Can Markov-regime switching models improve power price forecasts? Evidence for German daily power prices
AbstractNonlinear 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. --
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Bibliographic InfoPaper provided by University of Cologne, Department for Economic and Social Statistics in its series Discussion Papers in Statistics and Econometrics with number 1/05.
Date of creation: 2005
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Electricity spot prices; Markov regime-switching; forecasting;
Other versions of this item:
- Kosater, Peter & Mosler, Karl, 2006. "Can Markov regime-switching models improve power-price forecasts? Evidence from German daily power prices," Applied Energy, Elsevier, vol. 83(9), pages 943-958, September.
- Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
- L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
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