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Modelling and calibration errors in measures of portfolio credit risk

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  • Nikola A. Tarashev
  • Haibin Zhu
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    Abstract

    This paper develops an empirical procedure for analyzing the impact of model misspecification and calibration errors on measures of portfolio credit risk. When applied to large simulated portfolios with realistic characteristics, this procedure reveals that violations of key assumptions of the well-known Asymptotic Single-Risk Factor (ASRF) model are virtually inconsequential. By contrast, flaws in the calibrated interdependence of credit risk across exposures, which are driven by plausible small-sample estimation errors or popular rule-of-thumb values of asset return correlations, can lead to significant inaccuracies in measures of portfolio credit risk. Similar inaccuracies arise under erroneous, albeit standard, assumptions regarding the tails of the distribution of asset returns.

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    Bibliographic Info

    Paper provided by Bank for International Settlements in its series BIS Working Papers with number 230.

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    Length: 42 pages
    Date of creation: Jun 2007
    Date of revision:
    Handle: RePEc:bis:biswps:230

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    Related research

    Keywords: Correlated defaults; value at risk; multiple common factors; granularity; estimation error; tail dependence; bank capital;

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    1. Lütkebohmert, Eva & Gordy, Michael B., 2007. "Granularity adjustment for Basel II," Discussion Paper Series 2: Banking and Financial Studies 2007,01, Deutsche Bundesbank, Research Centre.
    2. Düllmann, Klaus & Scheicher, Martin & Schmieder, Christian, 2007. "Asset correlations and credit portfolio risk: an empirical analysis," Discussion Paper Series 2: Banking and Financial Studies 2007,13, Deutsche Bundesbank, Research Centre.
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    Cited by:
    1. Antão, Paula & Lacerda, Ana, 2011. "Capital requirements under the credit risk-based framework," Journal of Banking & Finance, Elsevier, vol. 35(6), pages 1380-1390, June.

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