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Operational Research, 6, Markov-Switching Time-Varying Copula Modeling of Dependence Structure between Oil and GCC Stock Markets. Heni Boubaker , Nadia Sghaier KEYWORDS: Time-Varying Copulas , Markov-Switching Model , Oil Price Changes , GCC Stock Markets , VaR. Open Journal of Statistics , Vol.

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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.

Wild oil prices, but brave stock markets! The case of GCC stock markets | SpringerLink

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.

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