IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v194y2017icp648-657.html
   My bibliography  Save this article

Global energy investment structure from the energy stock market perspective based on a Heterogeneous Complex Network Model

Author

Listed:
  • Li, Huajiao
  • An, Haizhong
  • Fang, Wei
  • Wang, Yue
  • Zhong, Weiqiong
  • Yan, Lili

Abstract

Energy is not only an important international commodity but is also an important financial product. Many studies address the global energy structure by considering energy as commodity, but few study it based on energy’s financial attributes. In this paper, we analyzed the global energy investment structure based on the shareholding relationships between listed energy companies and their shareholders by taking the frontier approach to complex network theory and treating these relationships as a heterogeneous complex network from a global angle. We constructed a primitive investment network of listed energy companies and their shareholders (two sets of actors). Then, based on the two-mode affiliation relationships between two sets of actors and countries, we constructed a derivative investment network of 112 countries (and regions). By calculating different topological features, we quantitatively analyzed the national diversity of outward and inward energy investment, the energy investment preference, the strength of the bilateral energy investment relationship between countries (and regions) and the most powerful group of energy investing countries based on the shareholding relationships of global listed energy companies. It is found that the vast majority of outward and inward investment relationships are still in the hands of a few countries: traditional developed countries, emerging countries, and a few particular island countries (and regions) that are tax havens. This study is helpful for analyzing the roles and investment relationships of nations as well as the global energy investment structure taking the perspective of the energy stock market.

Suggested Citation

  • Li, Huajiao & An, Haizhong & Fang, Wei & Wang, Yue & Zhong, Weiqiong & Yan, Lili, 2017. "Global energy investment structure from the energy stock market perspective based on a Heterogeneous Complex Network Model," Applied Energy, Elsevier, vol. 194(C), pages 648-657.
    • Handle: RePEc:eee:appene:v:194:y:2017:i:c:p:648-657
    DOI: 10.1016/j.apenergy.2016.05.062
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261916306596
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2016.05.062?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. Norman Mohd Saleh & Mara Ridhuan Che Abdul Rahman & Mohamat Sabri Hassan, 2009. "Ownership Structure and Intellectual Capital Performance in Malaysia," Asian Academy of Management Journal of Accounting and Finance (AAMJAF), Penerbit Universiti Sains Malaysia, vol. 5(1), pages 1-29.
    2. Appels, Lise & Lauwers, Joost & Degrève, Jan & Helsen, Lieve & Lievens, Bart & Willems, Kris & Van Impe, Jan & Dewil, Raf, 2011. "Anaerobic digestion in global bio-energy production: Potential and research challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4295-4301.
    3. Liliana Bunescu, 2008. "What Tax Havens Are?," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 3(3), pages 10-13, October.
    4. 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.
    5. Zhang, Hai-Ying & Ji, Qiang & Fan, Ying, 2014. "Competition, transmission and pattern evolution: A network analysis of global oil trade," Energy Policy, Elsevier, vol. 73(C), pages 312-322.
    6. Geng, Jiang-Bo & Ji, Qiang & Fan, Ying, 2014. "A dynamic analysis on global natural gas trade network," Applied Energy, Elsevier, vol. 132(C), pages 23-33.
    7. Li, Huajiao & An, Haizhong & Gao, Xiangyun & Huang, Jiachen & Xu, Qun, 2014. "On the topological properties of the cross-shareholding networks of listed companies in China: Taking shareholders’ cross-shareholding relationships into account," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 80-88.
    8. Takeshita, Takayuki, 2011. "Competitiveness, role, and impact of microalgal biodiesel in the global energy future," Applied Energy, Elsevier, vol. 88(10), pages 3481-3491.
    9. Li, Huajiao & An, Haizhong & Wang, Yue & Huang, Jiachen & Gao, Xiangyun, 2016. "Evolutionary features of academic articles co-keyword network and keywords co-occurrence network: Based on two-mode affiliation network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 657-669.
    10. 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.
    11. Jiang, Zhi-Qiang & Zhou, Wei-Xing, 2010. "Complex stock trading network among investors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4929-4941.
    12. Balat, Mustafa & Balat, Havva, 2009. "Recent trends in global production and utilization of bio-ethanol fuel," Applied Energy, Elsevier, vol. 86(11), pages 2273-2282, November.
    13. Zhang, Hai-Ying & Ji, Qiang & Fan, Ying, 2013. "An evaluation framework for oil import security based on the supply chain with a case study focused on China," Energy Economics, Elsevier, vol. 38(C), pages 87-95.
    14. 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.
    15. Saguan, Marcelo & Meeus, Leonardo, 2014. "Impact of the regulatory framework for transmission investments on the cost of renewable energy in the EU," Energy Economics, Elsevier, vol. 43(C), pages 185-194.
    16. Yang, Jin & Chen, Bin, 2014. "Global warming impact assessment of a crop residue gasification project—A dynamic LCA perspective," Applied Energy, Elsevier, vol. 122(C), pages 269-279.
    17. Ferreira Neto, Amir B. & Perobelli, Fernando S. & Bastos, Suzana Q.A., 2014. "Comparing energy use structures: An input–output decomposition analysis of large economies," Energy Economics, Elsevier, vol. 43(C), pages 102-113.
    18. Guo, Z.C. & Fu, Z.X., 2010. "Current situation of energy consumption and measures taken for energy saving in the iron and steel industry in China," Energy, Elsevier, vol. 35(11), pages 4356-4360.
    19. Chen, Shaoqing & Chen, Bin, 2015. "Urban energy consumption: Different insights from energy flow analysis, input–output analysis and ecological network analysis," Applied Energy, Elsevier, vol. 138(C), pages 99-107.
    20. Li, Huajiao & Fang, Wei & An, Haizhong & Yan, LiLi, 2014. "The shareholding similarity of the shareholders of the worldwide listed energy companies based on a two-mode primitive network and a one-mode derivative holding-based network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 525-532.
    21. Dhammika Dharmapala, 2008. "What problems and opportunities are created by tax havens?," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 24(4), pages 661-679, winter.
    22. Cunado, Juncal & Perez de Gracia, Fernando, 2014. "Oil price shocks and stock market returns: Evidence for some European countries," Energy Economics, Elsevier, vol. 42(C), pages 365-377.
    23. 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.
    24. Sun, Xiaolei & Li, Jianping & Wang, Yongfeng & Clark, Woodrow W., 2014. "China's Sovereign Wealth Fund Investments in overseas energy: The energy security perspective," Energy Policy, Elsevier, vol. 65(C), pages 654-661.
    25. Li, Huajiao & An, Haizhong & Huang, Jiachen & Huang, Xuan & Mou, Songtao & Shi, Yanli, 2016. "The evolutionary stability of shareholders’ co-holding behavior for China’s listed energy companies based on associated maximal connected sub-graphs of derivative holding-based networks," Applied Energy, Elsevier, vol. 162(C), pages 1601-1607.
    26. Montes, Germán Martínez & Prados Martín, Enrique & Ordóñez García, Javier, 2007. "The current situation of wind energy in Spain," Renewable and Sustainable Energy Reviews, Elsevier, vol. 11(3), pages 467-481, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Muzi Chen & Yuhang Wang & Boyao Wu & Difang Huang, 2024. "Dynamic Analyses of Contagion Risk and Module Evolution on the SSE A-Shares Market Based on Minimum Information Entropy," Papers 2403.19439, arXiv.org.
    2. Zhang, Peipei & Sun, Mei & Zhang, Xiaoling & Gao, Cuixia, 2017. "Who are leading the change? The impact of China’s leading PV enterprises: A complex network analysis," Applied Energy, Elsevier, vol. 207(C), pages 477-493.
    3. Rudkovskyy Serhii, 2020. "The influence of the investment factor on the transformation of the global energy market," Technology audit and production reserves, Socionet;Technology audit and production reserves, vol. 4(4(54)), pages 23-29.
    4. Liu, Wei & Ma, Qianting & Liu, Xiaoxing, 2022. "Research on the dynamic evolution and its influencing factors of stock correlation network in the Chinese new energy market," Finance Research Letters, Elsevier, vol. 45(C).
    5. Li, Huajiao & Ren, Huijun & An, Haizhong & Ma, Ning & Yan, Lili, 2021. "Multiplex cross-shareholding relations in the global oil & gas industry chain based on multilayer network modeling," Energy Economics, Elsevier, vol. 95(C).
    6. Feng, Chao & Liu, Yu-Qi & Yang, Jun, 2024. "Do energy trade patterns affect renewable energy development? The threshold role of digital economy and economic freedom," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    7. Chen, Wei & Qu, Shuai & Jiang, Manrui & Jiang, Cheng, 2021. "The construction of multilayer stock network model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    8. Zhu, Bo & Deng, Yuanyue & Lin, Renda & Hu, Xin & Chen, Pingshe, 2022. "Energy security: Does systemic risk spillover matter? Evidence from China," Energy Economics, Elsevier, vol. 114(C).
    9. Quan He & Xishen Cao, 2019. "Pattern and Influencing Factors of Foreign Direct Investment Networks between Countries along the “Belt and Road” Regions," Sustainability, MDPI, vol. 11(17), pages 1-23, August.
    10. Chao Zhou & Dongyu Liu & Pengfei Zhou & Jie Luo & Serhat Yuksel & Hasan Dincer, 2020. "Hybrid Predictive Decision-Making Approach to Emission Reduction Policies for Sustainable Energy Industry," Energies, MDPI, vol. 13(9), pages 1-21, May.
    11. Guan, Qing & An, Haizhong, 2017. "The exploration on the trade preferences of cooperation partners in four energy commodities’ international trade: Crude oil, coal, natural gas and photovoltaic," Applied Energy, Elsevier, vol. 203(C), pages 154-163.

    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. Li, Huajiao & Fang, Wei & An, Haizhong & Gao, Xiangyun & Yan, Lili, 2016. "Holding-based network of nations based on listed energy companies: An empirical study on two-mode affiliation network of two sets of actors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 224-232.
    2. Li, Huajiao & An, Haizhong & Liu, Xueyong & Gao, Xiangyun & Fang, Wei & An, Feng, 2016. "Price fluctuation in the energy stock market based on fluctuation and co-fluctuation matrix transmission networks," Energy, Elsevier, vol. 117(P1), pages 73-83.
    3. Li, Huajiao & An, Haizhong & Huang, Jiachen & Huang, Xuan & Mou, Songtao & Shi, Yanli, 2016. "The evolutionary stability of shareholders’ co-holding behavior for China’s listed energy companies based on associated maximal connected sub-graphs of derivative holding-based networks," Applied Energy, Elsevier, vol. 162(C), pages 1601-1607.
    4. Xi, Xian & Zhou, Jinsheng & Gao, Xiangyun & Liu, Donghui & Zheng, Huiling & Sun, Qingru, 2019. "Impact of changes in crude oil trade network patterns on national economy," Energy Economics, Elsevier, vol. 84(C).
    5. Zhu, Zhiyun & Dong, Zhiliang & Zhang, Yanxing & Suo, Guibin & Liu, Sen, 2020. "Strategic mineral resource competition: Strategies of the dominator and nondominator," Resources Policy, Elsevier, vol. 69(C).
    6. Sun, Qingru & Gao, Xiangyun & Zhong, Weiqiong & Liu, Nairong, 2017. "The stability of the international oil trade network from short-term and long-term perspectives," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 345-356.
    7. An, Qier & An, Haizhong & Wang, Lang & Gao, Xiangyun & Lv, Na, 2015. "Analysis of embodied exergy flow between Chinese industries based on network theory," Ecological Modelling, Elsevier, vol. 318(C), pages 26-35.
    8. An, Pengli & Li, Huajiao & Zhou, Jinsheng & Chen, Fan, 2017. "The evolution analysis of listed companies co-holding non-listed financial companies based on two-mode heterogeneous networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 558-568.
    9. 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.
    10. Kitamura, Toshihiko & Managi, Shunsuke, 2017. "Driving force and resistance: Network feature in oil trade," Applied Energy, Elsevier, vol. 208(C), pages 361-375.
    11. Sun, Bowen & Li, Huajiao & An, Pengli & Wang, Ze, 2020. "Dynamic energy stock selection based on shareholders’ coholding network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    12. Huan Chen & Lixin Tian & Minggang Wang & Zaili Zhen, 2017. "Analysis of the Dynamic Evolutionary Behavior of American Heating Oil Spot and Futures Price Fluctuation Networks," Sustainability, MDPI, vol. 9(4), pages 1-29, April.
    13. Li, Xiaotong & Zhang, Hua & Zhou, Xuanru & Zhong, Weiqiong, 2022. "Research on the evolution of the global import and export competition network of chromium resources from the perspective of the whole industrial chain," Resources Policy, Elsevier, vol. 79(C).
    14. Mobeen Ur Rehman, 2020. "Dynamic correlation pattern amongst alternative energy market for diversification opportunities," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 9(1), pages 1-24, December.
    15. Gao, Cuixia & Sun, Mei & Shen, Bo, 2015. "Features and evolution of international fossil energy trade relationships: A weighted multilayer network analysis," Applied Energy, Elsevier, vol. 156(C), pages 542-554.
    16. 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.
    17. Hao, Xiaoqing, 2023. "Import competition and pressure in the international crude oil trade: A network analysis," Resources Policy, Elsevier, vol. 82(C).
    18. Arif, Asma & An, Pengli & Qi, Yajie & Li, Huajiao & An, Haizhong & Hussain, Mujahid & Wang, Yanli, 2021. "The influence factors of the national roles in the FDI network: A combined methods of complex networks and Panel Data Analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    19. Ruijin Du & Gaogao Dong & Lixin Tian & Minggang Wang & Guochang Fang & Shuai Shao, 2016. "Spatiotemporal Dynamics and Fitness Analysis of Global Oil Market: Based on Complex Network," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-17, October.
    20. Cai, Xiaomei & Liu, Chan & Zheng, Shuxian & Hu, Han & Tan, Zhanglu, 2023. "Analysis on the evolution characteristics of barite international trade pattern based on complex networks," Resources Policy, Elsevier, vol. 83(C).

    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:194:y:2017:i:c:p:648-657. 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.