Modeling and estimating dependent loss given default

Economics Working Paper 2014-2: Further Investigation of Parametric Loss Given Default Modeling

We conduct a comprehensive study of some new or recently developed parametric methods to estimate loss given default using a common data set. We first propose to use a smearing estimator, a Monte Carlo estimator, and a global adjustment to refine transformation regressions that address loss given default boundary values. Although these refinements only marginally improve model performance, the ...

Modeling Expected Loss

This paper develops a methodology for modeling and estimating expected loss over arbitrary horizons. We jointly model the probability of default and the recovery rate given default. Different model specifications are estimated using an extensive default and recovery data set that contains the majority of defaults between 1980–2004 of AMEX, NYSE and NASDAQ listed companies. We undertake extensiv...

A framework for loss given default validation of retail portfolios

Modeling and estimating loss given default (LGD) is necessary for banks that apply for the internal ratings based approach for retail portfolios. To validate LGD estimations, there are only a few approaches discussed in the literature. In this paper, two models for validating relative LGD and absolute losses are developed. The validation of relative LGD is important for risk-adjusted credit pri...

Estimating bank loans loss given default by generalized additive models

Asymptotic Analysis of the Loss Given Default in the Presence of Multivariate Regular Variation

Consider a portfolio of n obligors subject to possible default. We propose a new structural model for the loss given default, which takes into account the severity of default. Then we study the tail behavior of the loss given default under the assumption that the losses of the n obligors jointly follow a multivariate regular variation structure. This structure provides an ideal framework for mo...