Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/119424
Authors: 
Shen, Zhiwei
Ritter, Matthias
Year of Publication: 
2015
Series/Report no.: 
SFB 649 Discussion Paper 2015-026
Abstract: 
The increasing share of wind energy in the portfolio of energy sources highlights its uncertainties due to changing weather conditions. To account for the uncertainty in predicting wind power production, this article examines the volatility forecasting abilities of different GARCH-type models for wind power production. Moreover, due to characteristic features of the wind power process, such as heteroscedasticity and nonlinearity, we also investigate the use of a Markov regime-switching GARCH (MRS-GARCH) model on forecasting volatility of wind power. The realized volatility, which is derived from lower-scale data, serves as a benchmark for the latent volatility. We find that the MRS-GARCH model significantly outperforms traditional GARCH models in predicting the volatility of wind power, while the exponential GARCH model is superior among traditional GARCH models.
Subjects: 
wind energy
volatility forecasting
GARCH models
Markov regime-switching
realized volatility
JEL: 
C22
Q42
Q47
Document Type: 
Working Paper

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