EconPapers    
Economics at your fingertips  
 

A Non-parametric Approach to Incorporating Incomplete Workouts Into Loss Given Default Estimates

Grazia Rapisarda and David Echeverry

MPRA Paper from University Library of Munich, Germany

Abstract: When estimating Loss Given Default (LGD) parameters using a workout approach, i.e. discounting cash flows over the workout period, the problem arises of how to take into account partial recoveries from incomplete work-outs. The simplest approach would see LGD based on complete recovery profiles only. Whilst simple, this approach may lead to data selection bias, which may be at the basis of regulatory guidance requiring the assessment of the relevance of incomplete workouts to LGD estimation. Despite its importance, few academic contributions have covered this topic. We enhance this literature by developing a non-parametric estimator that -under certain distributional assumptions on the recovery profiles- aggregates complete and incomplete workout data to produce unbiased and more efficient estimates of mean LGD than those obtained from the estimator based on resolved cases only. Our estimator is appropriate in LGD estimation for wholesale portfolios, where the exposure-weighted LGD estimators available in the literature would not be applicable under Basel II regulatory guidance.

Keywords: Credit risk; bank loans; loss-given-default; LGD; incomplete observations; mortality curves (search for similar items in EconPapers)
JEL-codes: C14 G32 (search for similar items in EconPapers)
Date: 2010-11-16, Revised 2010-11-16
New Economics Papers: this item is included in nep-ban, nep-ecm and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/26797/1/MPRA_paper_26797.pdf original version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:26797

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().

 
Page updated 2025-03-19
Handle: RePEc:pra:mprapa:26797