economic forecasting; Electricity supply industry; Energy management; Forward contracts; Power generation economics; Production; Risk management; Supply and demand; Time series analysis; ARCH; ARIMA; Electricity prices; GARCH; market modelling;

fLanguage

English

Publisher

ieee

Conference_Titel

Electricity Market, 2008. EEM 2008. 5th International Conference on European

Conference_Location

Lisboa

Print_ISBN

978-1-4244-1743-8

Electronic_ISBN

978-1-4244-1744-5

Type

conf

DOI

10.1109/EEM.2008.4579014

Filename

4579014