Correlation Risk Modelling and Management (2nd Edition)
First published:
ISBN: 978-1-78272-405-6
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Financial Correlation Models – Top-Down Approaches
Introduction
Correlation Basics: Definitions, Applications and Terminology
Empirical Properties of Correlation: How do Correlations Behave in the Real World?
The Pearson Correlation Model – Work of the Devil?
Cointegration – A Superior Concept to Correlation?
Financial Correlation Modelling – Bottom-up Approaches
Valuing CDOs with the Gaussian Copula – What Went Wrong?
The One-Factor Gaussian Copula Model – Too Simplistic?
Financial Correlation Models – Top-Down Approaches
Stochastic Correlation Models
Quantifying Market Correlation Risk
Quantifying Credit Correlation Risk
Hedging Correlation Risk
Correlation Trading Strategies – Opportunities and Limitations
Credit Value at Risk under Basel III – Too Simplistic?
Basel III and XVAs
Fundamental Review of the Trading Book
The Future of Correlation Modelling
Answers to Questions and Problems in Correlation Risk Modelling and Management
Imagination is more important than knowledge
– Albert Einstein
Financial credit models, which derive correlated default risk, can be characterised by the way the portfolio default intensity distribution is derived. In the bottom-up models of Chapters 3 to 7, the distribution of the portfolio intensity is an aggregate of the individual entities’ default intensity. In a top-down model the evolution of the portfolio intensity distribution is derived directly, ie, abstracted from the individual entities’ default intensities.
Top-down models are typically applied in practice if (1) the default intensities of the individual entities are unavailable or unreliable; (2) the default intensities of the individual entities are unnecessary (this may be the case when evaluating a homogeneous portfolio such as an index of homogeneous entities); or (3) the sheer size of a portfolio makes the modelling of individual default intensities problematic.
Top-down models are typically more parsimonious, computationally efficient and can often be calibrated better to market prices than bottom-up models. Although seemingly important information – such as the individual entities’ default
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