The Oxford handbook of credit derivatives / edited by Alexander Lipton and Andrew Rennie.

Includes bibliographical references and indexes.

PART I: INTRODUCTION -- 1. Non-technical Introduction -- 2. Technical Introduction -- PART II: STATISTICAL OVERVIEW -- 3. Default Recovery Rates and LGD in Credit Risk Modelling and Practice -- 4. A Guide to Modelling Credit Term Structures -- 5. Statistical Data Mining Procedures in Generalized Cox Regressions -- PART III: SINGLE AND MULTI-NAME THEORY -- 6. An Exposition of CDS Market Models -- 7. Single and Multi-name Credit Derivatives: Theory and Practice -- 8. Marshall-Olkin Copula Based Models -- 9. Contagion Models in Credit Risk -- 10. Markov Chain Models of Portfolio Credit Risk -- 11. Counterparty Risk in Credit Derivative Contracts -- 12. Credit Value Adjustment in the Extended Structural Default Model -- PART IV: BEYOND NORMALITY -- 13. A New Philosophy of the Market -- 14. An EVT Primer for Credit Risk -- 15. Saddlepoint Methods in Portfolio Theory -- PART V: SECURITZATION -- 16. Quantitative Aspects of the Collapse of the Parallel Banking System -- 17. Home Price Derivatives and Modelling -- 18. A Valuation Model for ABS CDOs.

From the late 1990s, the spectacular growth of a secondary market for credit through derivatives has been matched by the emergence of mathematical modelling analysing the credit risk embedded in these contracts. This book aims to provide a broad and deep overview of this modelling, covering statistical analysis and techniques, modelling of default of both single and multiple entities, counterparty risk, Gaussian and non-Gaussian modelling, and securitisation. 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 modelling, 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 modelling - 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 securitisation is covered, including house price modelling and pricing models for asset-backed CDOs. The current credit crisis has brought modelling 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 modelling that underpins both credit derivatives and securitisation. Though technical in nature, the pros and cons of various approaches attempt to provide a balanced view of the role that mathematical modelling plays in the modern credit markets.

This book will appeal to students and researchers in statistics, economics, and finance, as well as practitioners, credit traders, and quantitative analysts.