Bayesian Synthesis of Portfolio Credit Risk with Missing Ratings

26 Pages Posted: 25 Jun 2016

See all articles by Dror Parnes

Dror Parnes

University of South Florida

Date Written: October 21, 2015

Abstract

In this study we develop a universal Bayesian model that accounts for the time frames until future credit rating downgrades, the time lengths of no credit coverage, and the time intervals until default of individual debt issuances. We then use a maximum likelihood estimation to assess the projected average default rates (over diverse horizons) of debt portfolios that exhibit similar credit characteristics. We demonstrate the scheme over multiple large homogeneous portfolios and further authenticate the validity of the derived credit profiles by appointing to each uniform portfolio a descriptive credit grade. These combined credit ratings tend to be higher than their respective individual bonds. This reconfirms the universal advantage of portfolio diversification.

Keywords: Bayesian analysis, portfolio credit risk, maximum likelihood estimation, debt issuances, missing credit ratings

Suggested Citation

Parnes, Dror, Bayesian Synthesis of Portfolio Credit Risk with Missing Ratings (October 21, 2015). Journal of Risk, Vol. 18, No. 1, 2015, Available at SSRN: https://ssrn.com/abstract=2799709

Dror Parnes (Contact Author)

University of South Florida ( email )

Tampa, FL 33620
United States

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