An Accurate Solution for Credit Value Adjustment (CVA) and Wrong Way Risk

Abstract

This paper presents a Least Square Monte Carlo approach for accurately calculating credit value adjustment (CVA). In contrast to previous studies, the model relies on the probability distribution of a default time/jump rather than the default time itself, as the default time is usually inaccessible. As such, the model can achieve a high order of accuracy with a relatively easy implementation. We find that the valuation of a defaultable derivative is normally determined via backward induction when their payoffs could be positive or negative. Moreover, the model can naturally capture wrong or right way risk.

Keywords: credit value adjustment (CVA), wrong way risk, right way risk, credit risk modeling, risky valuation, default time approach (DTA), default probability approach (DPA), collateralization, margin and netting

JEL Classification: E44, G21, G12, G24, G32, G33, G18, G28