Quantile forecasting for credit risk management using possibly misspecified hidden Markov models
Abstract
Recent models for credit risk management make use of hidden Markov models (HMMs). HMMs are used to forecast quantiles of corporate default rates. Little research has been done on the quality of such forecasts if the underlying HMM is potentially misspecified. In this paper, we focus on misspecification in the dynamics and dimension of the HMM. We consider both discrete- and continuous-state HMMs. The differences are substantial. Underestimating the number of discrete states has an economically significant impact on forecast quality. Generally speaking, discrete models underestimate the high-quantile default rate forecasts. Continuous-state HMMs, however, vastly overestimate high quantiles if the true HMM has a discrete state space. In the reverse setting the biases are much smaller, though still substantial in economic terms. We illustrate the empirical differences using US default data. Copyright © 2008 John Wiley & Sons, Ltd.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.Bibliographic Info
Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.
Volume (Year): 27 (2008)
Issue (Month): 7 ()
Pages: 566-586
Contact details of provider:
Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966
Related research
Keywords:References
No references listed on IDEASYou 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 statisticsCorrections
When requesting a correction, please mention this item's handle: RePEc:jof:jforec:v:27:y:2008:i:7:p:566-586For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing) or (Christopher F. Baum).
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.