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

Arbeitspapier

Nonlinear autoregressive Markov regime-switching models are intuitive and frequently proposed time series approaches for the modelling of electricity spot prices. In this paper such models are compared to an ordinary linear autoregressive model with regard to their forecast performance. The study is carried out using German daily spot prices from the European Energy Exchange in Leipzig. Four nonlinear models are used for the forecast study. The resultsof the study suggest that Markov regime-switching models provide better forecasts than linear models.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Discussion Papers in Statistics and Econometrics ; No. 1/05

Classification and Topics

• Classification: Wirtschaft ; Energy: General ; Electric Utilities ; Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
• Subject: Electricity spot prices ; Markov regime-switching ; forecasting

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Kosater, Peter ; Mosler, Karl
• Event: Veröffentlichung
• (who): University of Cologne, Seminar of Economic and Social Statistics
• (where): Cologne
• (when): 2005

Further information

• Handle: http://hdl.handle.net/10419/26736
• Last update: 10.03.2025, 11:41 AM CET