In this paper, we extend the debate concerning Credit Default Swap valuation to include time varying correlation and co-variances. Traditional multi-variate techniques treat the correlations between covariates as constant over time; however, this view is not supported by the data. Secondly, since financial data does not follow a normal distribution because of its heavy tails, modeling the data using a Generalized Linear model (GLM) incorporating copulas emerge as a more robust technique over traditional approaches. This paper also includes an empirical analysis of the regime switching dynamics of credit risk in the presence of liquidity by following the general practice of assuming that credit and market risk follow a Markov process. The study was based on Credit Default Swap data obtained from Bloomberg that spanned the period January 1st 2004 to August 08th 2006. The empirical examination of the regime switching tendencies provided quantitative support to the anecdotal view that liquidity decreases as credit quality deteriorates. The analysis also examined the joint probability distribution of the credit risk determinants across credit quality through the use of a copula function which disaggregates the behavior embedded in the marginal gamma distributions, so as to isolate the level of dependence which is captured in the copula function. The results suggest that the time varying joint correlation matrix performed far superior as compared to the constant correlation matrix; the centerpiece of linear regression models.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. 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.
Publisher Info
Paper provided by University of Connecticut, Department of Economics in its series Working papers with number
2007-10.
Length: 37 pages Date of creation: Apr 2007 Date of revision: Handle: RePEc:uct:uconnp:2007-10
Note: We are extremely grateful to Ben Fine, Department of Mathematics, Fairfield University, for his many insightful suggestions and guidance which helped to improve the final manuscript. This is a preprint of an article submitted for consideration in the Journal of Empirical Finance. Contact details of provider: Postal: University of Connecticut 341 Mansfield Road, Unit 1063 Storrs, CT 06269-1063 Phone: (860) 486-4889 Fax: (860) 486-4463 Web page: http://www.econ.uconn.edu/ More information through EDIRC
For technical questions regarding this item, or to correct its listing, contact: (Christian Zimmermann).
References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
Andrew J. Patton, 2006.
"Modelling Asymmetric Exchange Rate Dependence,"
International Economic Review,
Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(2), pages 527-556, 05.
[Downloadable!] (restricted)
Other versions: