Abstract

http://ssrn.com/abstract=1824864
 
 

References (2)



 
 

Citations (1)



 


 



Real Time Counterparty Credit Risk Management in Monte Carlo


Luca Capriotti


Quantitative Strategies - Investment Banking Division - Credit Suisse Group

Shinghoi (Jacky) Lee


Quantitative Strategies - Investment Banking Division - Credit Suisse Group

Matthew Peacock


Credit Suisse AG

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.

Number of Pages in PDF File: 7

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

JEL Classification: C63

working papers series


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Date posted: April 28, 2011  

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: http://ssrn.com/abstract=1824864 or http://dx.doi.org/10.2139/ssrn.1824864

Contact Information

Luca Capriotti (Contact Author)
Quantitative Strategies - Investment Banking Division - Credit Suisse Group ( email )
Eleven Madison Avenue
New York, NY 10010
United States
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 Group ( email )
CRTI 4
P.O. Box
Zurich, CH-8070
Switzerland
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