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has been cited by the following article:

• 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.