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Analytical Framework for Credit Portfolios. Part I: Systematic Risk

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  • Mikhail Voropaev

Abstract

Analytical, free of time consuming Monte Carlo simulations, framework for credit portfolio systematic risk metrics calculations is presented. Techniques are described that allow calculation of portfolio-level systematic risk measures (standard deviation, VaR and Expected Shortfall) as well as allocation of risk down to individual transactions. The underlying model is the industry standard multi-factor Merton-type model with arbitrary valuation function at horizon (in contrast to the simplistic default-only case). High accuracy of the proposed analytical technique is demonstrated by benchmarking against Monte Carlo simulations.

Suggested Citation

  • Mikhail Voropaev, 2009. "Analytical Framework for Credit Portfolios. Part I: Systematic Risk," Papers 0911.0223, arXiv.org, revised Jul 2011.
  • Handle: RePEc:arx:papers:0911.0223
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    File URL: http://arxiv.org/pdf/0911.0223
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    Cited by:

    1. repec:eee:jbfina:v:81:y:2017:i:c:p:105-113 is not listed on IDEAS
    2. García-Céspedes, Rubén & Moreno, Manuel, 2014. "Estimating the distribution of total default losses on the Spanish financial system," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 242-261.
    3. Fermanian, Jean-David, 2014. "The limits of granularity adjustments," Journal of Banking & Finance, Elsevier, vol. 45(C), pages 9-25.
    4. M. B. Gordy & E. Lutkebohmert, 2013. "Granularity Adjustment for Regulatory Capital Assessment," International Journal of Central Banking, International Journal of Central Banking, vol. 9(3), pages 38-77, September.

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