Efficient Wrong-Way Risk Modelling for Funding Valuation Adjustments

Abstract

Wrong-Way Risk (WWR) is an important component in Funding Valuation Adjustment (FVA) modelling. Yet, it can be challenging to compute WWR efficiently. We propose to split the relevant exposure profile into two parts: an independent part and a WWR-driven part. For the first part, already available exposures can be used where correlations between the funding spread and market risks are ignored. We express the second part of the exposure profile in terms of the stochastic drivers and approximate these by a common Gaussian stochastic factor. The proposed approximation is generic, is an add-on to the existing xVA calculations and provides an efficient and robust way to include WWR in FVA modelling. Furthermore, the approximation provides some intuition on WWR. Case studies are presented for an interest rate swap and a representative multi-currency portfolio of swaps. They illustrate that the approximation method is applicable in a practical setting due to its generic nature. We analyze the approximation error and illustrate how the approximation can be used to compute WWR sensitivities, which are needed for risk management.