A Note on Diagnosing Multivariate Conditional Heteroscedasticity Models

In this paper we consider several tests for model misspecification after a multivariate conditional heteroscedasticity model has been fitted. We examine the performance of the recent test due to Ling and Li (J. Time Ser. Anal. 18 (1997), 447–64), the Box–Pierce test and the residual-based F test usi...

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Main Authors: TSE, Yiu Kuen, Tsui, Albert K.C.
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Language:English
Published: Institutional Knowledge at Singapore Management University 1999
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Online Access:https://ink.library.smu.edu.sg/soe_research/148
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spelling sg-smu-ink.soe_research-11472010-09-23T05:48:03Z A Note on Diagnosing Multivariate Conditional Heteroscedasticity Models TSE, Yiu Kuen Tsui, Albert K.C. In this paper we consider several tests for model misspecification after a multivariate conditional heteroscedasticity model has been fitted. We examine the performance of the recent test due to Ling and Li (J. Time Ser. Anal. 18 (1997), 447–64), the Box–Pierce test and the residual-based F test using Monte Carlo methods. We find that there are situations in which the Ling–Li test has very weak power. The residual-based diagnostics demonstrate significant under-rejection under the null. In contrast, the Box–Pierce test based on the cross-products of the standardized residuals often provides a useful diagnostic that has reliable empirical size as well as good power against the alternatives considered. 1999-01-01T08:00:00Z text https://ink.library.smu.edu.sg/soe_research/148 info:doi/10.1111/1467-9892.00166 Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Economics
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Economics
spellingShingle Economics
TSE, Yiu Kuen
Tsui, Albert K.C.
A Note on Diagnosing Multivariate Conditional Heteroscedasticity Models
description In this paper we consider several tests for model misspecification after a multivariate conditional heteroscedasticity model has been fitted. We examine the performance of the recent test due to Ling and Li (J. Time Ser. Anal. 18 (1997), 447–64), the Box–Pierce test and the residual-based F test using Monte Carlo methods. We find that there are situations in which the Ling–Li test has very weak power. The residual-based diagnostics demonstrate significant under-rejection under the null. In contrast, the Box–Pierce test based on the cross-products of the standardized residuals often provides a useful diagnostic that has reliable empirical size as well as good power against the alternatives considered.
format text
author TSE, Yiu Kuen
Tsui, Albert K.C.
author_facet TSE, Yiu Kuen
Tsui, Albert K.C.
author_sort TSE, Yiu Kuen
title A Note on Diagnosing Multivariate Conditional Heteroscedasticity Models
title_short A Note on Diagnosing Multivariate Conditional Heteroscedasticity Models
title_full A Note on Diagnosing Multivariate Conditional Heteroscedasticity Models
title_fullStr A Note on Diagnosing Multivariate Conditional Heteroscedasticity Models
title_full_unstemmed A Note on Diagnosing Multivariate Conditional Heteroscedasticity Models
title_sort note on diagnosing multivariate conditional heteroscedasticity models
publisher Institutional Knowledge at Singapore Management University
publishDate 1999
url https://ink.library.smu.edu.sg/soe_research/148
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