Structured Credit Portfolio Analysis, Baskets and CDOs
Features
Summary
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.
Table of Contents
From Single Credit Risks to Credit Portfolios
Modeling Single-Name Credit Risk
Ratings and Default Probabilities
Credit Exposure
Loss Given Default
Modeling Portfolio Credit Risk
Systematic and Idiosyncratic Credit Risk
Loss Distribution of Credit Portfolios
Practicability Versus Accuracy
Default Baskets
Introductory Example: Duo Baskets
First- and Second-to-Default Modeling
Derivation of PD Term Structures
A Time-Homogeneous Markov Chain Approach
A Non-Homogeneous Markov Chain Approach
Extrapolation Problems for PD Term Structures
Duo Basket Evaluation for Multi-Year Horizons
Dependent Default Times
Default Times and PD Term Structures
Survival Function and Hazard Rate
Calculation of Default Time Densities and Hazard
Rate Functions
From Latent Variables to Default Times
Dependence Modeling via Copula Functions
Copulas in Practice
Visualization of Copula Differences and Mathematical
Description by Dependence Measures
Impact of Copula Differences to the Duo Basket
A Word of Caution
Nth-to-Default Modeling
Nth-to-Default Basket with the Gaussian Copula
Nth-to-Default Basket with the Student-t Copula
Nth-to-Default Basket with the Clayton Copula
Nth-to-Default Simulation Study
Evaluation of Cash Flows in Default Baskets
Scenario Analysis
Example of a Basket Credit-Linked Note (CLN)
Collateralized Debt and Synthetic Obligations
A General Perspective on CDO Modeling
A Primer on CDOs
Risk Transfer
Spread and Rating Arbitrage
Funding Benefits
Regulatory Capital Relief
CDO Modeling Principles
CDO Modeling Approaches
Introduction of a Sample CSO
A First-Order Look at CSO Performance
Monte Carlo Simulation of the CSO
Implementing an Excess Cash Trap
Multi-Step and First Passage Time Models
Analytic, Semi-Analytic, and Comonotonic CDO Evaluation Approaches
Single-Tranche CDOs (STCDOs)
Basics of Single-Tranche CDOs
CDS Indices as Reference Pool for STCDOs
ITraxx Europe Untranched
ITraxx Europe Index Tranches: Pricing, Delta
Hedging, and Implied Correlations
Tranche Risk Measures
Expected Shortfall Contributions
Tranche Hit Contributions of Single Names
Applications: Asset Selection, Cost-to-Securitize
Remarks on Portfolios of CDOs
Some Practical Remarks
Suggestions for Further Reading
Appendix
The Gamma Distribution
The Chi-Square Distribution
The Student-t Distribution
A Natural Clayton-Like Copula Example
Entropy-Based Rationale for Gaussian and Exponential
Distributions as Natural Standard Choices
Tail Orientation in Typical Latent Variable Credit Risk Models
The Vasicek Limit Distribution
One-Factor Versus Multi-Factor Models
Description of the Sample Portfolio
CDS Names in CDX.NA.IG and iTraxx Europe
Editorial Reviews
"For anyone who is interested in how CDOs or other instruments linked to baskets of credits are modeled, this book is essential reading. ....the book is a goldmine. If you are interested in how correlation products are modeled in practice, I can't imagine you not reading it. There is no other resource like it… the book is unique. Read it."
--Glyn A. Holton, Contingency Analysis
"This careful treatment of portfolio credit risk modeling is the first book of its type. The exposition is rigorous, relevant to real business applications, and easily accessible to those with a modeling background. Those doing research on basket credit products, or on the risk management of portfolios of corporate debt, will clearly want a copy at their side!"
-Darrell Duffie, James I. Miller Professor of Finance, The Graduate School of Business, Stanford University, California, USA
"The field of credit risk management, in general, and the modeling of structured credit products, in particular, constitutes an extremely important area of applied and methodological research in modern finance. It is very much welcomed that two well-known practitioners, both with a strong mathematical background, brought together
some of the concepts and tools which are now used by banks all over the world. Their contribution will no doubt further develop the field considerably."
-Paul Embrechts, Professor, Department of Mathematics, Swiss Federal Institute of Technology (ETH) Zurich and RiskLab, Switzerland
