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Conrad, Christian
Kleen, Onno
Year of Publication: 
Series/Report no.: 
Discussion Paper Series 613
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.
Forecast evaluation
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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