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The Oxford Handbook of Credit Derivatives Oxford Handbooks in Finance

Andrew Rennie

Published by Oxford University Press
ISBN 10: 0199546789 / ISBN 13: 9780199546787
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Title: The Oxford Handbook of Credit Derivatives ...

Publisher: Oxford University Press

Binding: Hardcover

Book Condition: New

Book Type: Hardcover

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Hardcover. 736 pages. Dimensions: 9.8in. x 6.5in. x 1.9in.From the late nineties, the spectacular growth of a secondary market for credit through derivatives has been matched by the emergence of mathematical modeling analysing the credit risk embedded in these contracts. This book aims to provide a broad and deep overview of this modeling, covering statistical analysis and techniques, modeling of default of both single and multiple entities, counterparty risk, Gaussian and non-Gaussian modeling, and securitization. Both reduced-form and firm-value models for the default of single entities are considered in detail, with extensive discussion of both their theoretical underpinnings and practical usage in pricing and risk. For multiple entity modeling, the now notorious Gaussian copula is discussed with analysis of its shortcomings, as well as a wide range of alternative approaches including multivariate extensions to both firm-value and reduced form models, and continuous-time Markov chains. One important case of multiple entities modeling--counterparty risk in credit derivatives--is further explored in two dedicated chapters. Alternative non-Gaussian approaches to modelling are also discussed, including extreme-value theory and saddle-point approximations to deal with tail risk. Finally, the recent growth in securitization is covered, including house price modeling and pricing models for asset-backed CDOs. The current credit crisis has brought modeling of the previously arcane credit markets into the public arena. Lipton and Rennie with their excellent team of contributors, provide a timely discussion of the mathematical modeling that underpins both credit derivatives and securitization. Though technical in nature, the pros and cons of various approaches attempt to provide a balanced view of the role that mathematical modeling plays in the modern credit markets. This Handbook will appeal to students and researchers in statistics, economics, and finance, as well as practicioners, credit traders, and quantitative analysts. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Bookseller Inventory # 9780199546787

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Synopsis: From the late nineties, the spectacular growth of a secondary market for credit through derivatives has been matched by the emergence of mathematical modeling analysing the credit risk embedded in these contracts. This book aims to provide a broad and deep overview of this modeling, covering statistical analysis and techniques, modeling of default of both single and multiple entities, counterparty risk, Gaussian and non-Gaussian modeling, and securitization. Both reduced-form and firm-value models for the default of single entities are considered in detail, with extensive discussion of both their theoretical underpinnings and practical usage in pricing and risk. For multiple entity modeling, the now notorious Gaussian copula is discussed with analysis of its shortcomings, as well as a wide range of alternative approaches including multivariate extensions to both firm-value and reduced form models, and continuous-time Markov chains. One important case of multiple entities modeling--counterparty risk in credit derivatives--is further explored in two dedicated chapters. Alternative non-Gaussian approaches to modelling are also discussed, including extreme-value theory and saddle-point approximations to deal with tail risk. Finally, the recent growth in securitization is covered, including house price modeling and pricing models for asset-backed CDOs.

The current credit crisis has brought modeling of the previously arcane credit markets into the public arena. Lipton and Rennie with their excellent team of contributors, provide a timely discussion of the mathematical modeling that underpins both credit derivatives and securitization. Though technical in nature, the pros and cons of various approaches attempt to provide a balanced view of the role that mathematical modeling plays in the modern credit markets. This Handbook will appeal to students and researchers in statistics, economics, and finance, as well as practicioners, credit traders, and quantitative analysts.

About the Author:
Alexander Lipton is a Managing Director and Co-Head of the Global Quantitative Group at Bank of America Merrill Lynch, and Visiting Professor of Mathematics at Imperial College. Prior to his current role, he was Managing Director and Head of Capital Structure Quantitative Research at Citadel Investment Group in Chicago. He has also worked at Credit Suisse, Deutsche Bank, and Bankers Trust. Previously, he was a Full Professor of Mathematics at the University of Illinois, Chicago, and Consultant at Los Alamos National Laboratory. He received his undergraduate and graduate degrees from Moscow State University. Professor Lipton is author of two books and editor of three. He has published numerous research papers on hydrodynamics, magnetohydrodynamics, astrophysics, and financial engineering. He has delivered many invited lectures at leading universities and major conferences worldwide.

Andrew Rennie has spent sixteen years in finance, specialising in derivatives pricing and risk management. He has worked at UBS, Rabobank International, and Merrill Lynch, where he managed all quantitative and modelling activity in derivatives across fixed income, credit, foreign exchange, commodities, and equities globally. He retired from Merrill Lynch in 2009 to advise on pricing and risk issues to governments, regulators, banks, and hedge funds. He graduated with a First in Mathematics from Cambridge University and published papers in Mathematical Chemistry on the properties of one-dimensional inclusion compounds. He co-authored a textbook on derivative pricing- Financial Calculus- and has also co-edited Credit Correlation - Life after Copulas.

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