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Don’t Fall from the Saddle: the Importance of Higher Moments of Credit Loss Distributions

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Author Info
J. ANNAERT ()
Crispiniano Garcia Joao Batista
J. LAMOOT
G. LANINE ()
Abstract

The original Panjer recursion of the CreditRisk+ model is said to be unstable and therefore to yield inaccurate results of the tail distribution of credit portfolios. A much-hailed solution for the flaws of the Panjer recursion is the saddlepoint approximation method. In this paper we show that the saddlepoint approximation is an accurate and robust tool only for relatively homogenous credit portfolios with low skewness and kurtosis of the loss distribution. However, often credit portfolios are heterogeneous with large skewness and kurtosis. We show that for such portfolios the commonly applied saddlepoint approximations (the Lugannani-Rice and the Barndorff-Nielsen formulas) are not reliable. Moreover, when applied to such credit portfolios, the Lugannani-Rice formula is fragile. We explain it by the dependence of the high-order standardized cumulants and the relative error on the saddlepoints. The more the cumulants and the relative error vary, the less accurate the saddlepoint approximation is. Hence, the saddlepoint approximation is not a universal substitute to the Panjer recursion algorithm.

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Paper provided by Ghent University, Faculty of Economics and Business Administration in its series Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium with number 06/367.

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Length: 34 pages
Date of creation: Feb 2006
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Handle: RePEc:rug:rugwps:06/367

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  1. Michael B. Gordy, 1998. "A comparative anatomy of credit risk models," Finance and Economics Discussion Series 1998-47, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
  2. Gordy, Michael B., 2002. "Saddlepoint approximation of CreditRisk+," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1335-1353, July. [Downloadable!] (restricted)
  3. Acerbi, Carlo & Tasche, Dirk, 2002. "On the coherence of expected shortfall," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1487-1503, July. [Downloadable!] (restricted)
  4. Matthew Pritsker, 1997. "Evaluating Value at Risk Methodologies: Accuracy versus Computational Time," Journal of Financial Services Research, Springer, vol. 12(2), pages 201-242, October. [Downloadable!] (restricted)
  5. Michael B. Gordy, 2002. "A risk-factor model foundation for ratings-based bank capital rules," Finance and Economics Discussion Series 2002-55, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
  6. Gordy, Michael B., 2000. "A comparative anatomy of credit risk models," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 119-149, January. [Downloadable!] (restricted)
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