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Forecasting electricity spot prices using linear univariate time series models
http://www.erasmusenergy.com/articles/5/1/Forecasting-electricity-spot-prices-using-linear-univariate-time-series-models/Page1.html
Jesus Crespo Cuaresma
I am a professor of economics at the Department of Economics of the University of Innsbruck. 
By Jesus Crespo Cuaresma
Published on 09/20/2007
 

Keywords: Electricity spot prices, ARMA models, Structural time series, Forecasting
Published in: -
Publication year: 2002
Co-Author 1: Jaroslava Hlouskova
Co-Author 2: Stephan Kossmeier
Co-Author 3: Michael Obersteiner

This paper studies the forecasting abilities of a battery of univariate models on hourly electricity spot prices, using data from the Leipzig Power Exchange. The speci cations studied include autoregressive models, autoregressive-moving average models and unobserved components models. The results show that speci cations where each hour of the day is modelled separately present uniformly better forecasting properties than speci cations for the whole time series, and that the inclusion of simple probabilistic processes for the arrival ofextreme price events can lead to improvements in the forecasting abilities of univariate models for electricity spot prices.


Forecasting electricity spot prices using linear univariate time series models

This paper studies the forecasting abilities of a battery of univariate models on hourly electricity spot prices, using data from the Leipzig Power Exchange. The speci cations studied include autoregressive models, autoregressive-moving average models and unobserved components models. The results show that speci cations where each hour of the day is modelled separately present uniformly better forecasting properties than speci cations for the whole time series, and that the inclusion of simple probabilistic processes for the arrival ofextreme price events can lead to improvements in the forecasting abilities of univariate models for electricity spot prices.