2010. 2nd Edition. Hardcover. Illustrating mathematical models for structured credit with practical examples, this book presents an introduction to the foundations of structured credit portfolio modeling. It features material on estimation of asset correlations, and benchmark correlations based on securitizations of benchmark portfolios in the market. Series Editor(s): Dempster, M. A. H.; Cont, Rama; Madan, Dilip B. Series: Chapman & Hall/CRC Financial Mathematics Series. Num Pages: 384 pages, 50 black & white illustrations, 18 black & white tables. BIC Classification: KFFL. Category: (U) Tertiary Education (US: College). Dimension: 155 x 241 x 25. Weight in Grams: 700. . . . . . Books ship from the US and Ireland.

Bestandsnummer des Verk�ufers V9781584889922

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Bibliografische Details

Titel: Introduction to Credit Risk Modeling
Verlag: Taylor & Francis Inc
Erscheinungsjahr: 2010
Sprache: Englisch
ISBN-10: 1584889926
ISBN-13: 9781584889922
Einband: Hardcover
Auflage: 2. Auflage
Zustand: New

�ber diesen Titel

Inhaltsangabe

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.

�ber die Autorin bzw. den Autor

Over the years, Christian Bluhm has worked for Deutsche Bank, McKinsey, HypoVereinsbank’s Group Credit Portfolio Management, and Credit Suisse. He earned a Ph.D. in mathematics from the University of Erlangen-N�rnberg.

Ludger Overbeck is a professor of probability theory and quantitative finance and risk management in the Institute of Mathematics at the University of Giessen. During his career, he worked for Deutsche Bundesbank, Deutsche Bank, HypoVereinsbank/UniCredit, DZBank, and Commerzbank. He earned a Ph.D. in mathematics from the University of Bonn.

Christoph Wagner has worked for Deutsche Bank, Allianz Group Center, UniCredit/HypoVereinsbank, and Allianz Risk Transfer. He earned a Ph.D. in statistical physics from the Technical University of Munich.

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