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On the dynamic dependence and investment performance of crude oil and clean energy stocks

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  • Ahmad, Wasim

Abstract

This paper examines the directional spillover between crude oil prices and stock prices of technology and clean energy companies. The study uses the daily data over the period from May 2005 to April 2015. The estimated results exhibit following empirical regularities. First, it appears that technology stocks play vital role in the return and volatility spillovers of renewable energy stocks and crude oil prices. Second, technology (PSE) and clean energy indices (ECO) are the dominant emitters of return and volatility spillovers to the crude oil (WTI) prices. Third, the time and event-dependent movements are well captured by the directional spillover approach. Fourth, the application of directional spillover method seems to be more advantageous than MGARCH models as it not only establishes the inter-variables return and volatility spillovers but also helps in identifying direction of spillover through calculation of pairwise net spillovers. Last, the dynamic hedging results suggest that clean energy index can provide a profitable hedging opportunity in combination with crude oil futures than technology index. Many new findings further discussed and analysed.

Suggested Citation

  • Ahmad, Wasim, 2017. "On the dynamic dependence and investment performance of crude oil and clean energy stocks," Research in International Business and Finance, Elsevier, vol. 42(C), pages 376-389.
  • Handle: RePEc:eee:riibaf:v:42:y:2017:i:c:p:376-389
    DOI: 10.1016/j.ribaf.2017.07.140
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    1. Ling, Shiqing & McAleer, Michael, 2003. "Asymptotic Theory For A Vector Arma-Garch Model," Econometric Theory, Cambridge University Press, vol. 19(2), pages 280-310, April.
    2. Antonakakis, Nikolaos & Vergos, Konstantinos, 2013. "Sovereign bond yield spillovers in the Euro zone during the financial and debt crisis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 26(C), pages 258-272.
    3. Managi, Shunsuke & Okimoto, Tatsuyoshi, 2013. "Does the price of oil interact with clean energy prices in the stock market?," Japan and the World Economy, Elsevier, vol. 27(C), pages 1-9.
    4. Henriques, Irene & Sadorsky, Perry, 2008. "Oil prices and the stock prices of alternative energy companies," Energy Economics, Elsevier, vol. 30(3), pages 998-1010, May.
    5. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    6. Chkili, Walid, 2016. "Dynamic correlations and hedging effectiveness between gold and stock markets: Evidence for BRICS countries," Research in International Business and Finance, Elsevier, vol. 38(C), pages 22-34.
    7. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    8. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    9. Sadorsky, Perry, 2012. "Correlations and volatility spillovers between oil prices and the stock prices of clean energy and technology companies," Energy Economics, Elsevier, vol. 34(1), pages 248-255.
    10. Omri, Anis & Ben Mabrouk, Nejah & Sassi-Tmar, Amel, 2015. "Modeling the causal linkages between nuclear energy, renewable energy and economic growth in developed and developing countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 1012-1022.
    11. Sanjay Sehgal & Wasim Ahmad & Florent Deisting, 2015. "An investigation of price discovery and volatility spillovers in India’s foreign exchange market," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 42(2), pages 261-284, May.
    12. Kumar, Surender & Managi, Shunsuke & Matsuda, Akimi, 2012. "Stock prices of clean energy firms, oil and carbon markets: A vector autoregressive analysis," Energy Economics, Elsevier, vol. 34(1), pages 215-226.
    13. Bondia, Ripsy & Ghosh, Sajal & Kanjilal, Kakali, 2016. "International crude oil prices and the stock prices of clean energy and technology companies: Evidence from non-linear cointegration tests with unknown structural breaks," Energy, Elsevier, vol. 101(C), pages 558-565.
    14. Kamil Yilmaz, 2009. "Business Cycle Spillovers," 2009 Meeting Papers 1079, Society for Economic Dynamics.
    15. Maghyereh, Aktham I. & Awartani, Basel, 2016. "Dynamic transmissions between Sukuk and bond markets," Research in International Business and Finance, Elsevier, vol. 38(C), pages 246-261.
    16. Garman, Mark B & Klass, Michael J, 1980. "On the Estimation of Security Price Volatilities from Historical Data," The Journal of Business, University of Chicago Press, vol. 53(1), pages 67-78, January.
    17. Luc Bauwens & Sébastien Laurent & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109, January.
    18. Antonakakis, Nikolaos & Kizys, Renatas, 2015. "Dynamic spillovers between commodity and currency markets," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 303-319.
    19. 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(4), pages 535-551, December.
    20. Kamil Yilmaz, 2009. "International Business Cycle Spillovers," Koç University-TUSIAD Economic Research Forum Working Papers 0903, Koc University-TUSIAD Economic Research Forum, revised Nov 2009.
    21. Tamakoshi, Go & Hamori, Shigeyuki, 2016. "Time-varying co-movements and volatility spillovers among financial sector CDS indexes in the UK," Research in International Business and Finance, Elsevier, vol. 36(C), pages 288-296.
    22. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    23. Inchauspe, Julian & Ripple, Ronald D. & Trück, Stefan, 2015. "The dynamics of returns on renewable energy companies: A state-space approach," Energy Economics, Elsevier, vol. 48(C), pages 325-335.
    24. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    25. Cronin, David, 2014. "The interaction between money and asset markets: A spillover index approach," Journal of Macroeconomics, Elsevier, vol. 39(PA), pages 185-202.
    26. 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.
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    More about this item

    Keywords

    Clean energy stocks; Multivariate GARCH; Directional spillover; Oil prices;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources

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