Credit risk modeling for catastrophic events

Abstract

Estimating default probabilities of companies is one of the fundamental tasks in credit risk models and lending decision-making. One area of particular interest is how the companies' asset value behaves in the presence of unforeseen external shocks or catastrophes. On one hand, we want the default probabilities to address the likelihood of catastrophes correctly, and on the other hand, we want to be able to perform what-if analysis to investigate the possible consequences of catastrophes. This study proposes a framework to perform such what-if analysis in the jump diffusion framework.