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Modeling Bank Loan LGD of Corporate and SME Segments: A Case Study

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Abstract

Loss given default (LGD) is one of key parameters to estimate credit risk in an internal rating based approach considered in The New Basel Capital Accord. The aim of this paper is to find determinants of LGD using a set of firm loan micro-data of an anonymous Czech commercial bank. The authors find that LGD is driven primarily by the period of loan origination, relative value of collateral, loan size and length of business relationship. Different models employed in their analysis provide similar results; in more complex models, log-log models appear to perform better, implying an asymmetric response of the dependent variable.

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  • Radovan Chalupka & Juraj Kopecsni, 2009. "Modeling Bank Loan LGD of Corporate and SME Segments: A Case Study," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 59(4), pages 360-382, Oktober.
  • Handle: RePEc:fau:fauart:v:59:y:2009:i:4:p:360-382
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    1. Radovan Chalupka & Juraj Kopecsni, 2009. "Modeling Bank Loan LGD of Corporate and SME Segments: A Case Study," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 59(4), pages 360-382, Oktober.
    2. Jakub Seidler & Petr Jakubík, 2009. "Implied Market Loss Given Default in the Czech Republic: Structural-Model Approach," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 59(1), pages 20-40, January.
    3. Renault, Olivier & Scaillet, Olivier, 2004. "On the way to recovery: A nonparametric bias free estimation of recovery rate densities," Journal of Banking & Finance, Elsevier, vol. 28(12), pages 2915-2931, December.
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    5. Mark Carey, 1998. "Credit Risk in Private Debt Portfolios," Journal of Finance, American Finance Association, vol. 53(4), pages 1363-1387, August.
    6. Thorburn, Karin S., 2000. "Bankruptcy auctions: costs, debt recovery, and firm survival," Journal of Financial Economics, Elsevier, vol. 58(3), pages 337-368, December.
    7. R. A. Rigby & D. M. Stasinopoulos, 2005. "Generalized additive models for location, scale and shape," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(3), pages 507-554, June.
    8. Jon Frye, 2000. "Depressing recoveries," Emerging Issues, Federal Reserve Bank of Chicago, issue Oct.
    9. Dermine, J. & de Carvalho, C. Neto, 2006. "Bank loan losses-given-default: A case study," Journal of Banking & Finance, Elsevier, vol. 30(4), pages 1219-1243, April.
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    1. Radovan Chalupka & Juraj Kopecsni, 2009. "Modeling Bank Loan LGD of Corporate and SME Segments: A Case Study," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 59(4), pages 360-382, Oktober.
    2. Yaldız Hanedar, Elmas & Broccardo, Eleonora & Bazzana, Flavio, 2014. "Collateral requirements of SMEs: The evidence from less-developed countries," Journal of Banking & Finance, Elsevier, vol. 38(C), pages 106-121.
    3. Jakub Seidler & Petr Jakubík, 2009. "Implied Market Loss Given Default in the Czech Republic: Structural-Model Approach," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 59(1), pages 20-40, January.
    4. Maria Stefanova, 2012. "Recovery Risiko in der Kreditportfoliomodellierung," Springer Books, Springer, number 978-3-8349-4226-5, December.
    5. Natalia Nehrebecka, 2019. "Bank loans recovery rate in commercial banks: A case study of non-financial corporations," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 37(1), pages 139-172.
    6. Elmas Yaldiz Hanedar & Eleonora Broccardo & Flavio Bazzana, 2012. "Collateral Requirements of SMEs:The Evidence from Less–Developed Countries," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0034, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    7. Miller, Patrick & Töws, Eugen, 2018. "Loss given default adjusted workout processes for leases," Journal of Banking & Finance, Elsevier, vol. 91(C), pages 189-201.
    8. Raffaella Calabrese, 2012. "Estimating bank loans loss given default by generalized additive models," Working Papers 201224, Geary Institute, University College Dublin.
    9. Aneta Ptak-Chmielewska & Paweł Kopciuszewski, 2023. "Application of the Bayesian approach in loss given default modelling," Bank i Kredyt, Narodowy Bank Polski, vol. 54(6), pages 625-650.
    10. Tomas Konecny & Jakub Seidler & Aelta Belyaeva & Konstantin Belyaev, 2017. "The Time Dimension of the Links Between Loss Given Default and the Macroeconomy," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 67(6), pages 462-491, October.
    11. Yang, Bill Huajian & Tkachenko, Mykola, 2012. "Modeling of EAD and LGD: Empirical Approaches and Technical Implementation," MPRA Paper 57298, University Library of Munich, Germany.
    12. Wojciech Starosta, 2020. "Modelling Recovery Rate for Incomplete Defaults Using Time Varying Predictors," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 12(2), pages 195-225, June.
    13. 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.
    14. Yashkir, Olga & Yashkir, Yuriy, 2013. "Loss Given Default Modelling: Comparative Analysis," MPRA Paper 46147, University Library of Munich, Germany.
    15. Han, Chulwoo & Jang, Youngmin, 2013. "Effects of debt collection practices on loss given default," Journal of Banking & Finance, Elsevier, vol. 37(1), pages 21-31.

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    More about this item

    Keywords

    credit risk; loss given default; fractional responses; ordinal regression; quasi-maximum likelihood estimator;
    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

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