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Network connectedness between natural gas markets, uncertainty and stock markets

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  • Geng, Jiang-Bo
  • Chen, Fu-Rui
  • Ji, Qiang
  • Liu, Bing-Yue

Abstract

This paper explores dynamic information connectedness effects between natural gas markets, uncertainties and stock markets in the North American and European regions for high- and low-frequency bands using the time-frequency connectedness network model. The empirical results suggest that the total return and volatility spillover effects in North America and Europe are mainly generated by the high-frequency band (1–12 weeks), whereas the total spillover effect for the low-frequency band (12 weeks to longer) is relatively weak. Generally, in terms of return connectedness, the North American and European natural gas markets act as information receivers to the system. With regard to volatility connectedness, the North American gas market has an impact on energy market uncertainty and economic policy uncertainty, whereas the European gas market acts as an information receiver from economic policy uncertainty. Finally, our evidence shows that both these regional gas markets are affected to a considerable extent by financial market uncertainty in both the short and long term. These new findings suggest some useful implications for investors and policy makers with various time horizons.

Suggested Citation

  • Geng, Jiang-Bo & Chen, Fu-Rui & Ji, Qiang & Liu, Bing-Yue, 2021. "Network connectedness between natural gas markets, uncertainty and stock markets," Energy Economics, Elsevier, vol. 95(C).
  • Handle: RePEc:eee:eneeco:v:95:y:2021:i:c:s0140988320303418
    DOI: 10.1016/j.eneco.2020.105001
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    1. Syed Jawad Hussain Shahzad & Elie Bouri & Naveed Raza & David Roubaud, 2019. "Asymmetric impacts of disaggregated oil price shocks on uncertainties and investor sentiment," Review of Quantitative Finance and Accounting, Springer, vol. 52(3), pages 901-921, April.
    2. Gupta, Rangan & Wohar, Mark, 2017. "Forecasting oil and stock returns with a Qual VAR using over 150years off data," Energy Economics, Elsevier, vol. 62(C), pages 181-186.
    3. 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.
    4. Tiwari, Aviral Kumar & Jena, Sangram Keshari & Mitra, Amarnath & Yoon, Seong-Min, 2018. "Impact of oil price risk on sectoral equity markets: Implications on portfolio management," Energy Economics, Elsevier, vol. 72(C), pages 120-134.
    5. Filippo di Mauro & L. Vanessa Smith & Stephane Dees & M. Hashem Pesaran, 2007. "Exploring the international linkages of the euro area: a global VAR analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(1), pages 1-38.
    6. repec:dau:papers:123456789/14980 is not listed on IDEAS
    7. Libo Yin & Liyan Han, 2014. "Macroeconomic uncertainty: does it matter for commodity prices?," Applied Economics Letters, Taylor & Francis Journals, vol. 21(10), pages 711-716, July.
    8. Li, Lei & Yin, Libo & Zhou, Yimin, 2016. "Exogenous shocks and the spillover effects between uncertainty and oil price," Energy Economics, Elsevier, vol. 54(C), pages 224-234.
    9. Ian Dew-Becker & Stefano Giglio, 2016. "Asset Pricing in the Frequency Domain: Theory and Empirics," The Review of Financial Studies, Society for Financial Studies, vol. 29(8), pages 2029-2068.
    10. Zhang, Dayong & Wang, Tiantian & Shi, Xunpeng & Liu, Jia, 2018. "Is hub-based pricing a better choice than oil indexation for natural gas? Evidence from a multiple bubble test," Energy Economics, Elsevier, vol. 76(C), pages 495-503.
    11. Pástor, Ľuboš & Veronesi, Pietro, 2013. "Political uncertainty and risk premia," Journal of Financial Economics, Elsevier, vol. 110(3), pages 520-545.
    12. Kang, Wensheng & Ratti, Ronald A., 2013. "Structural oil price shocks and policy uncertainty," Economic Modelling, Elsevier, vol. 35(C), pages 314-319.
    13. Aboura, Sofiane & Chevallier, Julien, 2013. "Leverage vs. feedback: Which Effect drives the oil market?," Finance Research Letters, Elsevier, vol. 10(3), pages 131-141.
    14. Stiassny, Alfred, 1996. "A Spectral Decomposition for Structural VAR Models," Empirical Economics, Springer, vol. 21(4), pages 535-555.
    15. Schwert, G William, 2002. "Tests for Unit Roots: A Monte Carlo Investigation," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 5-17, January.
    16. Bouri, Elie & Lien, Donald & Roubaud, David & Shahzad, Syed Jawad Hussain, 2018. "Directional predictability of implied volatility: From crude oil to developed and emerging stock markets," Finance Research Letters, Elsevier, vol. 27(C), pages 65-79.
    17. Kang, Wensheng & Ratti, Ronald A. & Vespignani, Joaquin L., 2017. "Oil price shocks and policy uncertainty: New evidence on the effects of US and non-US oil production," Energy Economics, Elsevier, vol. 66(C), pages 536-546.
    18. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    19. Creti, Anna & Joëts, Marc & Mignon, Valérie, 2013. "On the links between stock and commodity markets' volatility," Energy Economics, Elsevier, vol. 37(C), pages 16-28.
    20. 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.
    21. Hans-Martin Krolzig, 2003. "General-to-Specific Model Selection Procedures for Structural Vector Autoregressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(s1), pages 769-801, December.
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