A comprehensive resource providing extensive coverage of the state of the art in credit secruritisations, derivatives, and risk management Credit Securitisations and Derivatives is a one-stop resource presenting the very latest thinking and developments in the field of credit risk. Written by leading thinkers from academia, the industry, and the regulatory environment, the book tackles areas such as business cycles; correlation modelling and interactions between financial markets, institutions, and instruments in relation to securitisations and credit derivatives; credit portfolio risk; credit portfolio risk tranching; credit ratings for securitisations; counterparty credit risk and clearing of derivatives contracts and liquidity risk. As well as a thorough analysis of the existing models used in the industry, the book will also draw on real life cases to illustrate model performance under different parameters and the impact that using the wrong risk measures can have.

Daniel Röschis Professor of Finance and Head of the
Institute of Banking and Finance at Leibniz Universität
Hannover. He received a PhD from the University of Regensburg. His
work covers a broad range in Banking, Asset Pricing and Empirical
Finance. He has published numerous articles on Risk Management,
Credit Risk, Banking, Quantitative Finance and Financial
Econometrics in leading international journals. He has been
conducting research projects with supervising authorities and is
consulting financial institutions on risk management issues.

Harald Scheule is Associate Professor of Finance at the
University of Technology, Sydney. His expertise is in the area of
banking, Financial Risk Measurement and Management, Insurance,
Prudential Regulation, Securities Evaluation and Structured
Finance. He is a regional director of the Global Association of
Risk Professionals. His research work has been accepted for
publication in a wide range of journals including the European
Financial Management, International Review of Finance, Journal of
Banking and Finance, Journal of Financial Research, Journal of the
Operational Research Society and The European Journal of
Finance. He has worked with prudential regulators of financial
institutions and undertaken consulting work for a wide range of
financial institutions and service providers in Australia, Europe
and North America.

PART I INTRODUCTION

1 Credit Securitizations and Derivatives 3

1.1 Economic Cycles and Credit Portfolio Risk 3

1.2 Credit Portfolio Risk Measurement 6

1.3 Credit Portfolio Risk Tranching 7

1.4 Credit Ratings 7

1.5 Actuarial vs. Market Credit Risk Pricing 7

1.6 Regulation 8

1.7 Thank You 9

References 9

2 Developments in Structured Finance Markets 11

2.1 Impairments of Asset-Backed Securities and Outstanding Ratings 11

2.2 Issuance of Asset-backed Securities and Outstanding Volume 17

2.3 Global CDO Issuance and Outstanding Volume 19

Concluding Remarks 29

Notes 29

References 31

PART II CREDIT PORTFOLIO RISK MEASUREMENT

3 Mortgage Credit Risk 35

3.1 Introduction 35

3.2 Five Cs of Credit and Mortgage Credit Risk 38

3.3 Determinants of Mortgage Default, Loss Given Default and Exposure at Default 41

3.3.1 Determinants of Mortgage Default 41

3.3.2 Determinants of Mortgage LGD 43

3.3.3 Determinants of Mortgage EAD 48

3.4 Modeling Methods for Default, LGD and EAD 48

3.5 Model Risk Management 48

3.6 Conclusions 51

References 51

4 Credit Portfolio Correlations and Uncertainty 53

4.1 Introduction 53

4.2 Gaussian and Semi-Gaussian Single Risk Factor Model 54

4.3 Individual and Simultaneous Confidence Bounds and Intervals 55

4.4 Confidence Intervals for Asset Correlations 57

4.5 Confidence Intervals for Default and Survival Time Correlations 59

4.5.1 Confidence Intervals for Default Correlations 60

4.5.2 Confidence Intervals for Survival Time Correlations 61

4.6 Example 63

4.7 Conclusion 65

Appendix 66

Notes 69

References 69

5 Credit Portfolio Correlations with Dynamic Leverage Ratios 71

5.1 Introduction 71

5.2 The Hui et al. (2007) Model 72

5.2.1 The Method of Images for Constant Coefficients 73

5.2.2 The Method of Images for Time-Varying Coefficients 74

5.3 Modelling Default Correlations in a Two-Firm Model 75

5.3.1 Default Correlations 75

5.3.2 A Two-Firm Model with Dynamic Leverage Ratios 75

5.3.3 Method of Images for Constant Coefficients at Certain Values of 12 78

5.3.4 Method of Images for Time-Varying Coefficients at Certain Values of 12 79

5.3.5 Alternative Methodologies for General Values of 12 81

5.4 Numerical Results 81

5.4.1 Accuracy 83

5.4.2 The Impact of Correlation between Two Firms 84

5.4.3 The Impact of Dfferent Credit Quality Paired Firms 86

5.4.4 The Impact of Volatilities 87

5.4.5 The Impact of Drift Levels 88

5.4.6 The Impact of Initial Value of Leverage Ratio Levels 89

5.4.7 Impact of Correlation between Firms and Interest Rates 89

5.4.8 The Price of Credit-Linked Notes 91

5.5 Conclusion 92

Notes 93

References 94

6 A Hierarchical Model of Tail-Dependent Asset Returns 95

6.1 Introduction 95

6.2 The Variance Compound Gamma Model 97

6.2.1 Multivariate Process for Logarithmic Asset Returns 97

6.2.2 Dependence Structure 101

6.2.3 Sampling 105

6.2.4 Copula Properties 105

6.3 An Application Example 110

6.3.1 Portfolio Setup 110

6.3.2 Test Portfolios 113

6.3.3 Parameter Setup 113

6.3.4 Simulation Results 114

6.4 Importance Sampling Algorithm 116

6.5 Conclusions 120

Appendix A: The VCG Probability Distribution Function 121

Appendix B: HAC Representation for the VCG Framework 123

Notes 124

References 124

7 Monte Carlo Methods for Portfolio Credit Risk 127