Publication Type
Journal Article
Version
publishedVersion
Publication Date
12-2002
Abstract
We examine the residual–based diagnostics for univariate and multivariate conditional heteroscedasticity models. The tests are based on the parameter estimates of an autoregression with the squared standardized residuals or the cross products of the standardized residuals as dependent variables. As the regression involves estimated regressors the standard distribution theories of the ordinary least squares estimates do not apply. We provide the asymptotic variance of the regression estimates. Diagnostic statistics, which are asymptotically distributed as ?[sup 2], are constructed. A Monte Carlo experiment is conducted to investigate the finite–sample properties of the residual–based tests for both univariate and multivariate models. The results show that the residual–based diagnostics provide useful checks for model adequacy in both univariate and multivariate cases.
Keywords
Conditional heteroscedasticity, Lagrange multiplier test, Monte Carlo experiment, Portmanteau statistic, Residual-based diagnostic
Discipline
Econometrics
Research Areas
Econometrics
Publication
Econometrics Journal
Volume
5
Issue
2
First Page
358
Last Page
373
ISSN
1368-4221
Identifier
10.1111/1368-423X.t01-1-00088
Publisher
Oxford University Press
Citation
TSE, Yiu Kuen.
Residual-Based Diagnostics for Conditional Heteroscedasticity Models. (2002). Econometrics Journal. 5, (2), 358-373.
Available at: https://ink.library.smu.edu.sg/soe_research/498
Copyright Owner and License
Publisher
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1111/1368-423X.t01-1-00088