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 InfoPaper provided by Stockholm School of Economics in its series Working Paper Series in Economics and Finance with number 292.
Length: 26 pages
Date of creation: 18 Dec 1998
Date of revision: 03 May 1999
Publication status: Published in Journal of Econometrics, 2002, pages 417-435.
Note: This is the final revised version (October 2001) of the original (December 1998) paper.
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More information through EDIRC
Conditional heteroskedasticity; model misspecification test; nonlinear time series; parameter constancy; smooth transition GARCH.;
Other versions of this item:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
This paper has been announced in the following NEP Reports:
- NEP-ALL-1999-01-18 (All new papers)
- NEP-ECM-1999-01-18 (Econometrics)
- NEP-ETS-1999-01-18 (Econometric Time Series)
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