Measuring portfolio credit risk correctly: why parameter uncertainty matters

Nikola Tarashev ()

No 280, BIS Working Papers from Bank for International Settlements

Abstract: Why should risk management systems account for parameter uncertainty? In order to answer this question, this paper lets an investor in a credit portfolio face non-diversifiable estimation-driven uncertainty about two parameters: probability of default and asset-return correlation. Bayesian inference reveals that - for realistic assumptions about the portfolio's credit quality and the data underlying parameter estimates - this uncertainty substantially increases the tail risk perceived by the investor. Since incorporating parameter uncertainty in a measure of tail risk is computationally demanding, the paper also derives and analyzes a closed-form approximation to such a measure.

Keywords: correlated defaults; estimation error; risk management (search for similar items in EconPapers)
Pages: 43 pages
Date: 2009-04
New Economics Papers: this item is included in nep-ban and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Related works:
Journal Article: Measuring portfolio credit risk correctly: Why parameter uncertainty matters (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:bis:biswps:280

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