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

2. Auflage 2016
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

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

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.