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The links between crude oil prices and GCC stock markets: Evidence from time-varying Granger causality tests

Author

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  • Mehmet Balcilar

    (Department of Economics, Eastern Mediterranean University)

  • Rangan Gupta

    (Department of Economics, University of Pretoria)

  • Ýsmail H. Gençb

    (Department of Economics School of Business Management American University of Sharjah)

Abstract

This paper investigates the impact of crude oil price movements on the stock markets of Gulf Corporation Council (GCC) countries using weekly data for the period of February 2, 1994-February 26, 2010. The causal link between oil and stock markets are modeled using a Markov switching vector autoregressive (MS-VAR) model in order to reflect changes in Granger causality over time. The MS-VAR model allows testing for both conditional Granger causality and regime predicting causality. The parameter instability tests indicate that causal links between crude oil prices and stock market indexes are highly time-varying. The full sample conditional Granger causality tests based on the MS-VAR model, which identifies four regimes each corresponding to causal relationships, rejects both the causal impact of lagged stock market prices on oil prices and the causal impact from crude oil spot prices to stock market indexes in the full sample. However, regime prediction causality from oil prices to GCC stock markets is not rejected for all countries we consider, indicating that oil prices have predictive content for the regime of GCC stock markets. These results encompass the previous findings and offer new insights into the nature of causal relationships between oil price and stock markets in GCC countries.

Suggested Citation

  • Mehmet Balcilar & Rangan Gupta & Ýsmail H. Gençb, 2016. "The links between crude oil prices and GCC stock markets: Evidence from time-varying Granger causality tests," Working Papers 15-30, Eastern Mediterranean University, Department of Economics.
  • Handle: RePEc:emu:wpaper:15-30.pdf
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    Cited by:

    1. Vassilios Babalos & Mehmet Balcilar & Rangan Gupta, 2014. "Revisiting Herding Behavior in REITs: A Regime-Switching Approach," Working Papers 201448, University of Pretoria, Department of Economics.
    2. Balcılar, Mehmet & Demirer, Rıza & Hammoudeh, Shawkat, 2015. "Regional and global spillovers and diversification opportunities in the GCC equity sectors," Emerging Markets Review, Elsevier, vol. 24(C), pages 160-187.
    3. Balcilar, Mehmet & Demirer, Rıza & Hammoudeh, Shawkat, 2013. "Investor herds and regime-switching: Evidence from Gulf Arab stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 23(C), pages 295-321.
    4. Elie I Bouri, 2013. "Correlation and Volatility of the MENA Equity Markets in Turbulent Periods, and Portfolio Implications," Economics Bulletin, AccessEcon, vol. 33(2), pages 1575-1593.
    5. Mehmet Balcilar & Riza Demirer & Shawkat Hammoudeh & Ahmed Khalifa, 2013. "Do Global Shocks Drive Investor Herds in Oil-Rich Frontier Markets?," Working Papers 819, Economic Research Forum, revised Dec 2013.
    6. Balcilar, Mehmet & Demirer, Rıza & Hammoudeh, Shawkat, 2014. "What drives herding in oil-rich, developing stock markets? Relative roles of own volatility and global factors," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 418-440.

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    More about this item

    Keywords

    Oil Price; Stock Market; Gulf Corporation Council (GCC) countries; Markov Switching Model; Time-Varying Granger-causality;
    All these keywords.

    JEL classification:

    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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