Loss Given Default Modelling: Comparative Analysis
AbstractIn this study we investigated several most popular Loss Given Default (LGD) models (LSM, Tobit, Three-Tiered Tobit, Beta Regression, Inflated Beta Regression, Censored Gamma Regression) in order to compare their performance. We show that for a given input data set, the quality of the model calibration depends mainly on the proper choice (and availability) of explanatory variables (model factors), but not on the fitting model. Model factors were chosen based on the amplitude of their correlation with historical LGDs of the calibration data set. Numerical values of non-quantitative parameters (industry, ranking, type of collateral) were introduced as their LGD average. We show that different debt instruments depend on different sets of model factors (from three factors for Revolving Credit or for Subordinated Bonds to eight factors for Senior Secured Bonds). Calibration of LGD models using distressed business cycle periods provide better fit than data from total available time span. Calibration algorithms and details of their realization using the R statistical package are presented. We demonstrate how LGD models can be used for stress testing. The results of this study can be of use to risk managers concerned with the Basel accord compliance.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 46147.
Date of creation: 27 Mar 2013
Date of revision:
LGD; Credit Risk; LGD model; Linear regression; Tobit model; Stress testing;
Find related papers by JEL classification:
- G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies
- G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
- G19 - Financial Economics - - General Financial Markets - - - Other
- G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-04-20 (All new papers)
- NEP-BAN-2013-04-20 (Banking)
- NEP-RMG-2013-04-20 (Risk Management)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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- Radovan Chalupka & Juraj Kopecsni, 2008. "Modelling Bank Loan LGD of Corporate and SME Segments: A Case Study," Working Papers IES 2008/27, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Nov 2008.
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- 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, 07.
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