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The Dynamic Volatility Connectedness Structure of Energy Futures and Global Financial Markets: Evidence From a Novel Time–Frequency Domain Approach

Author

Listed:
  • Ehsan Bagheri

    (K. N. Toosi University of Technology)

  • Seyed Babak Ebrahimi

    (K. N. Toosi University of Technology)

  • Arman Mohammadi

    (K. N. Toosi University of Technology)

  • Mahsa Miri

    (Islamic Azad University)

  • Stelios Bekiros

    (European University Institute)

Abstract

We consider directional volatility connectedness among energy markets and financial markets over time and frequencies simultaneously during the period 2007–2018. We utilize and expand Barunik and Krehlik (J Financ Econom 16:271-296, 2018) connectedness measurements using HVAR in order to achieve a better perspective of energy markets. Our results indicate that during a crisis, the connectedness among markets increases dramatically. Furthermore, our findings support that markets are mostly driven by short-term factors and are highly speculative. Among energy markets, Natural Gas Futures contribute the least to other markets in all time frames. Besides, London Gas Oil Futures and Heating Oil Futures collaborate. Currencies and Natural Gas Futures are suitable choices for portfolio managers to hedge their risks especially in the long run. The findings of this article can offer new insights to policymakers about the mechanism of connectedness among different markets and international investors.

Suggested Citation

  • Ehsan Bagheri & Seyed Babak Ebrahimi & Arman Mohammadi & Mahsa Miri & Stelios Bekiros, 2022. "The Dynamic Volatility Connectedness Structure of Energy Futures and Global Financial Markets: Evidence From a Novel Time–Frequency Domain Approach," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 1087-1111, March.
    • Handle: RePEc:kap:compec:v:59:y:2022:i:3:d:10.1007_s10614-021-10120-x
    DOI: 10.1007/s10614-021-10120-x
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    as
    1. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    2. Mert Demirer & Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2018. "Estimating global bank network connectedness," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(1), pages 1-15, January.
    3. Viral V. Acharya & Lasse H. Pedersen & Thomas Philippon & Matthew Richardson, 2017. "Measuring Systemic Risk," The Review of Financial Studies, Society for Financial Studies, vol. 30(1), pages 2-47.
    4. Billio, Monica & Getmansky, Mila & Lo, Andrew W. & Pelizzon, Loriana, 2012. "Econometric measures of connectedness and systemic risk in the finance and insurance sectors," Journal of Financial Economics, Elsevier, vol. 104(3), pages 535-559.
    5. Xiaoyong Xiao & Jing Huang, 2018. "Dynamic Connectedness of International Crude Oil Prices: The Diebold–Yilmaz Approach," Sustainability, MDPI, vol. 10(9), pages 1-16, September.
    6. Lutz Kilian, 2008. "The Economic Effects of Energy Price Shocks," Journal of Economic Literature, American Economic Association, vol. 46(4), pages 871-909, December.
    7. Hsu, Nan-Jung & Hung, Hung-Lin & Chang, Ya-Mei, 2008. "Subset selection for vector autoregressive processes using Lasso," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3645-3657, March.
    8. Tiwari, Aviral Kumar & Cunado, Juncal & Gupta, Rangan & Wohar, Mark E., 2018. "Volatility spillovers across global asset classes: Evidence from time and frequency domains," The Quarterly Review of Economics and Finance, Elsevier, vol. 70(C), pages 194-202.
    9. Shahzad, Syed Jawad Hussain & Hernandez, Jose Areola & Rehman, Mobeen Ur & Al-Yahyaee, Khamis Hamed & Zakaria, Muhammad, 2018. "A global network topology of stock markets: Transmitters and receivers of spillover effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 2136-2153.
    10. 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.
    11. Parkinson, Michael, 1980. "The Extreme Value Method for Estimating the Variance of the Rate of Return," The Journal of Business, University of Chicago Press, vol. 53(1), pages 61-65, January.
    12. Yuki Toyoshima & Shigeyuki Hamori, 2018. "Measuring the Time-Frequency Dynamics of Return and Volatility Connectedness in Global Crude Oil Markets," Energies, MDPI, vol. 11(11), pages 1-18, October.
    13. Nader Trabelsi, 2018. "Are There Any Volatility Spill-Over Effects among Cryptocurrencies and Widely Traded Asset Classes?," JRFM, MDPI, vol. 11(4), pages 1-17, October.
    14. Kang, Sang Hoon & Lee, Jang Woo, 2019. "The network connectedness of volatility spillovers across global futures markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    15. Awartani, Basel & Aktham, Maghyereh & Cherif, Guermat, 2016. "The connectedness between crude oil and financial markets: Evidence from implied volatility indices," Journal of Commodity Markets, Elsevier, vol. 4(1), pages 56-69.
    16. Shahzad, Syed Jawad Hussain & Arreola-Hernandez, Jose & Bekiros, Stelios & Shahbaz, Muhammad & Kayani, Ghulam Mujtaba, 2018. "A systemic risk analysis of Islamic equity markets using vine copula and delta CoVaR modeling," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 56(C), pages 104-127.
    17. Song Song & Peter J. Bickel, 2011. "Large Vector Auto Regressions," Papers 1106.3915, arXiv.org.
    18. Ferrer, Román & Shahzad, Syed Jawad Hussain & López, Raquel & Jareño, Francisco, 2018. "Time and frequency dynamics of connectedness between renewable energy stocks and crude oil prices," Energy Economics, Elsevier, vol. 76(C), pages 1-20.
    19. Wang, Yilin & Zhang, Zeming & Li, Xiafei & Chen, Xiaodan & Wei, Yu, 2020. "Dynamic return connectedness across global commodity futures markets: Evidence from time and frequency domains," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    20. Yuki Toyoshima & Tadahiro Nakajima & Shigeyuki Hamori, 2013. "Crude oil hedging strategy: new evidence from the data of the financial crisis," Applied Financial Economics, Taylor & Francis Journals, vol. 23(12), pages 1033-1041, June.
    21. Wang, Xunxiao & Wang, Yudong, 2019. "Volatility spillovers between crude oil and Chinese sectoral equity markets: Evidence from a frequency dynamics perspective," Energy Economics, Elsevier, vol. 80(C), pages 995-1009.
    22. Joseph McCarthy & Alexei G. Orlov, 2012. "Time-frequency analysis of crude oil and S&P500 futures contracts," Quantitative Finance, Taylor & Francis Journals, vol. 12(12), pages 1893-1908, December.
    23. Peter Schwendner & Martin Schuele & Thomas Ott & Martin Hillebrand, 2015. "European Government Bond Dynamics and Stability Policies: Taming Contagion Risks," Working Papers 8, European Stability Mechanism.
    24. Husain, Shaiara & Tiwari, Aviral Kumar & Sohag, Kazi & Shahbaz, Muhammad, 2019. "Connectedness among crude oil prices, stock index and metal prices: An application of network approach in the USA," Resources Policy, Elsevier, vol. 62(C), pages 57-65.
    25. Yoon, Seong-Min & Al Mamun, Md & Uddin, Gazi Salah & Kang, Sang Hoon, 2019. "Network connectedness and net spillover between financial and commodity markets," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 801-818.
    26. 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.
    27. Yi, Shuyue & Xu, Zishuang & Wang, Gang-Jin, 2018. "Volatility connectedness in the cryptocurrency market: Is Bitcoin a dominant cryptocurrency?," International Review of Financial Analysis, Elsevier, vol. 60(C), pages 98-114.
    28. Wen, Tiange & Wang, Gang-Jin, 2020. "Volatility connectedness in global foreign exchange markets," Journal of Multinational Financial Management, Elsevier, vol. 54(C).
    29. Zhang, Dayong, 2017. "Oil shocks and stock markets revisited: Measuring connectedness from a global perspective," Energy Economics, Elsevier, vol. 62(C), pages 323-333.
    30. Maghyereh, Aktham I. & Awartani, Basel & Bouri, Elie, 2016. "The directional volatility connectedness between crude oil and equity markets: New evidence from implied volatility indexes," Energy Economics, Elsevier, vol. 57(C), pages 78-93.
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