Stochastic evolution equations in portfolio credit modelling with applications to exotic credit products

TL;DR

This paper introduces a stochastic PDE-based structural credit model for large portfolios, enabling the analysis and pricing of exotic credit products like forward starting CDOs, with applications to market data calibration.

Contribution

It develops a novel stochastic PDE framework for portfolio credit risk, establishing existence and uniqueness, and applies it to pricing and calibrating exotic credit derivatives.

Findings

Model accurately prices credit indices pre and post crunch

Numerical methods effectively calibrate to market data

Demonstrates valuation of forward starting CDOs

Abstract

We consider a structural credit model for a large portfolio of credit risky assets where the correlation is due to a market factor. By considering the large portfolio limit of this system we show the existence of a density process for the asset values. This density evolves according to a stochastic partial differential equation and we establish existence and uniqueness for the solution taking values in a suitable function space. The loss function of the portfolio is then a function of the evolution of this density at the default boundary. We develop numerical methods for pricing and calibration of the model to credit indices and consider its performance pre and post credit crunch. Finally, we give further examples illustrating the valuation of exotic credit products, specifically forward starting CDOs.