The recent financial crisis has highlighted the need for better valuation models and risk management procedures, better understanding of structured products, and has called into question the actions of many financial institutions. It has become commonplace to blame the inadequacy of credit risk models, claiming that the crisis was due to sophisticated and obscure products being traded, but practitioners have for a long time been aware of the dangers and limitations of credit models. It would seem that a lack of understanding of these models is the root cause of their failures but until now little analysis had been published on the subject and, when published, it had gained very limited attention. Credit Models and the Crisis is a succinct but technical analysis of the key aspects of the credit derivatives modeling problems, tracing the development (and flaws) of new quantitative methods for credit derivatives and CDOs up to and through the credit crisis. Responding to the immediate need for clarity in the market and academic research environments, this book follows the development of credit derivatives and CDOs at a technical level, analyzing the impact, strengths and weaknesses of methods ranging from the introduction of the Gaussian Copula model and the related implied correlations to the introduction of arbitrage–free dynamic loss models capable of calibrating all the tranches for all the maturities at the same time. It also illustrates the implied copula, a method that can consistently account for CDOs with different attachment and detachment points but not for different maturities, and explains why the Gaussian Copula model is still used in its base correlation formulation. The book reports both alarming pre–crisis research and market examples, as well as commentary through history, using data up to the end of 2009, making it an important addition to modern derivatives literature. With banks and regulators struggling to fully analyze at a technical level, many of the flaws in modern financial models, it will be indispensable for quantitative practitioners and academics who want to develop stable and functional models in the future.
Professor Damiano Brigo is Chair and co-Head of the Mathematical Finance research group at Imperial College, London, ranked 8th university in the world and 3d in Europe in 2012, after Oxford and Cambridge, by Times Higher Education. Formerly Gilbart Professor and head of group at King's College, Damiano was previously Managing Director and Global Head of the Quantitative team in Fitch Solutions.
Earlier on Damiano worked as Head of Credit Models in Banca IMI's front office and as Fixed Income Professor at Bocconi University.
Damiano published more than 70 works in top journals for Mathematical Finance, Systems Theory, Probability and Statistics, and field reference books in Interest Rates and Credit Modeling for Springer and Wiley.
Damiano is Managing Editor of the International Journal of Theoretical and Applied Finance, he has been a member of the Fitch Advisory Board and is part of Scientific committees for conferences occurring at MIT and other academic and industry institutions.
Damiano has been listed as the most cited author in Risk Magazine in 2006 and 2010 and has an H-index of 24 as of September 2012 (Google Scholar).
Damiano's interests include valuation and pricing, risk measurement, credit and default modeling, counterparty risk, collateral and funding, stochastic dynamical models for commodities and inflation, the interaction between the exponential statistical manifold and the dynamic features of stochastic processes laws, nonlinear stochastic filtering, and stochastic processes consistent with mixtures of distributions.
Damiano obtained a Ph.D. in stochastic filtering with differential geometry in 1996 from the Free University of Amsterdam, following a BSc in Mathematics with honors from the University of Padua.