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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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 |
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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. |
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TSE, Yiu Kuen Tsui, Albert K.C. |
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TSE, Yiu Kuen Tsui, Albert K.C. |
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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 |
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A Note on Diagnosing Multivariate Conditional Heteroscedasticity Models |
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note on diagnosing multivariate conditional heteroscedasticity models |
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Institutional Knowledge at Singapore Management University |
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1999 |
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https://ink.library.smu.edu.sg/soe_research/148 |
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