COUNTERPARTY CREDIT RISK IN A CLEARING NETWORK
Abstract
In this paper, we offer a network model that derives the expected counterparty risk of an arbitrary market after netting in a closed-form expression. Graph theory is used to represent market participants and their relationship among each other. We apply the powerful theory of characteristic functions (c.f.) and Hilbert transforms to determine the expected counterparty risk. The latter concept is used to express the c.f. of the random variable (r.v.) max(Y,0) in terms of the c.f. of the r.v. Y. This paper applies this concept for the first time in mathematical finance in order to generalize results of Duffie & Zhu (2011), in several ways. The introduced network model is applied to study the features of an over-the-counter and a centrally cleared market. We also give a more general answer to the question of whether it is more advantageous for the overall counterparty risk to clear via a central counterparty or classically bilateral between the two involved counterparties.