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Consistent Information Multivariate Density Optimizing Methodology

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  • Miguel Segoviano

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    Abstract

    The estimation of the profit and loss distribution of a loan portfolio requires the modelling of the portfolio's multivariate distribution. This describes the joint likelihood of changes in the credit-risk quality of the loans that make-up the portfolio. A significant problem for portfolio credit risk measurement is the greatly restricted data that are available for its modelling. Under these circumstances, convenient parametric assumptions, however, usually do not appropiately describe the behaviour of the assets that are the subject of our interest, loans granted to small and medium enterprises (SMEs), unlisted and arm's length firms. This paper proposes the Consistent Information Multivariate Density Optimizing Methodology (CIMDO), based on the cross-entropy approach, as an alternative to generate probabilty multivariate densities from partial information and without making parametric assumptions. Using the probabilty integral transformation criterion, we show that the distributions recovered by CIMDO outperform distributions that are used for the measurement of portfolio credit risk of loans granted to SMEs, unlisted and arm's length firms.

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    File URL: http://www.lse.ac.uk/fmg/workingPapers/discussionPapers/fmgdps/dp557.pdf
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    Bibliographic Info

    Paper provided by Financial Markets Group in its series FMG Discussion Papers with number dp557.

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    Date of creation: Mar 2006
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    Handle: RePEc:fmg:fmgdps:dp557

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    Web page: http://www.lse.ac.uk/fmg/

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    Cited by:
    1. Miguel A. Segoviano & Charles Goodhart, 2010. "Distress Dependence and Financial Stability," Working Papers Central Bank of Chile 569, Central Bank of Chile.
    2. Mark Swinburne & Stéphanie Marie Stolz & Marina Moretti, 2008. "Stress Testing at the IMF," IMF Working Papers 08/206, International Monetary Fund.
    3. Carlos Caceres & D. Filiz Unsal, 2013. "Sovereign Spreads and Contagion Risks in Asia," Asian Economic Journal, East Asian Economic Association, vol. 27(3), pages 219-243, 09.
    4. Rodríguez-Moreno, María & Peña, Juan Ignacio, 2013. "Systemic risk measures: The simpler the better?," Journal of Banking & Finance, Elsevier, vol. 37(6), pages 1817-1831.
    5. Gorea, Denis & Radev, Deyan, 2014. "The euro area sovereign debt crisis: Can contagion spread from the periphery to the core?," International Review of Economics & Finance, Elsevier, vol. 30(C), pages 78-100.
    6. Radev, Deyan, 2013. "Systemic risk and sovereign debt in the Euro area," SAFE Working Paper Series 37, Center of Excellence SAFE - Sustainable Architecture for Finance in Europe, Goethe University Frankfurt.
    7. Miguel A. Segoviano Basurto & Carlos Caceres & Vincenzo Guzzo, 2010. "Sovereign Spreads: Global Risk Aversion, Contagion or Fundamentals?," IMF Working Papers 10/120, International Monetary Fund.
    8. Ola Melander & Malika Pant & Miguel Segoviano & Athanasios Vamvakidis, 2011. "Dancing Spreads: Market Assessment of Contagion from the Crisis in the Euro Periphery based on Distress Dependence Analysis," International Advances in Economic Research, Springer, vol. 17(3), pages 347-363, August.
    9. Miguel A. Segoviano Basurto, 2006. "Portfolio Credit Risk and Macroeconomic Shocks: Applications to Stress Testing Under Data-Restricted Environments," IMF Working Papers 06/283, International Monetary Fund.
    10. Charles Goodhart, 2010. "¿Cómo deberíamos regular el capital bancario y los productos financieros? ¿Cuál es el papel de los “testamentos en vida”?," Revista de Economía Institucional, Universidad Externado de Colombia - Facultad de Economía, vol. 12(23), pages 85-109, July-Dece.

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