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Merits and Drawbacks of Variance Targeting in GARCH Models

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  • Christian FRANCQ

    (Crest)

  • Lajos HORVATH

    (Crest)

  • Jean-Michel ZAKOIAN

    (Crest)

Abstract

Variance 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.

Suggested Citation

  • Christian FRANCQ & Lajos HORVATH & Jean-Michel ZAKOIAN, 2009. "Merits and Drawbacks of Variance Targeting in GARCH Models," Working Papers 2009-17, Center for Research in Economics and Statistics.
    • Handle: RePEc:crs:wpaper:2009-17
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    References listed on IDEAS

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    1. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(1), pages 122-150, February.
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    JEL classification:

    • 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; Diffusion Processes

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