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Volatility Contagion from Bulk Shipping and Petrochemical Industries to Oil Futures Market during the Economic Uncertainty

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  • Arthur Jin Lin

    (Graduate School of International Business, National Taipei University, New Taipei City 23741, Taiwan)

Abstract

The purposes of the research have evidenced the spillover effects of oil-related factors in the oil market and the leading indexes of petrochemical commodities and the bulk shipping markets. The research gap was fitted and explored the effects associated with leading indexes for the shipping and petrochemical markets on the oil market during the US-China trade war, which is seldom bridged with significant relations in the history of oil. The scope of data for the period from 4 January 2016, through 31 August 2022, were analyzed using a generalized autoregressive conditional heteroskedastic mixed data sampling model as methodology of mix frequency to examine volatility spillover of four research hypotheses from the bulk shipping and petrochemical markets to the oil market. Main contributions revealed that spillover from the bulk shipping and petrochemical commodity markets transmitted significant volatility to West Texas Intermediate (WTI) oil returns after the US-China trade war began, a trend that has continued throughout the COVID-19 era until Ukraine–Russia war. These rare events indicate that the realized volatility derived from these market variables can be used to track the more significant contagions on WTI futures volatility in this empirical research than the weak relation in past studies.

Suggested Citation

  • Arthur Jin Lin, 2023. "Volatility Contagion from Bulk Shipping and Petrochemical Industries to Oil Futures Market during the Economic Uncertainty," Mathematics, MDPI, vol. 11(17), pages 1-19, August.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:17:p:3737-:d:1229443
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    as
    1. Jiang, Jingze & Marsh, Thomas L. & Tozer, Peter R., 2015. "Policy induced price volatility transmission: Linking the U.S. crude oil, corn and plastics markets," Energy Economics, Elsevier, vol. 52(PA), pages 217-227.
    2. repec:dau:papers:123456789/14980 is not listed on IDEAS
    3. Elie Bouri & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2021. "Forecasting Realized Volatility of Bitcoin: The Role of the Trade War," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 29-53, January.
    4. Marcin Fałdziński & Piotr Fiszeder & Witold Orzeszko, 2020. "Forecasting Volatility of Energy Commodities: Comparison of GARCH Models with Support Vector Regression," Energies, MDPI, vol. 14(1), pages 1-18, December.
    5. Yang, Jun & Lu, Jing & Xiang, Cheng, 2020. "Company visits and stock price crash risk: Evidence from China," Emerging Markets Review, Elsevier, vol. 44(C).
    6. 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.
    7. Robert F. Engle & Eric Ghysels & Bumjean Sohn, 2013. "Stock Market Volatility and Macroeconomic Fundamentals," The Review of Economics and Statistics, MIT Press, vol. 95(3), pages 776-797, July.
    8. Boubaker, Sabri & Jouini, Jamel & Lahiani, Amine, 2016. "Financial contagion between the US and selected developed and emerging countries: The case of the subprime crisis," The Quarterly Review of Economics and Finance, Elsevier, vol. 61(C), pages 14-28.
    9. Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2021. "Forecasting realized volatility of bitcoin returns: tail events and asymmetric loss," The European Journal of Finance, Taylor & Francis Journals, vol. 27(16), pages 1626-1644, November.
    10. Lutz Kilian, 2009. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market," American Economic Review, American Economic Association, vol. 99(3), pages 1053-1069, June.
    11. 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.
    12. Liangcheng Wang & Yining Dai & Yifan Zhang & Yuye Ding, 2020. "Auditor gender and stock price crash risk: evidence from China," Applied Economics, Taylor & Francis Journals, vol. 52(55), pages 5995-6008, November.
    13. Matti-Mikael Koskinen & Olli-Pekka Hilmola, 2005. "Investment Cycles in the Newbuilding Market of Ice-Strengthened Oil Tankers," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 7(2), pages 173-188, June.
    14. Adland, Roar & Cullinane, Kevin, 2006. "The non-linear dynamics of spot freight rates in tanker markets," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 42(3), pages 211-224, May.
    15. Tsouknidis, Dimitris A., 2016. "Dynamic volatility spillovers across shipping freight markets," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 91(C), pages 90-111.
    16. Alizadeh, Amir H. & Huang, Chih-Yueh & van Dellen, Stefan, 2015. "A regime switching approach for hedging tanker shipping freight rates," Energy Economics, Elsevier, vol. 49(C), pages 44-59.
    17. Suyu Sun & Xueling Shang & Weiwei Liu, 2020. "Bank monitoring and stock price crash risk: Evidence from China," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 10(1), pages 1-2.
    18. Conrad, Christian & Loch, Karin & Rittler, Daniel, 2014. "On the macroeconomic determinants of long-term volatilities and correlations in U.S. stock and crude oil markets," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 26-40.
    19. Robert F. Engle & Jose Gonzalo Rangel, 2008. "The Spline-GARCH Model for Low-Frequency Volatility and Its Global Macroeconomic Causes," The Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1187-1222, May.
    20. Wang, Yudong & Liu, Li & Wu, Chongfeng, 2017. "Forecasting the real prices of crude oil using forecast combinations over time-varying parameter models," Energy Economics, Elsevier, vol. 66(C), pages 337-348.
    21. Bonga-Bonga, Lumengo, 2018. "Uncovering equity market contagion among BRICS countries: An application of the multivariate GARCH model," The Quarterly Review of Economics and Finance, Elsevier, vol. 67(C), pages 36-44.
    22. Gu, Fu & Wang, Jiqiang & Guo, Jianfeng & Fan, Ying, 2020. "Dynamic linkages between international oil price, plastic stock index and recycle plastic markets in China," International Review of Economics & Finance, Elsevier, vol. 68(C), pages 167-179.
    23. 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.
    24. Christian Conrad & Onno Kleen, 2020. "Two are better than one: Volatility forecasting using multiplicative component GARCH‐MIDAS models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 19-45, January.
    25. Manolis G. Kavussanos & Nikos K. Nomikos, 1999. "The forward pricing function of the shipping freight futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 19(3), pages 353-376, May.
    26. Michel A. Robe & Jonathan Wallen, 2016. "Fundamentals, Derivatives Market Information and Oil Price Volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(4), pages 317-344, April.
    27. Meng, Qingbin & Song, Xuan & Liu, Chunlin & Wu, Qun & Zeng, Hongchao, 2020. "The impact of block trades on stock price synchronicity: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 68(C), pages 239-253.
    28. Zhang, Yue-Jun & Wang, Jin-Li, 2019. "Do high-frequency stock market data help forecast crude oil prices? Evidence from the MIDAS models," Energy Economics, Elsevier, vol. 78(C), pages 192-201.
    29. Khaled Guesmi & Ilyes Abid & Anna Creti & Julien Chevallier, 2018. "Oil Price Risk and Financial Contagion," Post-Print hal-02314038, HAL.
    30. Masih, Mansur & Algahtani, Ibrahim & De Mello, Lurion, 2010. "Price dynamics of crude oil and the regional ethylene markets," Energy Economics, Elsevier, vol. 32(6), pages 1435-1444, November.
    31. An, Sufang & Gao, Xiangyun & An, Haizhong & An, Feng & Sun, Qingru & Liu, Siyao, 2020. "Windowed volatility spillover effects among crude oil prices," Energy, Elsevier, vol. 200(C).
    32. Wang, Lu & Ma, Feng & Liu, Jing & Yang, Lin, 2020. "Forecasting stock price volatility: New evidence from the GARCH-MIDAS model," International Journal of Forecasting, Elsevier, vol. 36(2), pages 684-694.
    33. Ruan, Qingsong & Wang, Yao & Lu, Xinsheng & Qin, Jing, 2016. "Cross-correlations between Baltic Dry Index and crude oil prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 453(C), pages 278-289.
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