Two Models of Stochastic Loss Given Default

TL;DR

This paper introduces two structural models for stochastic losses given default, integrating credit losses into default event models and analyzing the effects of correlations on portfolio losses.

Contribution

The paper presents novel structural models that incorporate stochastic losses and correlations between defaults and recoveries, enhancing credit risk modeling accuracy.

Findings

Models can be calibrated to real data

Correlations significantly impact loss distributions

Models improve risk assessment for credit portfolios

Abstract

We propose two structural models for stochastic losses given default which allow to model the credit losses of a portfolio of defaultable financial instruments. 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 correlations between the occurrences of defaults and recoveries by testing our models for a representative sample portfolio.