Efficient estimation of a multivariate multiplicative volatility model

We propose a multivariate generalization of the multiplicative volatility model of Engle and Rangel (2008), which has a nonparametric long run component and a unit multivariate GARCH short run dynamic component. We suggest various kernel-based estimation procedures for the parametric and nonparametr...

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Bibliographic Details
Published in:Econometrics 2010-11, Vol.159 (1), p.55-73
Main Authors: Hafner, Christian M., Linton, Oliver
Format: Article
Language:English
Subjects:
Applications
Econometric models
Econometrics
Estimating techniques
Exact sciences and technology
GARCH
GARCH Kernel estimation Local stationarity Semiparametric
GARCH models
Indexes
Insurance, economics, finance
Kernel estimation
Local stationarity
Mathematics
Model testing
Multivariate analysis
Parametric inference
Probability and statistics
Quantitative Finance
Sciences and techniques of general use
Securities markets
Semiparametric
Statistical Finance
Statistics
Stochastic models
Studies
Time series
Vector-autoregressive models
Volatility
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Summary:We propose a multivariate generalization of the multiplicative volatility model of Engle and Rangel (2008), which has a nonparametric long run component and a unit multivariate GARCH short run dynamic component. We suggest various kernel-based estimation procedures for the parametric and nonparametric components, and derive the asymptotic properties thereof. For the parametric part of the model, we obtain the semiparametric efficiency bound. Our method is applied to a bivariate stock index series. We find that the univariate model of Engle and Rangel (2008) appears to be violated in the data whereas our multivariate model is more consistent with the data.
ISSN:0304-4076
2225-1146
1872-6895
DOI:10.1016/j.jeconom.2010.04.007