Evaluating GARCH models
AbstractIn this paper a unified framework for testing the adequacy of an estimated GARCH model is presented. Parametric 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 nonnormal 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.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Econometrics.
Volume (Year): 110 (2002)
Issue (Month): 2 (October)
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Web page: http://www.elsevier.com/locate/jeconom
Other versions of this item:
- Stefan Lundbergh & Timo Teräsvirta, 1999. "Evaluating GARCH Models," Tinbergen Institute Discussion Papers 99-008/4, Tinbergen Institute.
- Lundbergh, Stefan & Teräsvirta, Timo, 1998. "Evaluating GARCH models," Working Paper Series in Economics and Finance 292, Stockholm School of Economics, revised 03 May 1999.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
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