Credit Models and the Crisis is a succinct but technical analysis of the key aspects of the credit derivatives modeling problems, tracing the development (and flaws) of new quantitative methods for credit derivatives and CDOs up to and through the credit crisis. Responding to the immediate need for clarity in the market and academic research environments, this book follows the development of credit derivatives and CDOs at a technical level, analyzing the impact, strengths and weaknesses of methods ranging from the introduction of the Gaussian Copula model and the related implied correlations to the introduction of arbitrage–free dynamic loss models capable of calibrating all the tranches for all the maturities at the same time. It also illustrates the implied copula, a method that can consistently account for CDOs with different attachment and detachment points but not for different maturities, and explains why the Gaussian Copula model is still used in its base correlation formulation.
The book reports both alarming pre–crisis research and market examples, as well as commentary through history, using data up to the end of 2009, making it an important addition to modern derivatives literature. With banks and regulators struggling to fully analyze at a technical level, many of the flaws in modern financial models, it will be indispensable for quantitative practitioners and academics who want to develop stable and functional models in the future.
About the Authors.
Notation and List of Symbols.
1 Introduction: Credit Modelling Pre– and In–Crisis.
1.1 Bottom–up models.
1.2 Compound correlation.
1.3 Base correlation.
1.4 Implied Copula.
1.5 Expected Tranche Loss Surface.
1.6 Top (down) framework.
1.7 GPL and GPCL models.
1.8 Structure of the book.
2 Market Quotes.
2.1 Credit indices.
2.2 CDO tranches.
3 Gaussian Copula Model and Implied Correlation.
3.1 One–factor Gaussian Copula model.
3.1.1 Finite pool homogeneous one–factor Gaussian Copula model.
3.1.2 Finite pool heterogeneous one–factor Gaussian Copula model.
3.1.3 Large pool homogeneous one–factor Gaussian Copula model.
3.2 Double–t Copula Model.
3.3 Compound correlation and base correlation.
3.4 Existence and non–monotonicity of market spread as a function of compound correlation.
3.5 Invertibility limitations of compound correlation: pre–crisis.
3.6 Base correlation.
3.7 Is base correlation a solution to the problems of compound correlation?
3.8 Can the Double–t Copula flatten the Gaussian base correlation skew?
3.9 Summary on implied correlation.
4 Consistency across Capital Structure: Implied Copula.
4.1 Calibration of Implied Copula.
4.2 Two–stage regularization.
4.3 Summary of considerations around Implied Copula.
5 Consistency across Capital Structure and Maturities: Expected Tranche Loss.
5.1 Index and tranche NPV as a function of ETL.
5.2 Numerical results.
5.3 Summary on Expected (Equity) Tranche Loss.
6 A Fully Consistent Dynamical Model: Generalized–Poisson Loss Model.
6.1 Loss dynamics.
6.2 Model limits.
6.3 Model calibration.
6.4 Detailed calibration procedure.
6.5 Calibration results.
7 Application to More Recent Data and the Crisis.
7.1 Compound correlation in–crisis.
7.2 Base correlation in–crisis.
7.3 Implied Copula in–crisis.
7.4 Expected Tranche Loss surface in–crisis.
7.4.1 Deterministic piecewise constant recovery rates.
7.5 Generalized–Poisson Loss model in–crisis.
8 Final Discussion and Conclusions.
8.1 There are more things in heaven and earth, Horatio. . . .
8.2 . . . Than are dreamt of in your philosophy.