Grid Monte Carlo in Portfolio CVA Valuation. Issue 70 (March 2014) - Qu, Dong
Abstract Credit valuation adjustment (CVA) valuation presents serious challenges to banks, as its implementation involves complex hybrid derivative modeling on large portfolios. Enhanced numerical techniques in portfolio CVA valuation not only represent an important quantitative advance, but also impact directly on banks' enterprise‐wide CVA infrastructure design and its success. This article proposes and discusses an efficient numerical technique, grid Monte Carlo (GMC), for the risk‐neutral valuation of portfolio CVA. It is shown that GMC has significant numerical advantages in terms of speed, accuracy, numerical convergence, and cost.