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Volatility Transmissions between Oil Prices and Emerging Market Sectors: Implications for Portfolio Management and Hedging Strategies

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  • Sercan Demiralay

    (Department of International Finance, Faculty of Commercial Sciences, Yeditepe University, 34755, Istanbul, Turkey)

  • Hatice Gaye Gencer

    (Department of Business Administration, Faculty of Economics and Administrative Sciences, Yeditepe University, 34755, Istanbul, Turkey)

Abstract

This paper investigates the mechanisms of return and volatility transmissions between oil prices and five emerging market sector returns. For the empirical method, we utilize a recent and novel technique: Vector Autoregressive-Asymmetric GARCH (VAR-AGARCH) model. We find some significant cross shock and volatility linkages between oil prices and the sectors. However, our results manifest that the sector indices are not affected equally or simultaneously by movements in oil prices. Additionally, we compute the optimal holding weights and hedge ratios for the two-asset portfolio consisting of oil and each sector index. Our empirical findings have potential implications for investors and portfolio managers.

Suggested Citation

  • Sercan Demiralay & Hatice Gaye Gencer, 2014. "Volatility Transmissions between Oil Prices and Emerging Market Sectors: Implications for Portfolio Management and Hedging Strategies," International Journal of Energy Economics and Policy, Econjournals, vol. 4(3), pages 442-447.
  • Handle: RePEc:eco:journ2:2014-03-13
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    References listed on IDEAS

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    1. Malik, Farooq & Ewing, Bradley T., 2009. "Volatility transmission between oil prices and equity sector returns," International Review of Financial Analysis, Elsevier, vol. 18(3), pages 95-100, June.
    2. Kroner, Kenneth F & Ng, Victor K, 1998. "Modeling Asymmetric Comovements of Asset Returns," Review of Financial Studies, Society for Financial Studies, vol. 11(4), pages 817-844.
    3. Lutz Kilian & Cheolbeom Park, 2009. "The Impact Of Oil Price Shocks On The U.S. Stock Market," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 50(4), pages 1267-1287, November.
    4. Park, Jungwook & Ratti, Ronald A., 2008. "Oil price shocks and stock markets in the U.S. and 13 European countries," Energy Economics, Elsevier, vol. 30(5), pages 2587-2608, September.
    5. Michael McAleer & Suhejla Hoti & Felix Chan, 2009. "Structure and Asymptotic Theory for Multivariate Asymmetric Conditional Volatility," Econometric Reviews, Taylor & Francis Journals, vol. 28(5), pages 422-440.
    6. Driesprong, Gerben & Jacobsen, Ben & Maat, Benjamin, 2008. "Striking oil: Another puzzle?," Journal of Financial Economics, Elsevier, vol. 89(2), pages 307-327, August.
    7. Narayan, Paresh Kumar & Narayan, Seema, 2010. "Modelling the impact of oil prices on Vietnam's stock prices," Applied Energy, Elsevier, vol. 87(1), pages 356-361, January.
    8. Filis, George & Degiannakis, Stavros & Floros, Christos, 2011. "Dynamic correlation between stock market and oil prices: The case of oil-importing and oil-exporting countries," International Review of Financial Analysis, Elsevier, vol. 20(3), pages 152-164, June.
    9. Kroner, Kenneth F. & Sultan, Jahangir, 1993. "Time-Varying Distributions and Dynamic Hedging with Foreign Currency Futures," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(04), pages 535-551, December.
    10. Sadorsky, Perry, 2001. "Risk factors in stock returns of Canadian oil and gas companies," Energy Economics, Elsevier, vol. 23(1), pages 17-28, January.
    11. Hamilton, James D, 1983. "Oil and the Macroeconomy since World War II," Journal of Political Economy, University of Chicago Press, vol. 91(2), pages 228-248, April.
    12. Arouri, Mohamed El Hedi & Lahiani, Amine & Nguyen, Duc Khuong, 2011. "Return and volatility transmission between world oil prices and stock markets of the GCC countries," Economic Modelling, Elsevier, vol. 28(4), pages 1815-1825, July.
    13. Sadorsky, Perry, 1999. "Oil price shocks and stock market activity," Energy Economics, Elsevier, vol. 21(5), pages 449-469, October.
    14. Jones, Charles M & Kaul, Gautam, 1996. " Oil and the Stock Markets," Journal of Finance, American Finance Association, vol. 51(2), pages 463-491, June.
    15. Elyasiani, Elyas & Mansur, Iqbal & Odusami, Babatunde, 2011. "Oil price shocks and industry stock returns," Energy Economics, Elsevier, vol. 33(5), pages 966-974, September.
    16. Mazin A. M. Al Janabi & Abdulnasser Hatemi-J & Manuchehr Irandoust, 2010. "Modeling Time-Varying Volatility and Expected Returns: Evidence from the GCC and MENA Regions," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 46(5), pages 39-47, September.
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    Cited by:

    1. Tanattrin Bunnag, 2015. "Hedging Petroleum Futures with Multivariate GARCH Models," International Journal of Energy Economics and Policy, Econjournals, vol. 5(1), pages 105-120.
    2. Mohamed Osman, 2015. "Dynamic Asymmetries in the Electric Consumption of the GCC Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 5(2), pages 461-467.
    3. repec:eeb:articl:v:3:y:2017:n:1:p:28-47 is not listed on IDEAS

    More about this item

    Keywords

    Emerging sector indices; oil prices; volatility transmission; optimal weights; hedge ratios;

    JEL classification:

    • 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
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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