Generalized beta regression models for random loss-given-default

DELFT UNIVERSITY OF TECHNOLOGY REPORT 08-10 Generalized Beta Regression Models for Random Loss-Given-Default

We propose a new framework for modeling systematic risk in LossGiven-Default (LGD) in the context of credit portfolio losses. The class of models is very flexible and accommodates well skewness and heteroscedastic errors. The quantities in the models have simple economic interpretation. Inference of models in this framework can be unified. Moreover, it allows efficient numerical procedures, suc...

Estimating bank loans loss given default by generalized additive models

Benchmarking regression algorithms for loss given default modeling

The introduction of the Basel II Accord has had a huge impact on financial institutions, allowing them to build credit risk models for three key risk parameters: PD (probability of default), LGD (loss given default) and EAD (exposure at default). Until recently, credit risk research has focused largely on the estimation and validation of the PD parameter, and much less on LGD modeling. In this ...

Two models of stochastic loss given default

We propose two structural models for stochastic loss given default that allow the credit losses of a portfolio of defaultable financial instruments to be modeled. The credit losses are integrated into a structural model of default events accounting for correlations between the default events and the associated losses. We show how the models can be calibrated and analyze the impact of correlatio...

Loss given default models incorporating macroeconomic variables for credit cards

Based onUKdata formajor retail credit cards,we build severalmodels of Loss GivenDefault based on account level data, including Tobit, a decision tree model, a Beta and fractional logit transformation. We find that Ordinary Least Squares models with macroeconomic variables perform best for forecasting Loss Given Default at the account and portfolio levels on independent hold-out data sets. The i...