Estimating Conditional Probability Distributions of Recovery Rates: A Utility-Based Approach

RECOVERY RISK: THE NEXT CHALLENGE IN CREDIT RISK MANGEMENT, Edward Altman, Andrea Resti and Andrea Sironi, eds., Risk Books, 2005

19 Pages Posted: 11 Jan 2006

See all articles by Craig A. Friedman

Craig A. Friedman

State++

Sven Sandow

Standard & Poor's - Quantitative Analytics

Abstract

Credit portfolio risk depends strongly on the recovery risk of the debt instruments in the portfolio. In order to make precise statements about recovery risk, one must understand the probability distribution of recovery values for each debt instrument, given the instrument's characteristics and the economic environment. We emphasize that it is important to make use of known information; to do so, we model a conditional probability distribution. By conditioning on the characteristics of the debt instruments in a particular portfolio, we allow our recovery-risk model to reflect the intricacies and peculiarities of the particular portfolio under consideration; by conditioning on the economic environment, we incorporate the link between recoveries and economy-wide default levels and tie the credit portfolio risk to the particular economic environment in which the risk is to be assessed.

Suggested Citation

Friedman, Craig A. and Sandow, Sven, Estimating Conditional Probability Distributions of Recovery Rates: A Utility-Based Approach. RECOVERY RISK: THE NEXT CHALLENGE IN CREDIT RISK MANGEMENT, Edward Altman, Andrea Resti and Andrea Sironi, eds., Risk Books, 2005, Available at SSRN: https://ssrn.com/abstract=874754

Craig A. Friedman (Contact Author)

State++ ( email )

New York, NY
United States

Sven Sandow

Standard & Poor's - Quantitative Analytics ( email )

55 Water Street
New York, NY 10041
United States