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dc.contributor.authorHibbeln, Martinen_US
dc.contributor.authorGürtler, Marcen_US
dc.date.accessioned2012-02-09en_US
dc.date.accessioned2012-02-10T15:38:55Z-
dc.date.available2012-02-10T15:38:55Z-
dc.date.issued2011en_US
dc.identifier.pidoi:10.2139/ssrn.1757714en_US
dc.identifier.urihttp://hdl.handle.net/10419/55246-
dc.description.abstractThe parameter loss given default (LGD) of loans plays a crucial role for risk-based decision making of banks including risk-adjusted pricing. Depending on the quality of the estimation of LGDs, banks can gain significant competitive advantage. For bank loans, the estimation is usually based on discounted recovery cash flows, leading to workout LGDs. In this paper, we reveal several problems that may occur when modeling workout LGDs, leading to LGD estimates which are biased or have low explanatory power. Based on a data set of 71,463 defaulted bank loans, we analyze these issues and derive recommendations for action in order to avoid these problems. Due to the restricted observation period of recovery cash flows the problem of length-biased sampling occurs, where long workout processes are underrepresented in the sample, leading to an underestimation of LGDs. Write-offs and recoveries are often driven by different influencing factors, which is ignored by the empirical literature on LGD modeling. We propose a two-step approach for modeling LGDs of non-defaulted loans which accounts for these differences leading to an improved explanatory power. For LGDs of defaulted loans, the type of default and the length of the default period have high explanatory power, but estimates relying on these variables can lead to a significant underestimation of LGDs. We propose a model for defaulted loans which makes use of these influence factors and leads to consistent LGD estimates.en_US
dc.language.isogeren_US
dc.publisherInstitut für Finanzwirtschaft, Technische Universität Braunschweig Braunschweigen_US
dc.relation.ispartofseriesWorking papers // Institut für Finanzwirtschaft, Technische Universität Braunschweig IF35V1en_US
dc.subject.jelG21en_US
dc.subject.jelG28en_US
dc.subject.ddc330en_US
dc.subject.keywordCredit risken_US
dc.subject.keywordBank loansen_US
dc.subject.keywordLoss given defaulten_US
dc.subject.keywordForecastingen_US
dc.titlePitfalls in modeling loss given default of bank loansen_US
dc.typeWorking Paperen_US
dc.identifier.ppn684986302en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen_US
dc.identifier.repecRePEc:zbw:tbsifw:IF35V1-
Appears in Collections:Working Paper Series, Institut für Finanzwirtschaft, TU Braunschweig

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