TITLE:
Markov-Switching Time-Varying Copula Modeling of Dependence Structure between Oil and GCC Stock Markets
AUTHORS:
Heni Boubaker, Nadia Sghaier
KEYWORDS:
Time-Varying Copulas, Markov-Switching Model, Oil Price Changes, GCC Stock Markets, VaR
JOURNAL NAME:
Open Journal of Statistics,
Vol.6 No.4,
July
29,
2016
ABSTRACT: 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.