Copulae and Multivariate Probability Distributions in Finance
- 208 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Copulae and Multivariate Probability Distributions in Finance
About this book
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.
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Information
Table of contents
- Cover
- Half Title
- Title Page
- Copyright Page
- Table of Contents
- Citation Information
- About the Editors
- Preface
- 1. The Advent of Copulas in Finance
- 2. Testing for structural changes in exchange rates’ dependence beyond linear correlation
- 3. Models for construction of multivariate dependence – a comparison study
- 4. Dependency without copulas or ellipticity
- 5. Copula goodness-of-fit testing: an overview and power comparison
- 6. Asymmetric dependence patterns in financial time series
- 7. Dynamic copula quantile regressions and tail area dynamic dependence in Forex markets
- 8. Risk and return of reinsurance contracts under copula models
- 9. Pricing bivariate option under GARCH-GH model with dynamic copula: application for Chinese market
- Index