Measuring portfolio credit risk correctly: Why parameter uncertainty matters

Nikola Tarashev ()

Journal of Banking & Finance, 2010, vol. 34, issue 9, 2065-2076

Abstract: Why should risk management systems account for parameter uncertainty? In addressing this question, the paper lets an investor in a credit portfolio face non-diversifiable uncertainty about two risk parameters - probability of default and asset-return correlation - and calibrates this uncertainty to a lower bound on estimation noise. In this context, a Bayesian inference procedure is essential for deriving and analyzing the main result, i.e. that parameter uncertainty raises substantially the tail risk perceived by the investor. Since a measure of tail risk that incorporates parameter uncertainty is computationally demanding, the paper also derives a closed-form approximation to such a measure.

Keywords: Correlated; defaults; Estimation; error; Risk; management (search for similar items in EconPapers)
Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (15)

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Working Paper: Measuring portfolio credit risk correctly: why parameter uncertainty matters (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbfina:v:34:y:2010:i:9:p:2065-2076

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