Copulae and Multivariate Probability Distributions in Finance
Portfolio theory and much of asset pricing, as well as many empirical applications, depend on the use of multivariate probability distributions to describe asset returns. Traditionally, this has meant the multivariate normal (or Gaussian) distribution. More recently, theoretical and empirical work in financial economics has employed the multivariate Student (and other) distributions which are members of the elliptically symmetric class. There is also a growing body of work which is based on skew-elliptical distributions. These probability models all exhibit the property that the marginal distributions differ only by location and scale parameters or are restrictive in other respects. Very often, such models are not supported by the empirical evidence that the marginal distributions of asset returns can differ markedly. Copula theory is a branch of statistics which provides powerful methods to overcome these shortcomings. This book provides a synthesis of the latest research in the area of copulae as applied to finance and related subjects such as insurance. Multivariate non-Gaussian dependence is a fact of life for many problems in financial econometrics. This book describes the state of the art in tools required to deal with these observed features of financial data.
This book was originally published as a special issue of the European Journal of Finance.
Preface Chris Adcock, Alexandra Dias and Mark Salmon
1. The Advent of Copulas in Finance Christian Genest, Michel Gendron and Michaël Bourdeau-Brien
2. Testing for structural changes in exchange rates’ dependence beyond linear correlation Alexandra Dias and Paul Embrechts
3. Models for construction of multivariate dependence – a comparison study Kjersti Aas and Daniel Berg
4. Dependency without copulas or ellipticity William T. Shaw and Asad Munir
5. Copula goodness-of-fit testing: an overview and power comparison Daniel Berg
6. Asymmetric dependence patterns in financial time series Manuel Ammann and Stephan Süss
7. Dynamic copula quantile regressions and tail area dynamic dependence in Forex markets Eric Bouyé and Mark Salmon
8. Risk and return of reinsurance contracts under copula models Martin Eling and Denis Toplek
9. Pricing bivariate option under GARCH-GH model with dynamic copula: application for Chinese market Dominique Guégan and Jing Zang