An Integrated Market and Credit Risk Portfolio Model

Abstract

We present a multi-step model to measure portfolio credit risk that integrates exposure simulation and portfolio credit risk techniques. Thus, it overcomes the major limitation currently shared by portfolio models with derivatives. Specifically, the model is an improvement over current portfolio credit risk models in three main aspects. First, it defines explicitly the joint evolution of market factors and credit drivers over time. Second, it models directly stochastic exposures through simulation, as in counterparty credit exposure models. Finally, it extends the Merton model of default to multiple steps. The model is computationally efficient because it combines a Mark-to-Future framework of counterparty exposures and a conditional default probability framework. Credit risk modeling is one of the most important topics in risk management and finance today. The last decade has seen the development of models for pricing credit risky instruments and derivatives, for assessing the credit worthiness ofm obligors, for managing exposures of derivatives and for computing portfolio credit losses for bonds and loan portfolios. In light of these financial innovations and modeling advances the Basle Committee on Banking Supervision has taken the first steps to amend current regulation and is reviewing the applicability of internal credit risk models for regulatory capital (Basle Committee on Banking Supervision, 1999a, 1999b). However, common practice still treats market and credit risk separately. When measuring market risk, credit risk is commonly not taken into account; when measuring portfolio credit risk, the market is assumed to be constant. The two risks are then “added ” in ad hoc ways, resulting in an incomplete picture of risk. There are two categories of credit risk