Catalogue


Rating based modeling of credit risk [electronic resource] : theory and application of migration matrices /
Stefan Trueck, Svetlozar T. Rachev.
imprint
London Burlington, MA : Academic, c2009.
description
xii, 266 p. : ill. ; 24 cm.
ISBN
0123736838, 9780123736833
format(s)
Book
More Details
imprint
London Burlington, MA : Academic, c2009.
isbn
0123736838
9780123736833
restrictions
Licensed for access by U. of T. users.
contents note
1. Introduction: Credit Risk Modeling, Ratings and Migration Matrices -- 2. Rating and Scoring Techniques -- 3. The New Basel Capital Accord -- 4. Rating Based Modeling -- 5. Migration Matrices and the Markov Chain Approach -- 6. Stability of Credit Migrations -- 7. Measures for Comparison of Transition Matrices -- 8. Real World and Risk-Neutral Transition Matrices -- 9. Conditional Credit Migrations: Adjustments and Forecasts -- 10. Dependence Modeling and Credit Migrations -- 11. Credit Derivatives.
abstract
In the last decade rating-based models have become very popular in credit risk management. These systems use the rating of a company as the decisive variable to evaluate the default risk of a bond or loan. The popularity is due to the straightforwardness of the approach, and to the upcoming new capital accord (Basel II), which allows banks to base their capital requirements on internal as well as external rating systems. Because of this, sophisticated credit risk models are being developed or demanded by banks to assess the risk of their credit portfolio better by recognizing the different underlying sources of risk. As a consequence, not only default probabilities for certain rating categories but also the probabilities of moving from one rating state to another are important issues in such models for risk management and pricing. It is widely accepted that rating migrations and default probabilities show significant variations through time due to macroeconomics conditions or the business cycle. These changes in migration behavior may have a substantial impact on the value-at-risk (VAR) of a credit portfolio or the prices of credit derivatives such as collateralized debt obligations (D+CDOs). In this book the authors develop a much more sophisticated analysis of migration behavior. Their contribution of more sophisticated techniques to measure and forecast changes in migration behavior as well as determining adequate estimators for transition matrices is a major contribution to rating based credit modeling. *Internal ratings-based systems are widely used in banks to calculate their value-at-risk (VAR) in order to determine their capital requirements for loan and bond portfolios under Basel II. One aspect of these ratings systems is credit migrations, addressed in a systematic and comprehensive way for the first time in this book. The book is based on in-depth work by Trueck and Rachev.
catalogue key
8045049
 
Includes bibliographical references (p. [249]-258) and index.
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Reviews
Review Quotes
"... an excellent overview of theory and application...." -Frank J. Fabozzi, PhD, CFA, Professor in the Practice of Finance, Yale School of Management, CT
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Summaries
Main Description
An up-to-date reference to the central problems of the field, this book focuses on the applications of transition matrices, including: rating based modeling, estimation techniques, Value-at-Risk simulation, adjustment and forecasting migration matrices, corporate-yield curve dynamics, dependent defaults and migrations, credit derivatives, collateralized debt obligations. The authors' contribution of more sophisticated techniques to measure and forecast changes in migration behavior as well as determining adequate estimators for transition matrices is a major contribution to rating based credit modeling. Book jacket.
Main Description
In the last decade rating-based models have become very popular in credit risk management. These systems use the rating of a company as the decisive variable to evaluate the default risk of a bond or loan. The popularity is due to the straightforwardness of the approach, and to the upcoming new capital accord (Basel II), which allows banks to base their capital requirements on internal as well as external rating systems. Because of this, sophisticated credit risk models are being developed or demanded by banks to assess the risk of their credit portfolio better by recognizing the different underlying sources of risk. As a consequence, not only default probabilities for certain rating categories but also the probabilities of moving from one rating state to another are important issues in such models for risk management and pricing. It is widely accepted that rating migrations and default probabilities show significant variations through time due to macroeconomics conditions or the business cycle. These changes in migration behavior may have a substantial impact on the value-at-risk (VAR) of a credit portfolio or the prices of credit derivatives such as collateralized debt obligations (D+CDOs). In this book the authors develop a much more sophisticated analysis of migration behavior. Their contribution of more sophisticated techniques to measure and forecast changes in migration behavior as well as determining adequate estimators for transition matrices is a major contribution to rating based credit modeling. *Internal ratings-based systems are widely used in banks to calculate their value-at-risk (VAR) in order to determine their capital requirements for loan and bond portfolios under Basel II *One aspect of these ratings systems is credit migrations, addressed in a systematic and comprehensive way for the first time in this book *The book is based on in-depth work by Trueck and Rachev,
Table of Contents
Prefacep. xi
Introduction: Credit Risk Modeling, Ratings, and Migration Matricesp. 1
Motivationp. 1
Structural and Reduced Form Modelsp. 2
Basel II, Scoring Techniques, and Internal Rating Systemsp. 3
Rating Based Modeling and the Pricing of Bondsp. 4
Stability of Transition Matrices, Conditional Migrations and Dependencep. 5
Credit Derivative Pricingp. 6
Chapter Outlinep. 7
Rating and Scoring Techniquesp. 11
Rating Agencies, Rating Processes, and Factorsp. 11
The Rating Processp. 14
Credit Rating Factorsp. 16
Types of Rating Systemsp. 17
Scoring Systemsp. 17
Discriminant Analysisp. 19
Logit and Probit Modelsp. 21
Logit Modelsp. 22
Probit Modelsp. 23
Model Evaluation: Methods and Difficultiesp. 25
Model Performance and Benchmarkingp. 25
Model Accuracy, Type I and II Errorsp. 29
The New Basel Capital Accordp. 31
Overviewp. 31
The First Pillar-Minimum Capital Requirementp. 33
The Second Pillar-Supervisory Review Processp. 35
The Third Pillar-Market Disciplinep. 35
The Standardized Approachp. 36
Risk Weights for Sovereigns and for Banksp. 36
Risk Weights for Corporatesp. 39
Maturityp. 39
Credit Risk Mitigationp. 40
The Internal Ratings Based Approachp. 41
Key Elements and Risk Componentsp. 41
Derivation of the Benchmark Risk Weight Functionp. 42
Asset Correlationp. 46
The Maturity Adjustmentp. 48
Expected, Unexpected Losses and the Required Capitalp. 50
Summaryp. 50
Rating Based Modelingp. 53
Introductionp. 53
Reduced Form and Intensity Modelsp. 54
The Model by Jarrow and Turnbull (1995)p. 59
The Model Suggested by Madan and Unal (1998)p. 60
The Model Suggested by Lando (1998)p. 61
The Model of Duffie and Singleton (1999)p. 63
The CreditMetrics Modelp. 63
The CreditRisk[superscript +] Modelp. 68
The First Modeling Approachp. 68
Modeling Severitiesp. 69
Shortcomings of the First Modeling Approachp. 71
Extensions in the CR[superscript +] Modelp. 72
Allocating Obligors to One of Several Factorsp. 72
The pgf for the Number of Defaultsp. 73
The pgf for the Default Loss Distributionp. 75
Generalization of Obligor Allocationp. 75
The Default Loss Distributionp. 76
Migration Matrices and the Markov Chain Approachp. 77
The Markov Chain Approachp. 77
Generator Matricesp. 78
Discrete Versus Continuous-Time Modelingp. 80
Some Conditions for the Existence of a Valid Generatorp. 86
Approximation of Generator Matricesp. 88
The Method Proposed by Jarrow, Lando, and Turnbull (1997)p. 88
Methods Suggested by Israel, Rosenthal, and Wei (2000)p. 89
Simulating Credit Migrationsp. 92
Time-Discrete Casep. 92
Time-Continuous Casep. 93
Nonparametric Approachp. 94
Stability of Credit Migrationsp. 97
Credit Migrations and the Business Cyclep. 97
The Markov Assumptions and Rating Driftsp. 102
Likelihood Ratio Testsp. 103
Rating Driftp. 104
An Empirical Studyp. 105
Time Homogeneity of Migration Matricesp. 109
Tests Using the Chi-Square Distancep. 110
Eigenvalues and Eigenvectorsp. 110
Migration Behavior and Effects on Credit VaRp. 113
Stability of Probability of Default Estimatesp. 120
Measures for Comparison of Transition Matricesp. 129
Classical Matrix Normsp. 129
Indices Based on Eigenvalues and Eigenvectorsp. 131
Risk-Adjusted Difference Indicesp. 133
The Direction of the Transition (DIR)p. 133
Transition to a Default or Nondefault State (TD)p. 134
The Probability Mass of the Cell (PM)p. 135
Migration Distance (MD)p. 136
Devising a Distance Measurep. 136
Difference Indices for the Exemplary Matricesp. 140
Summaryp. 142
Real-World and Risk-Neutral Transition Matricesp. 145
The JLT Modelp. 145
Adjustments Based on the Discrete-Time Transition Matrixp. 148
Adjustments Based on the Generator Matrixp. 151
Modifying Default Intensitiesp. 152
Modifying the Rows of the Generator Matrixp. 153
Modifying Eigenvalues of the Transition Probability Matrixp. 154
An Adjustment Technique Based on Economic Theoryp. 156
Risk-Neutral Migration Matrices and Pricingp. 157
Conditional Credit Migrations: Adjustments and Forecastsp. 159
Overviewp. 159
The CreditPortfolioView Approachp. 160
Adjustment Based on Factor Model Representationsp. 165
Deriving an Index for the Credit Cyclep. 166
Conditioning of the Migration Matrixp. 167
A Multifactor Model Extensionp. 171
Other Methodsp. 173
An Empirical Study on Different Forecasting Methodsp. 175
Forecasts Using the Factor Model Approachp. 176
Forecasts Using Numerical Adjustment Methodsp. 178
Regression Modelsp. 179
In-Sample Resultsp. 180
Out-of-Sample Forecastsp. 184
Dependence Modeling and Credit Migrationsp. 187
Introductionp. 187
Independencep. 188
Dependencep. 189
Capturing the Structure of Dependencep. 191
Under General Multivariate Distributionsp. 195
Copulasp. 196
Examples of Copulasp. 198
Properties of Copulasp. 199
Constructing Multivariate Distributions with Copulasp. 200
Modeling Dependent Defaultsp. 201
Modeling Dependent Migrationsp. 204
Dependence Based on a Credit Cycle Indexp. 205
Dependence Based on Individual Transitionsp. 206
Approaches Using Copulasp. 207
An Empirical Study on Dependent Migrationsp. 209
Distribution of Defaultsp. 209
The Distribution of Rating Changesp. 212
Credit Derivativesp. 217
Introductionp. 217
Types of Credit Derivativesp. 219
Collateralized Debt Obligations (CDO)p. 222
Pricing Single-Named Credit Derivativesp. 224
Modeling and Pricing of Collateralized Debt Obligations and Basket Credit Derivativesp. 231
Estimation of Macroeconomic Risk Factorsp. 235
Modeling of Conditional Migrations and Recovery Ratesp. 237
Some Empirical Resultsp. 238
Pricing Step-Up Bondsp. 243
Step-Up Bondsp. 244
Pricing of Step-Up Bondsp. 244
Bibliographyp. 249
Indexp. 259
Table of Contents provided by Ingram. All Rights Reserved.

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