Sample and Implied Volatility in GARCH Models
AbstractThe unconditional variance of various GARCH-type models is a function h(theta) of the parameter vector theta which is estimated by theta. For most models used in practice, closed-form expressions of h(.) have been found. On the contrary, the unconditional variance can be estimated by the sample variance sigma^2. This article establishes the asymptotic distributions of the differences sigma^2 - h(theta) and &sigma^2 - h(theta) for broad classes of GARCH-type models. Even though both limit distributions are normal, the asymptotic variances are not equal. Potential practical consequences of these results are discussed. Copyright 2006, Oxford University Press.
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Bibliographic InfoArticle provided by Society for Financial Econometrics in its journal Journal of Financial Econometrics.
Volume (Year): 4 (2006)
Issue (Month): 4 ()
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- Christian FRANCQ & Lajos HORVATH & Jean-Michel ZAKOIAN, 2009.
"Merits and Drawbacks of Variance Targeting in GARCH Models,"
Working Papers, Centre de Recherche en Economie et Statistique
2009-17, Centre de Recherche en Economie et Statistique.
- Christian Francq & Lajos Horváth, 2011. "Merits and Drawbacks of Variance Targeting in GARCH Models," Journal of Financial Econometrics, Society for 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.
- Stanislav Khrapov, 2011. "Pricing Central Tendency in Volatility," Working Papers, Center for Economic and Financial Research (CEFIR) w0168, Center for Economic and Financial Research (CEFIR).
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