(Not in Introduction to Credit Risk Modeling, Second Edition
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- e-Book: 384 pages
- Also available in Hardback
- Published: June 2010
- ISBN: 978-1-58488-993-9
- Publisher: Chapman & Hall
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- By Christian Bluhm, Ludger Overbeck and Christoph Wagner.
- Series Edited by M.A.H. Dempster, Dilip B. Madan and Rama Cont.
Series: 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.
Table of Contents
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
Reviews
Praise for the First Edition
"This is an outstanding book on the default models that are used internally by financial institutions. This practical book delves into the mathematics, the assumptions and the approximations that practitioners apply to make these models work."
—Glyn A. Holton, Contingency Analysis
"There are so many financial tools available today and numbers are likely to grow in the future. If you work in this field of credit risk modelling it is worth looking at the theoretical background, and this book is a well-rounded introduction."
—Journal of the Operational Research Society
"As an introductory survey it does an admirable job. … this book is an important guide into the field of credit risk models. Mainly for the practitioner … It is well written, fairly easy to follow."
—Horst Behncke, Zentralblatt MATH
Author Biography
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.
