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Conceptual and Statistical Issues Regarding the Probability of Default and Modeling Default Risk

Author

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  • Emilia ?I?AN

    (Academy of Economic Studies, Bucharest)

  • Adela Ioana TUDOR

    (Academy of Economic Studies, Bucharest)

Abstract

In today’s rapidly evolving financial markets, risk management offers different techniques in order to implement an efficient system against market risk. Probability of default (PD) is an essential part of business intelligence and customer relation management systems in the financial institutions. Recent studies indicates that underestimating this important component, and also the loss given default (LGD), might threaten the stability and smooth running of the financial markets. From the perspective of risk management, the result of predictive accuracy of the estimated probability of default is more valuable than the standard binary classification: credible or non credible clients. The Basle II Accord recognizes the methods of reducing credit risk and also PD and LGD as important components of advanced Internal Rating Based (IRB) approach.

Suggested Citation

  • Emilia ?I?AN & Adela Ioana TUDOR, 2011. "Conceptual and Statistical Issues Regarding the Probability of Default and Modeling Default Risk," Database Systems Journal, Academy of Economic Studies - Bucharest, Romania, vol. 2(1), pages 13-22, March.
    • Handle: RePEc:aes:dbjour:v:2:y:2011:i:1:p:13-22
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    File URL: http://dbjournal.ro/archive/3/2_Titan_Tudor.pdf
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    References listed on IDEAS

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    1. Dirk Tasche, 2003. "A traffic lights approach to PD validation," Papers cond-mat/0305038, arXiv.org.
    2. Edward I. Altman & Brooks Brady & Andrea Resti & Andrea Sironi, 2005. "The Link between Default and Recovery Rates: Theory, Empirical Evidence, and Implications," The Journal of Business, University of Chicago Press, vol. 78(6), pages 2203-2228, November.
    3. Krink, Thiemo & Paterlini, Sandra & Resti, Andrea, 2008. "The optimal structure of PD buckets," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2275-2286, October.
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    Cited by:

    1. Adela Ioana TUDOR & Adela BÂRA & Elena ANDREI (DRAGOMIR, 2012. "Clustering Analysis for Credit Default Probabilities in a Retail Bank Portfolio," Database Systems Journal, Academy of Economic Studies - Bucharest, Romania, vol. 3(2), pages 23-30, August.

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