Document Search
Add To My Bookshelf Sign in or Register Save And Annotate
Keywords:

credit sign in to follow this
default sign in to follow this
multivariate sign in to follow this
importance sign in to follow this
sampling sign in to follow this
Categories:

VaR Uses sign in to follow this
--Credit Risk sign in to follow this
Half-Life:
Impact:
Discuss This Paper
Sign in to follow this page
Recent Comments
  more
A Non-Gaussian Panel Time Series Model for Estimating and Decomposing Default Risk
Year Of Publication: 2005
Month Of Publication: May
Pages: 30
Download Count: 496
View Count:
Comment Num: 0
Language: EN
Source:
Who Can Read: Free
Date: 5-25-2006
Publisher: Administrator
Summary
We model 1981–2002 annual default frequencies for a panel of US firms in different ratingand age classes from the Standard and Poor’s database. The data is decomposedinto a systematic and firm-specific risk component, where the systematic component reflectsthe general economic conditions and default climate. We have to cope with (i) theshared exposure of each age cohort and rating class to the same systematic risk factor;(ii) strongly non-Gaussian features of the individual time series; (iii) possible dynamics ofan unobserved common risk factor; (iv) changing default probabilities over the age of therating, and (v) missing observations. We propose a non-Gaussian multivariate state spacemodel that deals with all of these issues simultaneously. The model is estimated usingimportance sampling techniques that have been modified to a multivariate setting. Weshow in a simulation study that such a multivariate approach improves the performanceof the importance sample
Author(s)
Koopman, Siem Jan Sign in to follow this author
Lucas, Andre Sign in to follow this author
Daniels, Robert J. Sign in to follow this author
This document's citation network:
Similar Documents:
Close window
Sign up in one step, no personal information required. Already a Member?



Email:
Repeat Email:
User Name:
Password:
Confirm Password:

Sign Up


Welcome to GloriaMundi!
Thanks for singning up



continue or edit your profile