Reads Introduction to Credit Risk Modeling (Chapman & Hall/CRC Financial Mathematics Series)

Description Introduction to Credit Risk Modeling (Chapman & Hall/CRC Financial Mathematics Series)

Contains Nearly 100 Pages of New Material The recent financial crisis has shown that credit risk in particular and finance in general remain important fields for the application of mathematical concepts to real-life situations. While continuing to focus on common mathematical approaches to model credit portfolios, Introduction to Credit Risk Modeling, Second Edition presents updates on model developments that have occurred since the publication of the best-selling first edition. New to the Second Edition An expanded section on techniques for the generation of loss distributions Introductory sections on new topics, such as spectral risk measures, an axiomatic approach to capital allocation, and nonhomogeneous Markov chains Updated sections on the probability of default, exposure-at-default, loss-given-default, and regulatory capital A new section on multi-period models Recent developments in structured credit The financial crisis illustrated the importance of effectively communicating model outcomes and ensuring that the variation in results is clearly understood by decision makers. The crisis also showed that more modeling and more analysis are superior to only one model. This accessible, self-contained book recommends using a variety of models to shed light on different aspects of the true nature of a credit risk problem, thereby allowing the problem to be viewed from different angles.

Introduction to Credit Risk Modeling (Chapman & Hall/CRC Financial Mathematics Series) ebooks

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©2003 CRC Press LLC - UNTAG ~ His main responsibilities are the credit portfolio model for the group-wide RAROC process, the risk assesement of credit derivatives, ABS, and other securitization products, and operational risk modeling. Before joining Deutsche Bank in 1997, he worked with the Deutsche Bundesbank in the supervision department, examining internal market risk .

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