Deficiencies of the Basel III standard approach for CVA capital charge led to fundamental changes in the proposed Fundamental Review of the Trading Book FRTB SA-CVA framework. With this approach, banks have to compute CVA sensitivities to a large number of market risk factors, which are typically in the hundreds or even thousands. The FRTB-CVA document states: “CVA sensitivities to market risk factors are computationally very expensive.” (While this is true for the traditional bump-and-revalue approach (finite differences) as it means hundreds to thousands of revaluations of the entire CVA multi-step Monte-Carlo simulation, Adjoint Algorithmic Differentiation (AAD) provides a way out. With AAD, all sensitivities can be obtained at a small additional computational cost compared to a single valuation.
This paper gives a brief overview of the proposed FRTB SA-CVA framework, discusses the complexities and reviews approaches for computing CVA sensitivities. It shows how AAD can be applied leading to large performance gains and gives practical implementation guidelines.