Credit Models and the Crisis (ePub)

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.