Credit valuation adjustment wrong-way risk in a Gaussian copula model

Kelin Pan and Chandra Khandrika

Abstract

The credit valuation adjustment (CVA) is currently calculated in financial institutions to measure counterparty credit risk (CCR) on over-the-counter derivatives. A key factor in CVA is wrong-way risk (WWR): the correlation between counterparty exposures and credit qualities. In this paper, we present an analytical expression for CVA with WWR under the assumption of the lognormally distributed trade value. Using a Gaussian latent variable to drive market–credit correlation, the calculation of WWR is easily incorporated into the existing exposure simulation process in a CCR system. The proposed CVA with WWR model is used to find the CVA alpha that is a function of the market–credit correlation and the counterparty credit quality. The CVA alpha is used to study general WWR and specific WWR. The numerical results show that the entity’s rating downgrade has more of an impact on specific WWR than on general WWR.