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Evaluating GARCH models

delete2002-10-01
delete91
PRE
AI
S
Stefan Lundbergh
T
Timo Teräsvirta *
DOI：10.1016/S0304-4076(02)00096-9delete
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Abstract

Abstract

En 中文
In this paper, a unified framework for testing the adequacy of an estimated GARCH model is presented. Parametric Lagrange multiplier (LM) or LM type tests of no ARCH in standardized errors, linearity, and parameter constancy are proposed. The asymptotic null distributions of the tests are standard, which makes application easy. Versions of the tests that are robust against normormal errors are provided. The finite sample properties of the test statistics are investigated by simulation. The robust tests prove superior to the nonrobust ones when the errors are nonnormal. They also compare favourably in terms of power with misspecification tests previously proposed in the literature. (C) 2002 Elsevier Science B.V. All rights reserved.
Keywords:
conditional heteroskedasticity
model misspecification test
nonlinear time series
parameter constancy
smooth transition GARCH
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Journal

Journal of Econometrics cover
Journal of Econometrics
IF:
4
Papers:
5.2K
Citations:
3.0W

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