Francq, Christian and Horvath, Lajos and Zakoian, JeanMichel (2009): Merits and drawbacks of variance targeting in GARCH models.

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Abstract
Variance targeting estimation is a technique used to alleviate the numerical difficulties encountered in the quasimaximum likelihood (QML) estimation of GARCH models. It relies on a reparameterization of the model and a firststep estimation of the unconditional variance. The remaining parameters are estimated by QML in a second step. This paper establishes the asymptotic distribution of the estimators obtained by this method in univariate GARCH models. Comparisons with the standard QML are provided and the merits of the variance targeting method are discussed. In particular, it is shown that when the model is misspecified, the VTE can be superior to the QMLE for longterm prediction or ValueatRisk calculation. An empirical application based on stock market indices is proposed.
Item Type:  MPRA Paper 

Original Title:  Merits and drawbacks of variance targeting in GARCH models 
Language:  English 
Keywords:  Consistency and Asymptotic Normality; GARCH; Heteroskedastic Time Series; Quasi Maximum Likelihood Estimation; ValueatRisk; Variance Targeting Estimator. 
Subjects:  C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C13  Estimation: General C  Mathematical and Quantitative Methods > C2  Single Equation Models; Single Variables > C22  TimeSeries Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models 
Item ID:  15143 
Depositing User:  Christian Francq 
Date Deposited:  09. May 2009 17:36 
Last Modified:  16. Feb 2013 00:47 
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URI:  http://mpra.ub.unimuenchen.de/id/eprint/15143 