Merits and Drawbacks of Variance Targeting in GARCH Models
AbstractVariance targeting estimation (VTE) is a technique used to alleviate the numerical difficultiesencountered in the quasi-maximum likelihood (QML) estimation of GARCH models. It relieson a reparameterization of the model and a first-step estimation of the unconditional variance.The remaining parameters are estimated by QML in a second step. This paper establishesthe asymptotic distribution of the estimators obtained by this method. Comparisons with thestandard QML are provided. In particular, when the model is misspecified the VTE can besuperior to the QMLE for long-term prediction or Value-at-Risk calculation. An empiricalapplication based on stock market indices is proposed.
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Bibliographic InfoPaper provided by Centre de Recherche en Economie et Statistique in its series Working Papers with number 2009-17.
Date of creation: 2009
Date of revision:
Other versions of this item:
- Christian Francq & Lajos Horváth, 2011. "Merits and Drawbacks of Variance Targeting in GARCH Models," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 9(4), pages 619-656.
- Francq, Christian & Horvath, Lajos & Zakoian, Jean-Michel, 2009. "Merits and drawbacks of variance targeting in GARCH models," MPRA Paper 15143, University Library of Munich, Germany.
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
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