Higher-dimensional copula models and their application: Bayesian inference for D-vine pair-copula constructions based on different bivariate families

Jiabao Ma

ISBN 10: 3639307062 / ISBN 13: 9783639307061

Published by VDM Verlag Dr. M�ller 2010-11-03, 2010

About this Item

Seller Inventory # 6666-IUK-9783639307061

Bibliographic Details

• Title: Higher-dimensional copula models and their application: Bayesian inference for D-vine pair-copula constructions based on different bivariate families
• Publisher: VDM Verlag Dr. M�ller 2010-11-03
• Publication Date: 2010
• Language: English
• ISBN 10: 3639307062
• ISBN 13: 9783639307061
• Binding: Paperback
• Condition: New

About this title

Synopsis

Modelling multivariate dependence structures has proven to be an important aspect in the field of finance. The reality of financial markets shows clear evidence that asset returns exhibit non-normal dependence. Since copula functions have been applied to the solution of these non-normal distributed problems, they find wide-ranging application in the fields of risk management, derivative pricing, hedging and optimal portfolio decisions. Pair-copula construction allows modelling of the dependence structure between different higher-dimensional time series. The author shows a flexible way to estimate and calibrate such higher-dimensional copula models and provides the application of U.S. industrial returns. In his simulation study he shows the sensitivity with respect to the copula parameter and different families using newly developed R-packages.

About the Author

Jiabao Ma, Dipl.-Math. Oec. Univ.: Studied Mathematical Finance and Economics at Technische Universität München (TUM) in Germany. Investmentcontroller at NORD/LB Asset Management, Hannover, Germany.