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Dynamic volatility spillovers across oil and natural gas futures markets based on a time-varying spillover method

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  • Gong, Xu
  • Liu, Yun
  • Wang, Xiong

Abstract

This paper analyzes dynamic volatility spillovers between four major energy commodities (i.e., crude oil, gasoline, heating oil and natural gas) in the oil-natural gas future markets. We construct a time-varying spillover method by combining the TVP-VAR-SV model and the spillover method of Diebold and Yilmaz (2009, 2012, 2014). We use the spillover method to obtain time-varying total, directional and pairwise volatility spillover indices. Our results summarize as follows: (1) The volatility spillover indices present peaks and troughs during some periods, such as shale gas revolution, financial crisis, and oil price crash; (2) After the U.S. shale gas revolution, the size of volatility spillover from natural gas future market has reduced sharply, but volatility doesn't decouple from the other three oil future markets; (3) The directional spillover is asymmetric. The crude oil and heating oil futures market are main net transmitter of volatility risk information, while the gasoline and natural gas futures markets are the net receiver; (4) For natural gas future market, the pairwise volatility spillover from crude oil future market has the most significant influence.

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  • Gong, Xu & Liu, Yun & Wang, Xiong, 2021. "Dynamic volatility spillovers across oil and natural gas futures markets based on a time-varying spillover method," International Review of Financial Analysis, Elsevier, vol. 76(C).
    • Handle: RePEc:eee:finana:v:76:y:2021:i:c:s1057521921001277
    DOI: 10.1016/j.irfa.2021.101790
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    as
    1. Jozef Baruník & Evžen KoÄ enda b,a & Lukáš Vácha, 2016. "Volatility Spillovers Across Petroleum Markets," The Energy Journal, , vol. 37(1), pages 136-158, January.
    2. 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.
    3. 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.
    4. Chang, C-L. & McAleer, M.J. & Tansuchat, R., 2010. "Analyzing and Forecasting Volatility Spillovers and Asymmetries in Major Crude Oil Spot, Forward and Futures Markets," Econometric Institute Research Papers EI 2010-14, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. Zhang, Dayong & Ji, Qiang & Kutan, Ali M., 2019. "Dynamic transmission mechanisms in global crude oil prices: Estimation and implications," Energy, Elsevier, vol. 175(C), pages 1181-1193.
    6. Jebabli, Ikram & Arouri, Mohamed & Teulon, Frédéric, 2014. "On the effects of world stock market and oil price shocks on food prices: An empirical investigation based on TVP-VAR models with stochastic volatility," Energy Economics, Elsevier, vol. 45(C), pages 66-98.
    7. 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.
    8. Gong, Xu & Lin, Boqiang, 2018. "The incremental information content of investor fear gauge for volatility forecasting in the crude oil futures market," Energy Economics, Elsevier, vol. 74(C), pages 370-386.
    9. Bassam Fattouh, Lutz Kilian, and Lavan Mahadeva, 2013. "The Role of Speculation in Oil Markets: What Have We Learned So Far?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    10. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2020. "Dynamic frequency connectedness between oil and natural gas volatilities," Economic Modelling, Elsevier, vol. 84(C), pages 181-189.
    11. Batten, Jonathan A. & Ciner, Cetin & Lucey, Brian M., 2017. "The dynamic linkages between crude oil and natural gas markets," Energy Economics, Elsevier, vol. 62(C), pages 155-170.
    12. Nicola, Francesca de & De Pace, Pierangelo & Hernandez, Manuel A., 2016. "Co-movement of major energy, agricultural, and food commodity price returns: A time-series assessment," Energy Economics, Elsevier, vol. 57(C), pages 28-41.
    13. Chang, Chia-Lin & McAleer, Michael & Tansuchat, Roengchai, 2010. "Analyzing and forecasting volatility spillovers, asymmetries and hedging in major oil markets," Energy Economics, Elsevier, vol. 32(6), pages 1445-1455, November.
    14. Zhang, Yue-Jun & Ma, Shu-Jiao, 2019. "How to effectively estimate the time-varying risk spillover between crude oil and stock markets? Evidence from the expectile perspective," Energy Economics, Elsevier, vol. 84(C).
    15. Geert Bekaert & Campbell R. Harvey & Angela Ng, 2005. "Market Integration and Contagion," The Journal of Business, University of Chicago Press, vol. 78(1), pages 39-70, January.
    16. Jin, Xiaoye & Xiaowen Lin, Sharon & Tamvakis, Michael, 2012. "Volatility transmission and volatility impulse response functions in crude oil markets," Energy Economics, Elsevier, vol. 34(6), pages 2125-2134.
    17. Boldanov, Rustam & Degiannakis, Stavros & Filis, George, 2016. "Time-varying correlation between oil and stock market volatilities: Evidence from oil-importing and oil-exporting countries," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 209-220.
    18. Karali, Berna & Ramirez, Octavio A., 2014. "Macro determinants of volatility and volatility spillover in energy markets," Energy Economics, Elsevier, vol. 46(C), pages 413-421.
    19. Xu Gong & Boqiang Lin, 2018. "Structural breaks and volatility forecasting in the copper futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(3), pages 290-339, March.
    20. Strohsal, Till & Weber, Enzo, 2015. "Time-varying international stock market interaction and the identification of volatility signals," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 28-36.
    21. Michael S. Haigh & Matthew T. Holt, 2002. "Crack spread hedging: accounting for time-varying volatility spillovers in the energy futures markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(3), pages 269-289.
    22. Zhang, Bing & Wang, Peijie, 2014. "Return and volatility spillovers between china and world oil markets," Economic Modelling, Elsevier, vol. 42(C), pages 413-420.
    23. Jouchi Nakajima, 2011. "Time-Varying Parameter VAR Model with Stochastic Volatility: An Overview of Methodology and Empirical Applications," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 29, pages 107-142, November.
    24. Lin, Boqiang & Wesseh, Presley K. & Appiah, Michael Owusu, 2014. "Oil price fluctuation, volatility spillover and the Ghanaian equity market: Implication for portfolio management and hedging effectiveness," Energy Economics, Elsevier, vol. 42(C), pages 172-182.
    25. Li, Jianglong & Xie, Chunping & Long, Houyin, 2019. "The roles of inter-fuel substitution and inter-market contagion in driving energy prices: evidences from China’s coal market," LSE Research Online Documents on Economics 102540, London School of Economics and Political Science, LSE Library.
    26. Wen, Fenghua & Gong, Xu & Cai, Shenghua, 2016. "Forecasting the volatility of crude oil futures using HAR-type models with structural breaks," Energy Economics, Elsevier, vol. 59(C), pages 400-413.
    27. Xu, Weiju & Ma, Feng & Chen, Wang & Zhang, Bing, 2019. "Asymmetric volatility spillovers between oil and stock markets: Evidence from China and the United States," Energy Economics, Elsevier, vol. 80(C), pages 310-320.
    28. Zhang, Weiping & Zhuang, Xintian & Lu, Yang & Wang, Jian, 2020. "Spatial linkage of volatility spillovers and its explanation across G20 stock markets: A network framework," International Review of Financial Analysis, Elsevier, vol. 71(C).
    29. Yip, Pick Schen & Brooks, Robert & Do, Hung Xuan & Nguyen, Duc Khuong, 2020. "Dynamic volatility spillover effects between oil and agricultural products," International Review of Financial Analysis, Elsevier, vol. 69(C).
    30. Niaz Bashiri Behmiri, Matteo Manera, and Marcella Nicolini, 2019. "Understanding Dynamic Conditional Correlations between Oil, Natural Gas and Non-Energy Commodity Futures Markets," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    31. Feng Wu & Zhengfei Guan & Robert J. Myers, 2011. "Volatility spillover effects and cross hedging in corn and crude oil futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 31(11), pages 1052-1075, November.
    32. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 821-852.
    33. Liu, Tangyong & Gong, Xu, 2020. "Analyzing time-varying volatility spillovers between the crude oil markets using a new method," Energy Economics, Elsevier, vol. 87(C).
    34. Li, Jianglong & Xie, Chunping & Long, Houyin, 2019. "The roles of inter-fuel substitution and inter-market contagion in driving energy prices: Evidences from China’s coal market," Energy Economics, Elsevier, vol. 84(C).
    35. Gozgor, Giray & Lau, Chi Keung Marco & Bilgin, Mehmet Huseyin, 2016. "Commodity markets volatility transmission: Roles of risk perceptions and uncertainty in financial markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 44(C), pages 35-45.
    36. Ji, Qiang & Bouri, Elie & Lau, Chi Keung Marco & Roubaud, David, 2019. "Dynamic connectedness and integration in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 257-272.
    37. Panagiotidis, Theodore & Rutledge, Emilie, 2007. "Oil and gas markets in the UK: Evidence from a cointegrating approach," Energy Economics, Elsevier, vol. 29(2), pages 329-347, March.
    38. Sukcharoen, Kunlapath & Leatham, David J., 2017. "Hedging downside risk of oil refineries: A vine copula approach," Energy Economics, Elsevier, vol. 66(C), pages 493-507.
    39. Ji, Qiang & Geng, Jiang-Bo & Tiwari, Aviral Kumar, 2018. "Information spillovers and connectedness networks in the oil and gas markets," Energy Economics, Elsevier, vol. 75(C), pages 71-84.
    40. Erdős, Péter, 2012. "Have oil and gas prices got separated?," Energy Policy, Elsevier, vol. 49(C), pages 707-718.
    41. Sumudu W. Watugala, 2019. "Economic uncertainty, trading activity, and commodity futures volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(8), pages 921-945, August.
    42. Hsu, Stephen D.H. & Murray, Brian M., 2007. "On the volatility of volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 380(C), pages 366-376.
    43. Antonakakis, Nikolaos & Chatziantoniou, Ioannis & Filis, George, 2017. "Oil shocks and stock markets: Dynamic connectedness under the prism of recent geopolitical and economic unrest," International Review of Financial Analysis, Elsevier, vol. 50(C), pages 1-26.
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