Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/162956 
Year of Publication: 
2016
Series/Report no.: 
Discussion Paper Series No. 613
Publisher: 
University of Heidelberg, Department of Economics, Heidelberg
Abstract: 
We examine the statistical properties of multiplicative GARCH models. First, we show that in multiplicative models, returns have higher kurtosis and squared returns have a more persistent autocorrelation function than in the nested GARCH model. Second, we extend the results of Andersen and Bollerslev (1998) on the upper bound of the R2 in a Mincer-Zarnowitz regression to the case of a multiplicative GARCH model, using squared returns as a proxy for the true but unobservable conditional variance. Our theoretical results imply that multiplicative GARCH models provide an explanation for stylized facts that cannot be captured by classical GARCH modeling.
Subjects: 
Forecast evaluation
GARCH-MIDAS
Mincer-Zarnowitz regression
volatility persistence
volatility component model
long-term volatility
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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