IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v185y2017ip2p1788-1798.html
   My bibliography  Save this article

Evolution of world crude oil market integration and diversification: A wavelet-based complex network perspective

Author

Listed:
  • Jia, Xiaoliang
  • An, Haizhong
  • Sun, Xiaoqi
  • Huang, Xuan
  • Wang, Lijun

Abstract

Previous research on the crude oil market has focused on the constant degree of the market integration or diversification, ignoring the time-varying market integration and diversification during different typical stages of the global oil price volatility. This paper proposes a novel wavelet-based complex network method to investigate the evolution feature of the world crude oil market integration and diversification from the perspective of the interdependent structural relationship of global oil prices, so that two critical reference indexes, namely the reference decision-making cycle and the target regional market, will be proposed for decision makers to better adjust their strategies. The results show that the dominant evolution cycle of the market integration from the stable stage to the high shock stage is time-varying, featuring the weekly→weekly→short yearly→short quarterly→short monthly cycle, and the dominant evolution cycle of the market diversification is also time-varying, characterized by the short monthly→weekly→long yearly→weekly→weekly cycle. These findings provide a clearer reference decision-making cycle for decision makers to create a more efficient period-oriented strategy. Two larger stable homogeneous groups of regional oil markets and the dominant regional markets in the process of the market evolution are discovered, providing more details regarding the target monitoring regional market for the oil-related early warningstrategy and hedging strategies.

Suggested Citation

  • Jia, Xiaoliang & An, Haizhong & Sun, Xiaoqi & Huang, Xuan & Wang, Lijun, 2017. "Evolution of world crude oil market integration and diversification: A wavelet-based complex network perspective," Applied Energy, Elsevier, vol. 185(P2), pages 1788-1798.
    • Handle: RePEc:eee:appene:v:185:y:2017:i:p2:p:1788-1798
    DOI: 10.1016/j.apenergy.2015.11.007
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261915014488
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2015.11.007?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Reboredo, Juan C., 2011. "How do crude oil prices co-move?: A copula approach," Energy Economics, Elsevier, vol. 33(5), pages 948-955, September.
    2. Ramsey James B. & Lampart Camille, 1998. "The Decomposition of Economic Relationships by Time Scale Using Wavelets: Expenditure and Income," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 3(1), pages 1-22, April.
    3. Salisu, Afees A. & Fasanya, Ismail O., 2013. "Modelling oil price volatility with structural breaks," Energy Policy, Elsevier, vol. 52(C), pages 554-562.
    4. M. A. Adelman, 1984. "International Oil Agreements," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 1-10.
    5. Ji, Qiang & Guo, Jian-Feng, 2015. "Oil price volatility and oil-related events: An Internet concern study perspective," Applied Energy, Elsevier, vol. 137(C), pages 256-264.
    6. Charles, Amélie & Darné, Olivier, 2009. "The efficiency of the crude oil markets: Evidence from variance ratio tests," Energy Policy, Elsevier, vol. 37(11), pages 4267-4272, November.
    7. Giulietti, Monica & Iregui, Ana María & Otero, Jesús, 2014. "Crude oil price differentials, product heterogeneity and institutional arrangements," Energy Economics, Elsevier, vol. 46(S1), pages 28-32.
    8. Kim Sangbae & In Francis Haeuck, 2003. "The Relationship Between Financial Variables and Real Economic Activity: Evidence From Spectral and Wavelet Analyses," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(4), pages 1-18, December.
    9. An, Haizhong & Gao, Xiangyun & Fang, Wei & Ding, Yinghui & Zhong, Weiqiong, 2014. "Research on patterns in the fluctuation of the co-movement between crude oil futures and spot prices: A complex network approach," Applied Energy, Elsevier, vol. 136(C), pages 1067-1075.
    10. Jammazi, Rania, 2012. "Cross dynamics of oil-stock interactions: A redundant wavelet analysis," Energy, Elsevier, vol. 44(1), pages 750-777.
    11. Lin, Sue J. & Lu, I.J. & Lewis, Charles, 2007. "Grey relation performance correlations among economics, energy use and carbon dioxide emission in Taiwan," Energy Policy, Elsevier, vol. 35(3), pages 1948-1955, March.
    12. repec:zbw:bofrdp:2005_001 is not listed on IDEAS
    13. Zhang, Yue-Jun & Zhang, Lu, 2015. "Interpreting the crude oil price movements: Evidence from the Markov regime switching model," Applied Energy, Elsevier, vol. 143(C), pages 96-109.
    14. Andrew N. Kleit, 2001. "Are Regional Oil Markets Growing Closer Together?: An Arbitrage Cost Approach," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 1-15.
    15. Liu, Li & Chen, Ching-Cheng & Wan, Jieqiu, 2013. "Is world oil market “one great pool”?: An example from China's and international oil markets," Economic Modelling, Elsevier, vol. 35(C), pages 364-373.
    16. Li, Raymond & Leung, Guy C.K., 2011. "The integration of China into the world crude oil market since 1998," Energy Policy, Elsevier, vol. 39(9), pages 5159-5166, September.
    17. Huang, Xuan & An, Haizhong & Gao, Xiangyun & Hao, Xiaoqing & Liu, Pengpeng, 2015. "Multiresolution transmission of the correlation modes between bivariate time series based on complex network theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 493-506.
    18. Jia, Xiaoliang & An, Haizhong & Fang, Wei & Sun, Xiaoqi & Huang, Xuan, 2015. "How do correlations of crude oil prices co-move? A grey correlation-based wavelet perspective," Energy Economics, Elsevier, vol. 49(C), pages 588-598.
    19. Benhmad, François, 2013. "Dynamic cyclical comovements between oil prices and US GDP: A wavelet perspective," Energy Policy, Elsevier, vol. 57(C), pages 141-151.
    20. Candelon, Bertrand & Joëts, Marc & Tokpavi, Sessi, 2013. "Testing for Granger causality in distribution tails: An application to oil markets integration," Economic Modelling, Elsevier, vol. 31(C), pages 276-285.
    21. Weiner, R.J., 1991. "Is the World Oil Market "One Great Pool?"," Papers 9120, Laval - Recherche en Energie.
    22. Hao, Xiaoqing & An, Haizhong & Qi, Hai & Gao, Xiangyun, 2016. "Evolution of the exergy flow network embodied in the global fossil energy trade: Based on complex network," Applied Energy, Elsevier, vol. 162(C), pages 1515-1522.
    23. Fattouh, Bassam, 2010. "The dynamics of crude oil price differentials," Energy Economics, Elsevier, vol. 32(2), pages 334-342, March.
    24. James D. Hamilton, 2009. "Understanding Crude Oil Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 179-206.
    25. Robert J. Weiner, 1991. "Is the World Oil Market "One Great Pool"?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 95-108.
    26. Bhar, Ramaprasad & Hammoudeh, Shawkat & Thompson, Mark A., 2008. "Component structure for nonstationary time series: Application to benchmark oil prices," International Review of Financial Analysis, Elsevier, vol. 17(5), pages 971-983, December.
    27. Narayan, Paresh Kumar & Narayan, Seema & Popp, Stephan, 2011. "Investigating price clustering in the oil futures market," Applied Energy, Elsevier, vol. 88(1), pages 397-402, January.
    28. Patrick Crowley, 2005. "An intuitive guide to wavelets for economists," Econometrics 0503017, University Library of Munich, Germany.
    29. Ju, Keyi & Zhou, Dequn & Zhou, P. & Wu, Junmin, 2014. "Macroeconomic effects of oil price shocks in China: An empirical study based on Hilbert–Huang transform and event study," Applied Energy, Elsevier, vol. 136(C), pages 1053-1066.
    30. Ramsey, James B. & Lampart, Camille, 1998. "Decomposition Of Economic Relationships By Timescale Using Wavelets," Macroeconomic Dynamics, Cambridge University Press, vol. 2(1), pages 49-71, March.
    31. Ali Ahmed, Huson Joher & Bashar, Omar H.M.N. & Wadud, I.K.M. Mokhtarul, 2012. "The transitory and permanent volatility of oil prices: What implications are there for the US industrial production?," Applied Energy, Elsevier, vol. 92(C), pages 447-455.
    32. An, Haizhong & Zhong, Weiqiong & Chen, Yurong & Li, Huajiao & Gao, Xiangyun, 2014. "Features and evolution of international crude oil trade relationships: A trading-based network analysis," Energy, Elsevier, vol. 74(C), pages 254-259.
    33. repec:zbw:bofrdp:2010_006 is not listed on IDEAS
    34. Reboredo, Juan C. & Rivera-Castro, Miguel A., 2014. "Wavelet-based evidence of the impact of oil prices on stock returns," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 145-176.
    35. Gencay, Ramazan & Selcuk, Faruk & Whitcher, Brandon, 2005. "Multiscale systematic risk," Journal of International Money and Finance, Elsevier, vol. 24(1), pages 55-70, February.
    36. Maslyuk, Svetlana & Smyth, Russell, 2009. "Cointegration between oil spot and future prices of the same and different grades in the presence of structural change," Energy Policy, Elsevier, vol. 37(5), pages 1687-1693, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jia, Xiaoliang & An, Haizhong & Fang, Wei & Sun, Xiaoqi & Huang, Xuan, 2015. "How do correlations of crude oil prices co-move? A grey correlation-based wavelet perspective," Energy Economics, Elsevier, vol. 49(C), pages 588-598.
    2. Jia, Xiaoliang & An, Haizhong & Sun, Xiaoqi & Huang, Xuan & Gao, Xiangyun, 2016. "Finding the multipath propagation of multivariable crude oil prices using a wavelet-based network approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 331-344.
    3. Kuck, Konstantin & Schweikert, Karsten, 2017. "A Markov regime-switching model of crude oil market integration," Journal of Commodity Markets, Elsevier, vol. 6(C), pages 16-31.
    4. Duan, Kun & Ren, Xiaohang & Wen, Fenghua & Chen, Jinyu, 2023. "Evolution of the information transmission between Chinese and international oil markets: A quantile-based framework," Journal of Commodity Markets, Elsevier, vol. 29(C).
    5. Liu, Li & Chen, Ching-Cheng & Wan, Jieqiu, 2013. "Is world oil market “one great pool”?: An example from China's and international oil markets," Economic Modelling, Elsevier, vol. 35(C), pages 364-373.
    6. 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.
    7. Zhang, Qi & Di, Peng & Farnoosh, Arash, 2021. "Study on the impacts of Shanghai crude oil futures on global oil market and oil industry based on VECM and DAG models," Energy, Elsevier, vol. 223(C).
    8. Yu, Hui & Ding, Yinghui & Sun, Qingru & Gao, Xiangyun & Jia, Xiaoliang & Wang, Xinya & Guo, Sui, 2021. "Multi-scale comovement of the dynamic correlations between copper futures and spot prices," Resources Policy, Elsevier, vol. 70(C).
    9. Niyati Bhanja & Samia Nasreen & Arif Billah Dar & Aviral Kumar Tiwari, 2022. "Connectedness in International Crude Oil Markets," Computational Economics, Springer;Society for Computational Economics, vol. 59(1), pages 227-262, January.
    10. Jiasha Fu & Hui Qiao, 2022. "The Time-Varying Connectedness Between China’s Crude Oil Futures and International Oil Markets: A Return and Volatility Spillover Analysis," Letters in Spatial and Resource Sciences, Springer, vol. 15(3), pages 341-376, December.
    11. Atanu Ghoshray and Tatiana Trifonova, 2014. "Dynamic Adjustment of Crude Oil Price Spreads," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    12. 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.
    13. Bravo Caro, José Manuel & Golpe, Antonio A. & Iglesias, Jesús & Vides, José Carlos, 2020. "A new way of measuring the WTI – Brent spread. Globalization, shock persistence and common trends," Energy Economics, Elsevier, vol. 85(C).
    14. Cui, Jinxin & Maghyereh, Aktham, 2023. "Time-frequency dependence and connectedness among global oil markets: Fresh evidence from higher-order moment perspective," Journal of Commodity Markets, Elsevier, vol. 30(C).
    15. Huang, Shupei & An, Haizhong & Gao, Xiangyun & Wen, Shaobo & Jia, Xiaoliang, 2016. "The global interdependence among oil-equity nexuses," Energy, Elsevier, vol. 107(C), pages 259-271.
    16. Niyati Bhanja & Arif Billah Dar & Aviral Kumar Tiwari, 2018. "Do Global Crude Oil Markets Behave as One Great Pool? A Cyclical Analysis," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(2), pages 219-241, November.
    17. Ftiti, Zied & Guesmi, Khaled & Abid, Ilyes, 2016. "Oil price and stock market co-movement: What can we learn from time-scale approaches?," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 266-280.
    18. Bertrand Candelon & Marc Joëts & Sessi Tokpavi, 2012. "Testing for crude oil markets globalization during extreme price movements," EconomiX Working Papers 2012-28, University of Paris Nanterre, EconomiX.
    19. Ayman Omar, 2015. "West Texas Intermediate and Brent Spread during Organization of the Petroleum Exporting Countries Supply Disruptions," International Journal of Energy Economics and Policy, Econjournals, vol. 5(3), pages 693-703.
    20. Reboredo, Juan C., 2011. "How do crude oil prices co-move?: A copula approach," Energy Economics, Elsevier, vol. 33(5), pages 948-955, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:185:y:2017:i:p2:p:1788-1798. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.