http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
"Preface Second Edition The first edition of this book appeared eight years ago. Since then the banking industry experienced a lot of change and challenges. The most recent financial crisis which started around May 2007 and lasted in its core period until early 2009 gave rise for a lot of scepticism whether credit risk models are appropriate to capture the true nature of risks inherent in credit portfolios in general and structured credit products in particular. In a recent article two of us discuss common credit risk modeling approaches in the light of the most recent crisis and invite readers to participate in the discussion; see [25]. A key observation in a discussion like the one in [25] is that the universe of available models and tools is sufficiently rich for doing a good job even in a severe crisis scenario as banks recently experienced it. What seems to be more critical is an appropriate model choice, parameterization of models, dealing with uncertainties, e.g., based on insufficient data, and communication of model outcomes to decision makers and executive senior management. These are the four main areas of challenge where we think that a lot of work and rethinking needs to be done in a p͡ost-crisis ̕reflection of credit risk models. In the first edition of this book we focussed on the description of common mathematical approaches to model credit portfolios. We did not change this philosophy for the second edition. Therefore, we left large parts of the book unchanged in its core message but supplemented the exposition with new model developments and with details we omitted in the first edition"--
1. The Basics of Credit Risk Management -- 1.1. Expected Loss -- 1.1.1. Probability of Default (PD) -- 1.1.2. The Exposure at Default -- 1.1.3. The Loss Given Default -- 1.1.4. A Remark on the Relation between PD, EAD, LGD -- 1.2. Unexpected Loss -- 1.2.1. Economic Capital -- 1.2.2. The Losws Distribution -- 1.2.3. Modeling Correlations by Means of Factor Modles -- 1.3. Regulatory Capital and the Basel Initiative -- 2. Modeling Correlated Defaults -- 2.1. The Bernoulli Model -- 2.1.1. A General Bernoulli Mixture Model -- 2.1.2. Uniform Default Probability and Uniform Correlation -- 2.2. The Poisson Model -- 2.2.1. A General Poisson Mixture Model -- 2.2.2. Uniform Default Intensity and Uniform Correlation -- 2.3. Bernoulli versus Poisson Mixture -- 2.4. An Overview of Common Model Concepts -- 2.4.1. Moody's KMV's and RiskMetrics' Model Approach -- 2.4.2. MOdel Approach of CreditRisk+ -- 2.4.3. Credit Portfolio View -- 2.4.4. Basic Remarks on Dynamic Intensity Models -- 2.5. One Factor/Sector Models -- 2.5.1. One-Factor Models in the Asset Value Model Setup -- 2.5.2. The CreditRisk+ One-Sector Model -- 2.5.3. Comparison of One-Factor and One-Sector Models -- 2.6. Loss Dependence by Means of Copula Functions -- 2.6.1. Copulas: Variations of a Scheme -- 2.7. Working Example on Asset Correlations -- 2.8. Generating the Portfolio Loss Distribution -- 2.8.1. Some Prerequisites from Probability Theory -- 2.8.2. Conditional Independence -- 2.8.3. Technique I: Recursive Generation -- 2.8.4. Technique II: Fourier Transformation -- 2.8.5. Technique III: Saddle-Point Approximation -- 2.8.6. Technique IV: Importance Sampling -- 3. Asset Value Models -- 3.1. Introduction and a Brief Guide to the Literature -- 3.2. A Few Words about Calls and puts -- 3.2.1. Geometric Brownian Motion -- 3.2.2. Put and Call Options -- 3.3. Merton's Asset Value Model -- 3.3.1. Capital Structure: Option- Theoretic Approach --3.3.2. Asset from Equity Values -- 3.4. Transforming Equity into Asset Values: A Working Approach -- 3.4.1. Ito's Formula "Light" -- 3.4.2. Black-Scholes Partial Differential Equation -- 4. The Credit Rik+ Model -- 4.1. The Modeling Framewiork of CreditRisk+ -- 4.2. Construction Step 1: Independent Obligors -- 4.3. Construction Step 2: Sector Model -- 4.3.1. Sector Default Distribution -- 4.3.2. Sector Compound Distribution -- 4.3.3. Sector Convolution -- 4.3.4. Calculating the Loss Distribution -- 5. Risk Measures and Capital Allocation -- 5.1. Coherent Risk Measures and Expected Shortfall -- 5.1.1. Expected Shortfall -- 5.1.2. Spectral Risk Measures -- 5.1.3. Density of a Risk Measure -- 5.2. Contributorty Capital -- 5.2.1. Axiomatic Approach to Capital Allocation -- 5.2.2. Capital Allocation in Practice -- 5.2.3. Variance/Covariance Approach -- 5.2.4. Capital Allocation w.r.t. Value-at-Risk -- 5.2.5. Capital Allocations w.r.t. Expected Shortfall -- 5.2.6. A Simulation Study -- 6. Term Structure of Default Probability -- 6.1. Survival Function and Hazard Rate -- 6.2. Risk-Neutral vs. Actual Default Probabilities -- 6.3. Term Structure Based on Historical Default Information -- 6.3.1. Exponential Term Structure -- 6.3.2. Direct Calibration of Multi-Year Default Probabilities -- 6.3.3. Migration Technique and Q-Matrices -- 6.3.4. A Non-Homogeneous Markov Chain Approach -- 6.4. Term Structure Based on Market Spreads -- 7. Credit Derivatives -- 7.1. Total Return Swaps -- 7.2. Credit Default Products -- 7.3. Basket Credit Derivatives -- 7.4. Credit Spread Products -- 7.5. Credit-Linked Notes -- 8. Collateralized Debt Obligations -- 8.1. Introduction to Collateralized Debt Obligations -- 8.1.1. Typical Cash Flow CDO Structure -- 8.1.2. Typical Synthetic CLO Structure -- 8.2. Different Roles of Banks in the CDO Market -- 8.2.1. The Originator's Point of View --8.2.2. The Investor's Point of View -- 8.3. CDOs from the Modeling Point of View -- 8.4. Multi-Period Credit Models -- 8.4.1. Migration Model -- 8.4.2. Correlated Default Time Models -- 8.4.3. First-Passage-Time Models -- 8.4.4. Stochastic Default Intensity Models -- 8.4.5. Intertemporal Dependence and Autocorrelation -- 8.5. Former Rating Agency Model: Moody's BET -- 8.6. Developments, Model Issues and Further Reading.
Christian Bluhm, Ludger Overbeck, Christoph Wagner.
Includes bibliographical references and index.
Chapman & Hall/CRC financial mathematics series