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Real Time Counterparty Credit Risk Management in Monte Carlo

7 Pages Posted: 28 Apr 2011  

Luca Capriotti

Quantitative Strategies - Investment Banking Division - Credit Suisse Group; University College London

Shinghoi (Jacky) Lee

Quantitative Strategies - Investment Banking Division - Credit Suisse Group

Matthew Peacock

Credit Suisse AG

Date Written: April 27, 2011

Abstract

Adjoint algorithmic differentiation can be used to implement efficiently the calculation of counterparty credit risk. We demonstrate how this powerful technique can be used to reduce the computational cost by hundreds of times, thus opening the way to real time risk management in Monte Carlo.

Keywords: Algorithmic Differentiation, Monte Carlo Simulations, Derivatives Pricing, Credit Derivatives

JEL Classification: C63

Suggested Citation

Capriotti, Luca and Lee, Shinghoi (Jacky) and Peacock, Matthew, Real Time Counterparty Credit Risk Management in Monte Carlo (April 27, 2011). Risk Magazine (in press). Available at SSRN: https://ssrn.com/abstract=1824864 or http://dx.doi.org/10.2139/ssrn.1824864

Luca Capriotti (Contact Author)

Quantitative Strategies - Investment Banking Division - Credit Suisse Group ( email )

Eleven Madison Avenue
New York, NY 10010
United States

University College London ( email )

Gower Street
London, WC1E 6BT
United Kingdom

Shinghoi (Jacky) Lee

Quantitative Strategies - Investment Banking Division - Credit Suisse Group ( email )

Eleven Madison Avenue
New York, NY 10010
United States

Matthew Peacock

Credit Suisse AG ( email )

CRTI 4
P.O. Box
Zurich, CH-8070
Switzerland

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