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dc.contributor.authorHibbeln, Martinen
dc.contributor.authorGürtler, Marcen
dc.date.accessioned2012-02-09-
dc.date.accessioned2012-02-10T15:38:55Z-
dc.date.available2012-02-10T15:38:55Z-
dc.date.issued2011-
dc.identifier.pidoi:10.2139/ssrn.1757714en
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
dc.language.isogeren
dc.publisher|aTechnische Universität Braunschweig, Institut für Finanzwirtschaft |cBraunschweigen
dc.relation.ispartofseries|aWorking Paper Series |xIF35V1en
dc.subject.jelG21en
dc.subject.jelG28en
dc.subject.ddc330en
dc.subject.keywordCredit risken
dc.subject.keywordBank loansen
dc.subject.keywordLoss given defaulten
dc.subject.keywordForecastingen
dc.titlePitfalls in modeling loss given default of bank loans-
dc.typeWorking Paperen
dc.identifier.ppn684986302en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen
dc.identifier.repecRePEc:zbw:tbsifw:IF35V1en

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