Residual-Based Diagnostics for Conditional Heteroscedasticity Models
Publication Type
Journal Article
Publication Date
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.
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
Wiley
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
Additional URL
https://doi.org/10.1111/1368-423X.t01-1-00088