The financial industry is swamped by credit products whose economic performance is linked to the performance of some underlying portfolio of credit-risky instruments, like loans, bonds, swaps, or asset-backed securities. Financial institutions continuously use these products for tailor-made long and short positions in credit risks. Based on a steadily growing market, there is a high demand for concepts and techniques applicable to the evaluation of structured credit products. Written from the perspective of practitioners who apply mathematical concepts to structured credit products, Structured Credit Portfolio Analysis, Baskets & CDOs starts with a brief wrap-up on basic concepts of credit risk modeling and then quickly moves on to more advanced topics such as the modeling and evaluation of basket products, credit-linked notes referenced to credit portfolios, collateralized debt obligations, and index tranches. The text is written in a self-contained style so readers with a basic understanding of probability will have no difficulties following it. In addition, many examples and calculations have been included to keep the discussion close to business applications. Practitioners as well as academics will find ideas and tools in the book that they can use for their daily work.

The financial industry is swamped by credit products whose economic performance is linked to the performance of some underlying portfolio of credit-risky instruments, like loans, bonds, swaps, or asset-backed securities. Financial institutions continuously use these products for tailor-made long and short positions in credit risks. Based on a steadily growing market, there is a high demand for concepts and techniques applicable to the evaluation of structured credit products. Written from the perspective of practitioners who apply mathematical concepts to structured credit products, Structured Credit Portfolio Analysis, Baskets & CDOs starts with a brief wrap-up on basic concepts of credit risk modeling and then quickly moves on to more advanced topics such as the modeling and evaluation of basket products, credit-linked notes referenced to credit portfolios, collateralized debt obligations, and index tranches. The text is written in a self-contained style so readers with a basic understanding of probability will have no difficulties following it. In addition, many examples and calculations have been included to keep the discussion close to business applications. Practitioners as well as academics will find ideas and tools in the book that they can use for their daily work.

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.

Jeder Kredit birgt fur den Kreditgeber ein Risiko, da unsicher ist, ob der Kreditnehmer seinen Zahlungsverpflichtungen nachkommen wird. Gemessen wird dieses Kreditrisiko mit Hilfe statistischer Methoden. Vor dem Hintergrund Basel II hat die Kreditrisikomessung an Bedeutung gewonnen. Dieses Buch schliesst die Lucke zwischen statistischer Grundlagenliteratur und mathematisch anspruchsvollen Werken. Es bietet einen Einstieg in die Kreditrisikomessung und die dafur notwendige Statistik. Ausgehend von den wichtigsten Begriffen zum Kreditrisiko werden deren statistische Analoga beschrieben. Enthalten sind relevante statistische Verteilungen und eine Einfuhrung in stochastische Prozesse, Portfoliomodelle und Score- bzw. Ratingmodelle. Zahlreiche praxisnahe Beispiele ermoeglichen den idealen Einstieg fur Praktiker und Quereinsteiger.