FIRST-ORDER ASYMPTOTIC THEORY FOR PARAMETRIC MISSPECIFICATION TESTS OF GARCH MODELS

Andreea G. Halunga and Chris Orme ()

Econometric Theory, 2009, vol. 25, issue 02, pages 364-410

Abstract: This paper develops a framework for the construction and analysis of parametric misspecification tests for generalized autoregressive conditional heteroskedastic (GARCH) models, based on first-order asymptotic theory. The principal finding is that estimation effects from the correct specification of the conditional mean (regression) function can be asymptotically nonnegligible. This implies that certain procedures, such as the asymmetry tests of Engle and Ng (1993, Journal of Finance 48, 1749 svirta (2002, Journal of Econometrics 110, 417 svirta (2002) procedures.

Date: 2009

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Related works:
Working Paper: First order asymptotic theory for parametric misspecification tests of GARCH models (2007)
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Persistent link: http://EconPapers.repec.org/RePEc:cup:etheor:v:25:y:2009:i:02:p:364-410_09

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