Introduction to Credit Risk Modeling, Second Edition

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.

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.

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 FunctionsWorking 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 ModelsFormer Rating Agency Model: Moody’s BET Developments, Model Issues, and Further Reading
References
Index