Empirical likelihood for garch models

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Detail(s)

Original languageEnglish
Pages (from-to)403-428
Journal / PublicationEconometric Theory
Volume22
Issue number3
Publication statusPublished - Jun 2006
Externally publishedYes

Abstract

This paper develops an empirical likelihood approach for regular generalized autoregressive conditional heteroskedasticity (GARCH) models and GARCH models with unit roots. For regular GARCH models, it is shown that the log empirical likelihood ratio statistic asymptotically follows a χ 2 distribution. For GARCH models with unit roots, two versions of the empirical likelihood methods, the least squares score and the maximum likelihood score functions, are considered. For both cases, the limiting distributions of the log empirical likelihood ratio statistics are established. These two statistics can be used to test for unit roots under the GARCH framework. Finite-sample performances are assessed through simulations for GARCH models with unit roots. © 2006 Cambridge University Press.

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Citation Format(s)

Empirical likelihood for garch models. / Chan, Ngai Hang; Ling, Shiqing.
In: Econometric Theory, Vol. 22, No. 3, 06.2006, p. 403-428.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review