Estimation and Inference in ARCH Models in the Presence of Outliers
In this paper, we show the effects that outliers have on estimation and inference for autoregressive conditional heteroskedasticity (ARCH) models. We propose for a wide class of ARCH models commonly estimated, an empirically tractable solution to this problem by replacing outliers with their conditional expectations (optimal forecasts) in the likelihood function. This solution works well in both simulations and applications, as opposed to dummy variables which can lead to multimodality in the ARCH likelihood and invalid inference. We demonstrate the accuracy of our procedure for parameter estimation and forecasting. The empirical examples include U.S. interest rate, foreign exchange rate, and stock index data. In addition, we suggest a robust bootstrap test for outliers and evaluate this against the Andrews (2003) S test. Copyright The Author 2010. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: email@example.com, Oxford University Press.
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.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 8 (2010)
Issue (Month): 4 (Fall)
|Contact details of provider:|| Postal: |
Fax: 01865 267 985
Web page: http://jfec.oxfordjournals.org/Email:
More information through EDIRC
|Order Information:||Web: http://www.oup.co.uk/journals|
When requesting a correction, please mention this item's handle: RePEc:oup:jfinec:v:8:y:2010:i:4:p:547-549. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Oxford University Press)or (Christopher F. Baum)
If references are entirely missing, you can add them using this form.