Can Markov regime-switching models improve power-price forecasts? Evidence from German daily power prices

Non-linear autoregressive Markov regime-switching models are intuitive. Time-series approaches for the modelling of electricity spot prices are frequently proposed. In this paper, such models are compared with an ordinary linear autoregressive model with regard to their forecast performances. The st...

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Bibliographic Details
Published in:Applied energy 2006-09, Vol.83 (9), p.943-958
Main Authors: Kosater, Peter, Mosler, Karl
Format: Article
Language:English
Subjects:
Applied sciences
Devices using thermal energy
Electricity spot prices
Electricity spot prices Markov regime-switching Forecasting
Energy
Energy. Thermal use of fuels
Exact sciences and technology
Forecasting
Furnaces
Markov regime-switching
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Summary:Non-linear autoregressive Markov regime-switching models are intuitive. Time-series approaches for the modelling of electricity spot prices are frequently proposed. In this paper, such models are compared with an ordinary linear autoregressive model with regard to their forecast performances. The study is carried out using German daily spot-prices from the European Energy Exchange in Leipzig. Four non-linear models are used for the forecast study. The results of the study suggest that Markov regime-switching models provide better forecasts than linear models.
ISSN:0306-2619
1872-9118
DOI:10.1016/j.apenergy.2005.10.007