Cutting CVA's complexity

Calculating credit value adjustments can be very numerically intensive, often involving nested Monte Carlo simulations. Pierre Henry-Labordère uses marked branching diffusions to construct an efficient algorithm based on a Galton-Watson random tree, to dramatically reduce computational costs

The recent financial crisis has highlighted the importance of the credit value adjustment (CVA) when pricing derivatives. Bilateral counterparty risk is the risk that the issuer of a derivative, or its counterparty, may default prior to the expiry and fail to make future payments. For Markovian models, this leads naturally to non-linear second-order parabolic partial differential equations (PDEs) to price the contract. More precisely, the non-linearity in the pricing equation affects none of the