Efficient Monte Carlo CVA Estimation
Proceedings of the 2014 Winter Simulation Conference
12 Pages Posted: 23 Dec 2014
Date Written: December 21, 2014
Abstract
This paper presents an overview of the efficient Monte Carlo counterparty credit risk (CCR) estimation framework recently developed by Ghamami and Zhang (2014). We focus on the estimation of credit value adjustment (CVA), one of the most widely used and regulatory-driven counterparty credit risk measures. Our proposed efficient CVA estimators are developed based on novel applications of well-known mean square error (MSE) reduction techniques in the simulation literature. Our numerical examples illustrate that the efficient estimators outperform the existing crude estimators of CVA substantially in terms of MSE.
Keywords: Risk Management, Counterparty Credit Risk, Credit Value Adjutment, Monte Carlo, Basel III
JEL Classification: C15, G1, G2
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