Advanced Search
MyIDEAS: Login

Asymptotic Distribution-Free Diagnostic Tests For Heteroskedastic Time Series Models

Contents:

Author Info

  • J. Carlos Escanciano

    (Indiana University)

Abstract

This article investigates model checks for a class of possibly nonlinear heteroskedastic time series models, including but not restricted to ARMA-GARCH models. We propose omnibus tests based on functionals of certain weighted standardized residual empirical processes. The new tests are asymptotically distribution-free, suitable when the conditioning set is in?nite- dimensional, and consistent against a class of Pitman?s local alternatives converging at the parametric rate n??1=2; with n the sample size. A Monte Carlo study shows that the simulated level of the proposed tests is close to the asymptotic level already for moderate sample sizes and that tests have a satisfactory power performance. Finally, we illustrate our methodology with an application to the well-known S&P 500 daily stock index. The paper also contains an asymptotic uniform expansion for weighted residual empirical processes when initial conditions are considered, a result of independent interest.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://www.iub.edu/~caepr/RePEc/PDF/2009/CAEPR2009-019.pdf
Download Restriction: no

Bibliographic Info

Paper provided by Center for Applied Economics and Policy Research, Economics Department, Indiana University Bloomington in its series Caepr Working Papers with number 2009-019.

as in new window
Length: 33 pages
Date of creation: Sep 2009
Date of revision:
Handle: RePEc:inu:caeprp:2009-019

Contact details of provider:
Postal: Wylie Hall Room 105, Bloomington, IN 47405-6620
Phone: 812-855-1021
Fax: 812-855-3736
Email:
Web page: http://www.iub.edu/~caepr
More information through EDIRC

Related research

Keywords:

Other versions of this item:

This paper has been announced in the following NEP Reports:

References

No references listed on IDEAS
You can help add them by filling out this form.

Citations

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:inu:caeprp:2009-019

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Heather Steele).

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.