Pricing and hedging collateralized loan obligations with implied factor models

Jovan Nedeljkovic, Dan Rosen, David Saunders

Abstract

ABSTRACT

The current financial crisis has highlighted the need for transparent and robust methods for valuing and hedging structured credit portfolios. First-generation models such as Gaussian copula-based methods have documented practical and theoretical limitations well. In this paper we demonstrate the practical application of the weighted Monte Carlo methodology for valuing and computing sensitivities and risk statistics for collateralized loan obligation (CLO) portfolios and CLOsquared structures. The model extends the full bottom-up approach of Rosen and Saunders for pricing bespoke collateralized debt obligations to include cancelability and stochastic losses given default in a natural way. The performance of the model is analyzed across a three-month period in 2008 during the credit crisis. The model calibrates very well to observed prices for the CDX.HY and LCDX indices, and provides stable implied distributions for the systematic factor. Furthermore, it gives robust, consistent prices and sensitivities for CLOs and CLO-squared transactions, even during this very volatile period.