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Modelling, Pricing, and Hedging Counterparty Credit Exposure

A Technical Guide

  • Book
  • © 2009

Overview

  • Roadmap to finding practical solutions to the problem of computing counterparty credit exposure for large books of both vanilla and exotic derivatives usually traded by large Investment Banks
  • Combines a rigorous but simple mathematical approach with a practical view of the financial problem at hand
  • Includes supplementary material: sn.pub/extras

Part of the book series: Springer Finance (FINANCE)

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Table of contents (14 chapters)

  1. Methodology

  2. Architecture and Implementation

  3. Products

  4. Hedging and Managing Counterparty Risk

Keywords

About this book

It was the end of 2005 when our employer, a major European Investment Bank, gave our team the mandate to compute in an accurate way the counterparty credit exposure arising from exotic derivatives traded by the ?rm. As often happens, - posure of products such as, for example, exotic interest-rate, or credit derivatives were modelled under conservative assumptions and credit of?cers were struggling to assess the real risk. We started with a few models written on spreadsheets, t- lored to very speci?c instruments, and soon it became clear that a more systematic approach was needed. So we wrote some tools that could be used for some classes of relatively simple products. A couple of years later we are now in the process of building a system that will be used to trade and hedge counterparty credit ex- sure in an accurate way, for all types of derivative products in all asset classes. We had to overcome problems ranging from modelling in a consistent manner different products booked in different systems and building the appropriate architecture that would allow the computation and pricing of credit exposure for all types of pr- ucts, to ?nding the appropriate management structure across Business, Risk, and IT divisions of the ?rm. In this book we describe some of our experience in modelling counterparty credit exposure, computing credit valuation adjustments, determining appropriate hedges, and building a reliable system.

Authors and Affiliations

  • UBS AG, London, United Kingdom

    Giovanni Cesari, John Aquilina, Niels Charpillon, Zlatko Filipovic, Gordon Lee, Ion Manda

About the authors

Giovanni Cesari is Managing Director at UBS. He has more than 10 years' experience in modelling and pricing counterparty credit exposure. Before moving to finance, Giovanni worked for several years in particle physics and in theoretical computer science. Giovanni holds a Laurea in Electrical Engineering from the University of Trieste, a Perfezionamento in Physics from the University of Padova, and a Ph.D. from ETH, Zurich.
John Aquilina holds an M.Phil. in Statistical Science from the University of Cambridge and a Ph.D. in Mathematical Finance from the University of Bath. He has worked on modelling counterparty credit exposure at UBS since 2005.
Niels Charpillon holds a Diplôme d'Ingénieur from Ecole des Mines, an M.Sc. in Financial Mathematics from Warwick Business School, and a Licence in Economics from University of St. Etienne. He joined the counterparty exposure team at UBS in 2006.
Zlatko Filipovic started working for UBS in 2005 as a Quantitative Analyst in the counterparty exposure team. Before joining UBS, Zlatko had been working for Mako Global Derivatives, London, as a Financial Engineer. Zlatko obtained a Ph.D. in Quantitative Finance from Imperial College, London, after graduating from the Faculty of Mathematics, University of Belgrade.
Gordon Lee joined the counterparty exposure team at UBS in 2006. Prior to UBS, he was a Senior Associate in quantitative risk and performance analysis at Wilshire Associates. Gordon holds an M.A. in Mathematics from Churchill College, University of Cambridge.
Ion Manda holds a Diploma de Inginer in Software Engineering from the University of Bucharest and a M.Sc. in Financial Engineering from Birkbeck College, University of London. He has been working in the credit exposure team at UBS since 2006. Ion has about 10 years' experience as a software engineer.

 

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