%0 Journal Article
%T Markov-Switching Time-Varying Copula Modeling of Dependence Structure between Oil and GCC Stock Markets
%A Heni Boubaker
%A Nadia Sghaier
%J Open Journal of Statistics
%P 565-589
%@ 2161-7198
%D 2016
%I Scientific Research Publishing
%R 10.4236/ojs.2016.64048
%X This paper proposes a Markov-switching
copula model to examine the presence of regime change in the time-varying
dependence structure between oil price changes and stock market returns in six
GCC countries. The marginal distributions are assumed to follow a long-memory
model while the copula parameters are supposed to evolve according to the
Markov-switching process. Furthermore, we estimate the Value-at-Risk (VaR)
based on the proposed approach. The empirical results provide evidence of three
regime changes, representing precrisis, financial crisis and post-crisis, in
the dependence structure between energy and GCC stock markets. In particular,
in the pre- and post-crisis regimes, there is no dependence, while in the
crisis regime, there is significant tail dependence. For OPEC countries, we
find lower tail dependence whereas in non-OPEC countries, we see upper tail
dependence. VaR experiments show that the Markov-switching time- varying copula
model performs better than the time-varying copula model.
%K Time-Varying Copulas
%K Markov-Switching Model
%K Oil Price Changes
%K GCC Stock Markets
%K VaR
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=69318