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Survival Analysis in LGD Modeling

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Abstract
The paper proposes an application of the survival time analysis methodology to estimations of the Loss Given Default (LGD) parameter. The main advantage of the survival analysis approach compared to classical regression methods is that it allows exploiting partial recovery data. The model is also modified in order to improve performance of the appropriate goodness of fit measures. The empirical testing shows that the Cox proportional model applied to LGD modeling performs better than the linear and logistic regressions. In addition a significant improvement is achieved with the modified “pseudo” Cox LGD model.

Suggested Citation

  • Jiří Witzany & Michal Rychnovský & Pavel Charamza, 2010. "Survival Analysis in LGD Modeling," Working Papers IES 2010/02, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Feb 2010.
    • Handle: RePEc:fau:wpaper:wp2010_02
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    File URL: http://ies.fsv.cuni.cz/default/file/download/id/12703
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    References listed on IDEAS

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    1. repec:bla:ecnote:v:33:y:2004:i:2:p:183-208 is not listed on IDEAS
    2. G Andreeva, 2006. "European generic scoring models using survival analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(10), pages 1180-1187, October.
    3. Sudheer Chava & Catalina Stefanescu & Stuart Turnbull, 2011. "Modeling the Loss Distribution," Management Science, INFORMS, vol. 57(7), pages 1267-1287, July.
    4. Jiří Witzany, 2009. "Unexpected Recovery Risk and LGD Discount Rate Determination," European Financial and Accounting Journal, Prague University of Economics and Business, vol. 2009(1), pages 61-84.
    5. Greg M. Gupton, 2005. "Advancing Loss Given Default Prediction Models: How the Quiet Have Quickened," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 34(2), pages 185-230, July.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Matuszyk, Anna & So, Mee Chi & Mues, Christophe & Moore, Angela, 2016. "Modelling repayment patterns in the collections process for unsecured consumer debt: A case studyAuthor-Name: Thomas, Lyn C," European Journal of Operational Research, Elsevier, vol. 249(2), pages 476-486.
    2. Cheng, Dan & Cirillo, Pasquale, 2018. "A reinforced urn process modeling of recovery rates and recovery times," Journal of Banking & Finance, Elsevier, vol. 96(C), pages 1-17.
    3. Jiří Witzany & Anastasiia Kozina, 2022. "Recovery process optimization using survival regression," Operational Research, Springer, vol. 22(5), pages 5269-5296, November.
    4. Rumyantseva, Ekaterina & Furmanov, Kirill, 2017. "Realisation of mortgage property: Survival analysis," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 48, pages 22-43.
    5. Morne Joubert & Tanja Verster & Helgard Raubenheimer & Willem D. Schutte, 2021. "Adapting the Default Weighted Survival Analysis Modelling Approach to Model IFRS 9 LGD," Risks, MDPI, vol. 9(6), pages 1-17, June.
    6. Arno Botha & Tanja Verster & Roelinde Bester, 2024. "The TruEnd-procedure: Treating trailing zero-valued balances in credit data," Papers 2404.17008, arXiv.org, revised Nov 2024.
    7. Jennifer Betz & Ralf Kellner & Daniel Rösch, 2021. "Time matters: How default resolution times impact final loss rates," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(3), pages 619-644, June.
    8. Aneta Ptak-Chmielewska & Paweł Kopciuszewski & Anna Matuszyk, 2023. "Application of the kNN-Based Method and Survival Approach in Estimating Loss Given Default for Unresolved Cases," Risks, MDPI, vol. 11(2), pages 1-14, February.
    9. Joseph L. Breeden, 2024. "An Age–Period–Cohort Framework for Profit and Profit Volatility Modeling," Mathematics, MDPI, vol. 12(10), pages 1-23, May.
    10. Konstantin Belyaev & Aelita Belyaeva & Tomas Konecny & Jakub Seidler & Martin Vojtek, 2012. "Macroeconomic Factors as Drivers of LGD Prediction: Empirical Evidence from the Czech Republic," Working Papers 2012/12, Czech National Bank.

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    More about this item

    Keywords

    credit risk; recovery rate; loss given default; correlation; regulatory capital;
    All these keywords.

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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