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The Resource Concentration risk in credit portfolios, Eva Lütkebohmert, (electronic book)

Concentration risk in credit portfolios, Eva Lütkebohmert, (electronic book)

Label
Concentration risk in credit portfolios
Title
Concentration risk in credit portfolios
Statement of responsibility
Eva Lütkebohmert
Creator
Subject
Language
eng
Member of
Cataloging source
OSU
http://library.link/vocab/creatorName
Lütkebohmert, Eva
Dewey number
332.7011
Illustrations
illustrations
Index
index present
LC call number
HG3751
LC item number
.L88 2009
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
Series statement
EAA lecture notes,
http://library.link/vocab/subjectName
  • Credit
  • Credit
  • Credit scoring systems
  • Portfolio management
  • Risk management
Label
Concentration risk in credit portfolios, Eva Lütkebohmert, (electronic book)
Instantiates
Publication
Bibliography note
Includes bibliographical references (p. [217]-222) and index
Color
mixed
Contents
Introduction to Credit Risk Modeling 1 Risk Measurement 3 1.1 Variables of Risk 4 1.2 The General Model Setting 5 1.3 Exchangeable Models 7 2 Modeling Credit Risk 9 2.1 The Regulatory Framework 10 2.2 Expected and Unexpected Loss 12 2.3 Value-at-Risk 13 2.4 Expected Shortfall 15 2.5 Economic Capital 17 3 The Merton Model 19 3.1 The General Framework 20 3.2 The Multi-Factor Merton Model 23 3.3 Industry Models Based on the Merton Approach 29 3.3.1 The KMV Model 29 3.3.2 The CreditMetrics Model 30 4 The Asymptotic Single Risk Factor Model 31 4.1 The ASRF Model 32 4.2 The IRB Risk Weight Functions 35 4.3 The Loss Distribution of an Infinitely Granular Portfolio 38 5 Mixture Models 43 5.1 Bernoulli and Poisson Mixture Models 43 5.2 The Influence of the Mixing Distribution on the Loss Distribution 48 5.3 Relation Between Latent Variable Models and Mixture Models 50 6 The CreditRisk[superscript +] Model 53 6.1 Basic Model Setting 54 6.2 The Poisson Approximation 56 6.3 Model with Random Default Probabilities 57 Part II Concentration Risk in Credit Portfolios 7 Introduction 63 8 Ad-Hoc Measures of Concentration 67 8.1 Concentration Indices 68 8.2 Conclusion 72 9 Name Concentration 75 9.1 A Granularity Adjustment for the ASRF Model 76 9.1.1 Example as Motivation for GA Methodology 77 9.1.2 The General Framework 78 9.1.3 The Granularity Adjustment in a Single Factor CreditRisk[superscript +] Setting 81 9.1.4 Data on German Bank Portfolios 84 9.1.5 Numerical Results 86 9.1.6 Summary 88 9.2 The Semi-Asymptotic Approach 90 9.2.1 The General Framework 90 9.2.2 Numerical Results 93 9.3 Methods Based on the Saddle-Point Approximation 93 9.3.1 The General Framework 94 9.3.2 Application to Name Concentration Risk 96 9.4 Discussion and Comparison Study of the Granularity Adjustment Methods 99 9.4.1 Empirical Relevance of the Granularity Adjustment 100 9.4.2 Why a Granularity Adjustment Instead of the HHI? 100 9.4.3 Accuracy of the Granularity Adjustment and Robustness to Regulatory Parameters 102 9.4.4 Comparison of Granularity Adjustment with Other Model-Based Approaches 103 9.4.5 Agreement of Granularity Adjustment and Saddle-Point Approximation Method in the CreditRisk[superscript +] Model 104 10 Sector Concentration 107 10.1 Analytical Approximation Models 108 10.1.1 Analytical Approximation for Value-at-Risk 109 10.1.2 Analytical Approximation for Expected Shortfall 117 10.1.3 Performance Testing 118 10.1.4 Summary and Discussion 119 10.2 Diversification Factor Models 120 10.2.1 The Multi-Sector Framework 121 10.2.2 The Capital Diversification Factor 123 10.2.3 Marginal Capital Contributions 124 10.2.4 Parameterization 126 10.2.5 Application to a Bank Internal Multi-Factor Model 127 10.2.6 Discussion 129 11 Empirical Studies on Concentration Risk 131 11.1 Sector Concentration and Economic Capital 132 11.1.1 The Model Framework 133 11.1.2 Data Description and Portfolio Composition 133 11.1.3 Impact of Sector Concentration on Economic Capital 135 11.1.4 Robustness of EC Approximations 136 11.1.5 Discussion 139 11.2 The Influence of Systematic and Idiosyncratic Risk on Large Portfolio Losses 140 11.2.1 Descriptive Analysis of SNC Data 140 11.2.2 Simple Indices of Name and Sector Concentration 141 11.2.3 Modeling Dependencies in Losses 142 11.2.4 Monte Carlo Simulation of the Portfolio Loss Distribution 143 11.2.5 Empirical Results 145 11.2.6 Summary and Discussion 147 Part III Default Contagion 12 Introduction 151 13 Empirical Studies on Default Contagion 155 13.1 The Doubly Stochastic Property and its Testable Implications 156 13.2 Data for Default Intensity Estimates 159 13.3 Goodness-of-Fit Tests 159 13.4 Discussion 162 14 Models Based on Copulas 165 14.1 Equivalence of Latent Variable Models 166 14.2 Sensitivity of Losses on the Dependence Structure 168 14.3 Discussion 170 15 A Voter Model for Credit Contagion 173 15.1 The Model Framework 174 15.2 Invariant and Ergodic Measures for the Voter Model 177 15.3 The Non-Dense Business Partner Network 179 15.4 The Dense Business Partner Network 180 15.5 Aggregate Losses on Large Portfolios 182 15.6 Discussion and Comparison with Alternative Approaches 186 15.6.1 The Mean-Field Model with Interacting Default Intensities 187 15.6.2 A Dynamic Contagion Model 189 15.7 Contagion Through Macro- and Microstructural Channels 190 15.7.1 A Model with Macro- and Micro-Structural Dependence 191 15.7.2 The Rating Migrations Process 193 15.7.3 Results and Discussion 194 16 Equilibrium Models 197 16.1 A Mean-Field Model of Credit Ratings 198 16.2 The Mean-Field Model with Local Interactions 202 16.3 Large Portfolio Losses 205 16.4 Discussion
Control code
SPR298322247
Dimensions
unknown
Extent
1 online resource (xvii, 225 p.)
Form of item
online
Isbn
9783540708704
Isbn Type
(e-isbn)
Other physical details
ill.
Publisher number
12240043
Specific material designation
remote
Label
Concentration risk in credit portfolios, Eva Lütkebohmert, (electronic book)
Publication
Bibliography note
Includes bibliographical references (p. [217]-222) and index
Color
mixed
Contents
Introduction to Credit Risk Modeling 1 Risk Measurement 3 1.1 Variables of Risk 4 1.2 The General Model Setting 5 1.3 Exchangeable Models 7 2 Modeling Credit Risk 9 2.1 The Regulatory Framework 10 2.2 Expected and Unexpected Loss 12 2.3 Value-at-Risk 13 2.4 Expected Shortfall 15 2.5 Economic Capital 17 3 The Merton Model 19 3.1 The General Framework 20 3.2 The Multi-Factor Merton Model 23 3.3 Industry Models Based on the Merton Approach 29 3.3.1 The KMV Model 29 3.3.2 The CreditMetrics Model 30 4 The Asymptotic Single Risk Factor Model 31 4.1 The ASRF Model 32 4.2 The IRB Risk Weight Functions 35 4.3 The Loss Distribution of an Infinitely Granular Portfolio 38 5 Mixture Models 43 5.1 Bernoulli and Poisson Mixture Models 43 5.2 The Influence of the Mixing Distribution on the Loss Distribution 48 5.3 Relation Between Latent Variable Models and Mixture Models 50 6 The CreditRisk[superscript +] Model 53 6.1 Basic Model Setting 54 6.2 The Poisson Approximation 56 6.3 Model with Random Default Probabilities 57 Part II Concentration Risk in Credit Portfolios 7 Introduction 63 8 Ad-Hoc Measures of Concentration 67 8.1 Concentration Indices 68 8.2 Conclusion 72 9 Name Concentration 75 9.1 A Granularity Adjustment for the ASRF Model 76 9.1.1 Example as Motivation for GA Methodology 77 9.1.2 The General Framework 78 9.1.3 The Granularity Adjustment in a Single Factor CreditRisk[superscript +] Setting 81 9.1.4 Data on German Bank Portfolios 84 9.1.5 Numerical Results 86 9.1.6 Summary 88 9.2 The Semi-Asymptotic Approach 90 9.2.1 The General Framework 90 9.2.2 Numerical Results 93 9.3 Methods Based on the Saddle-Point Approximation 93 9.3.1 The General Framework 94 9.3.2 Application to Name Concentration Risk 96 9.4 Discussion and Comparison Study of the Granularity Adjustment Methods 99 9.4.1 Empirical Relevance of the Granularity Adjustment 100 9.4.2 Why a Granularity Adjustment Instead of the HHI? 100 9.4.3 Accuracy of the Granularity Adjustment and Robustness to Regulatory Parameters 102 9.4.4 Comparison of Granularity Adjustment with Other Model-Based Approaches 103 9.4.5 Agreement of Granularity Adjustment and Saddle-Point Approximation Method in the CreditRisk[superscript +] Model 104 10 Sector Concentration 107 10.1 Analytical Approximation Models 108 10.1.1 Analytical Approximation for Value-at-Risk 109 10.1.2 Analytical Approximation for Expected Shortfall 117 10.1.3 Performance Testing 118 10.1.4 Summary and Discussion 119 10.2 Diversification Factor Models 120 10.2.1 The Multi-Sector Framework 121 10.2.2 The Capital Diversification Factor 123 10.2.3 Marginal Capital Contributions 124 10.2.4 Parameterization 126 10.2.5 Application to a Bank Internal Multi-Factor Model 127 10.2.6 Discussion 129 11 Empirical Studies on Concentration Risk 131 11.1 Sector Concentration and Economic Capital 132 11.1.1 The Model Framework 133 11.1.2 Data Description and Portfolio Composition 133 11.1.3 Impact of Sector Concentration on Economic Capital 135 11.1.4 Robustness of EC Approximations 136 11.1.5 Discussion 139 11.2 The Influence of Systematic and Idiosyncratic Risk on Large Portfolio Losses 140 11.2.1 Descriptive Analysis of SNC Data 140 11.2.2 Simple Indices of Name and Sector Concentration 141 11.2.3 Modeling Dependencies in Losses 142 11.2.4 Monte Carlo Simulation of the Portfolio Loss Distribution 143 11.2.5 Empirical Results 145 11.2.6 Summary and Discussion 147 Part III Default Contagion 12 Introduction 151 13 Empirical Studies on Default Contagion 155 13.1 The Doubly Stochastic Property and its Testable Implications 156 13.2 Data for Default Intensity Estimates 159 13.3 Goodness-of-Fit Tests 159 13.4 Discussion 162 14 Models Based on Copulas 165 14.1 Equivalence of Latent Variable Models 166 14.2 Sensitivity of Losses on the Dependence Structure 168 14.3 Discussion 170 15 A Voter Model for Credit Contagion 173 15.1 The Model Framework 174 15.2 Invariant and Ergodic Measures for the Voter Model 177 15.3 The Non-Dense Business Partner Network 179 15.4 The Dense Business Partner Network 180 15.5 Aggregate Losses on Large Portfolios 182 15.6 Discussion and Comparison with Alternative Approaches 186 15.6.1 The Mean-Field Model with Interacting Default Intensities 187 15.6.2 A Dynamic Contagion Model 189 15.7 Contagion Through Macro- and Microstructural Channels 190 15.7.1 A Model with Macro- and Micro-Structural Dependence 191 15.7.2 The Rating Migrations Process 193 15.7.3 Results and Discussion 194 16 Equilibrium Models 197 16.1 A Mean-Field Model of Credit Ratings 198 16.2 The Mean-Field Model with Local Interactions 202 16.3 Large Portfolio Losses 205 16.4 Discussion
Control code
SPR298322247
Dimensions
unknown
Extent
1 online resource (xvii, 225 p.)
Form of item
online
Isbn
9783540708704
Isbn Type
(e-isbn)
Other physical details
ill.
Publisher number
12240043
Specific material designation
remote

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