A comprehensive look at the enormous growth and evolution of distressed debt, corporate
bankruptcy, and credit risk default This Third Edition of the most authoritative finance book …

This paper studies loss given default using a large set of historical loan-level default and
recovery data of high loan-to-value residential mortgages from several private mortgage …

We compare six modeling methods for Loss Given Default (LGD). We find that non-
parametric methods (regression tree and neural network) perform better than parametric …

Three main variables affect the credit risk of a financial asset:(i) the probability of default
(PD);(ii) the 'loss given default'(LGD), which is equal to one minus the recovery rate in the …

Logistic quantile regression (LQR) is used for studying recovery rates. It is developed using
monotone transformations. Using Moody's Ultimate Recovery Database, we show that the …

A vast majority of Loss Given Default (LGD) models are currently in use. Over all the years
since the new Capital Accord was published in June 2004, there has been increasing …

The financial crisis that began in 2008 placed renewed emphasis and responsibility on
financial institutions to assess financial risks and provide evidence of adequate capital to …

Jordanian banks traditionally use a set of indicators, based on their internal explicit
knowledge to examine the credit risk caused by default loans of individual borrowers. The …

In this paper we describe a methodology for deriving the upper and lower profit and loss
(P&L) bounds in the presence of counterparty risk that does not rely on either structural or …

Abstract When estimating Loss Given Default (LGD) parameters using a workout approach,
ie discounting cash flows over the workout period, the problem arises of how to take into …