An Introduction to Credit Risk Modeling

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ISBN 9781584883265
Cat# C326X
 

Features

  • Concisely presents the most fundamental and up-to-date concepts of credit portfolio management
  • Introduces modeling frameworks such as KMV, CreditMetrics, and CreditRisk+
  • Presents best practices in credit risk modeling
  • Keeps mathematical proofs to a minimum while remaining mathematically solid
  • Summary

    In today's increasingly competitive financial world, successful risk management, portfolio management, and financial structuring demand more than up-to-date financial know-how. They also call for quantitative expertise, including the ability to effectively apply mathematical modeling tools and techniques.

    An Introduction to Credit Risk Modeling supplies both the bricks and the mortar of risk management. In a gentle and concise lecture-note style, it introduces the fundamentals of credit risk management, provides a broad treatment of the related modeling theory and methods, and explores their application to credit portfolio securitization, credit risk in a trading portfolio, and credit derivatives risk. The presentation is thorough but refreshingly accessible, foregoing unnecessary technical details yet remaining mathematically precise.

    Whether you are a risk manager looking for a more quantitative approach to credit risk or you are planning a move from the academic arena to a career in professional credit risk management, An Introduction to Credit Risk Modeling is the book you've been looking for. It will bring you quickly up to speed with information needed to resolve the questions and quandaries encountered in practice.

    Table of Contents

    THE BASICS OF CREDIT RISK MANAGEMENT
    Expected Loss
    Unexpected Loss
    Regulatory Capital and the Basel Initiative
    MODELLING CORRELATED DEFAULTS
    The Bernoulli Model
    The Poisson Model
    Bernoulli Versus Poisson Mixture
    An Overview of Today's Industry Models
    One-Factor/Sector Models
    Loss Distributions by Means of Copula Functions
    Working Example: Estimation of Asset Correlations
    ASSET VALUE MODELS
    Introduction and A Small 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
    ALTERNATIVE RISK MEASURES AND CAPITAL ALLOCATION
    Coherent Risk Measures and Conditional 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
    3.
    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
    Different Roles of Banks in the CDO Market
    CDOs from the Modeling Point of View
    Rating Agency Models: Moody's BET
    Conclusion
    Some Remarks on the Literature
    Remarks
    REFERENCES

    Editorial Reviews

    "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 modeling, 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

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