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Measuring Portfolio Credit Risk Correctly: Why parameter uncertainty matters

by Nikola A Tarashev of the Bank for International Settlements

April 3, 2009

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.

JEL Classification: G20, G32, C11.

Keywords: Correlated defaults; Estimation error; Risk management.

Published in: Journal of Banking & Finance, Vol. 34, No. 9, (September 2010), pp. 2065-2076.

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