Bluhm / Overbeck / Wagner Introduction to Credit Risk Modeling, Second Edition

2. Auflage 2010
ISBN: 978-1-58488-993-9
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 384 Seiten

Reihe: 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.

Zielgruppe

Advanced undergraduate and graduate students and researchers in quantitative finance and finance; practitioners in quantitative finance and investment.

Autoren/Hrsg.

Bluhm, Christian

Overbeck, Ludger

Wagner, Christoph

Fachgebiete

• Wirtschaftswissenschaften Finanzsektor & Finanzdienstleistungen Finanzsektor & Finanzdienstleistungen: Allgemeines
• Mathematik | Informatik Mathematik Stochastik

Inhaltsverzeichnis

The Basics of Credit Risk Management

Expected Loss

Unexpected Loss

Regulatory Capital and the Basel Initiative
Modeling Correlated Defaults

The Bernoulli Model

The Poisson Model

Bernoulli versus Poisson Mixture

An Overview of Common Model Concepts

One-Factor/Sector Models

Loss Dependence by Means of Copula Functions
Working Example on Asset Correlations

Generating the Portfolio Loss Distribution
Asset Value Models

Introduction and a Brief Guide to the Literature

A Few Words about Calls and Puts

Merton’s Asset Value Model

Transforming Equity into Asset Values: A Working Approach
The CreditRisk+ Model

The Modeling Framework of CreditRisk+

Construction Step 1: Independent Obligors

Construction Step 2: Sector Model
Risk Measures and Capital Allocation

Coherent Risk Measures and Expected Shortfall

Contributory Capital
Term Structure of Default Probability

Survival Function and Hazard Rate

Risk-Neutral vs. Actual Default Probabilities

Term Structure Based on Historical Default Information

Term Structure Based on Market Spreads
Credit Derivatives

Total Return Swaps

Credit Default Products

Basket Credit Derivatives

Credit Spread Products

Credit-Linked Notes
Collateralized Debt Obligations

Introduction to Collateralized Debt Obligations (CDOs)
Different Roles of Banks in the CDO Market

CDOs from the Modeling Point of View

Multi-Period Credit Models
Former Rating Agency Model: Moody’s BET

Developments, Model Issues, and Further Reading
References
Index

Über Autor(innen)

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-Nürnberg.

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.