Structured Credit Portfolio Analysis, Baskets and CDOs

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ISBN 9781584886471
Cat# C6471



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ISBN 9781420011470
Cat# CE6471



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  • Illustrates mathematical models for structured credit with many examples of practical relevance
  • Offers an accessible exposition of the foundations of structured credit portfolio modeling
  • Explains elements of financial engineering via default baskets and collateralized debt/synthetic obligations§Focuses on modeling principles that are applicable in a broad context §Considers full Monte Carlo simulation approaches as well as back-of-the-envelope calculations and scenario analyses§Provides access to a deeper understanding of the latest developments from the structured credit market§Contains a rich appendix that provides useful background information§Includes a separate chapter on references with comments on further readings
  • 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
    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