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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

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  • Li, Huajiao
  • An, Haizhong
  • Huang, Jiachen
  • Huang, Xuan
  • Mou, Songtao
  • Shi, Yanli

Abstract

Listed energy companies play an important role in both the energy financial market and energy commodity market. As owners of listed energy companies, shareholders can influence the stability of the energy stock market by increasing or decreasing their holdings. To analyze the evolutionary features and stability of shareholders’ co-holding behavior, we constructed a derivative holding-based structural equivalence network of the shareholders (holding-based network) based on the primitive shareholding network of the listed companies and their shareholders. The main data used in this paper are the semi-annual reports from 2003 to 2012 that contain information about Chinese listed energy companies’ top 10 shareholders. The holding-based network takes the shareholders as nodes, whether holding the same listed energy companies’ stock at the same time as the edges, and the number of listed energy companies co-held as the weights. Due to the unique topological features of the holding-based network, we improved the Heuristic Algorithm to find the associated maximal connected sub-graph of the network, which is the main group of shareholders with shareholding consistency of the listed energy companies. This paper creates a new approach to analyze the relationships in the energy stock market, presenting a new method to analyze shareholder behavior.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:appene:v:162:y:2016:i:c:p:1601-1607
    DOI: 10.1016/j.apenergy.2015.04.049
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    4. An, Feng & Gao, Xiangyun & Guan, Jianhe & Huang, Shupei & Liu, Qian, 2017. "Modeling the interdependent network based on two-mode networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 57-67.
    5. Sui, Guo & Li, Huajiao & Feng, Sida & Liu, Xueyong & Jiang, Meihui, 2018. "Correlations of stock price fluctuations under multi-scale and multi-threshold scenarios," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1501-1512.
    6. Lu, Shuai & Li, Shouwei & Zhou, Wei & Yang, Wenke, 2022. "Network herding of energy funds in the post-Carbon-Peak Policy era: Does it benefit profitability and stability?," Energy Economics, Elsevier, vol. 109(C).
    7. 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).
    8. Qing Yao & Tim S Evans & Kim Christensen, 2019. "How the network properties of shareholders vary with investor type and country," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-19, August.
    9. Liu, Xueyong & An, Haizhong & Huang, Shupei & Wen, Shaobo, 2017. "The evolution of spillover effects between oil and stock markets across multi-scales using a wavelet-based GARCH–BEKK model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 374-383.
    10. An, Pengli & Li, Huajiao & Zhou, Jinsheng & Li, Yang & Sun, Bowen & Guo, Sui & Qi, Yajie, 2020. "Volatility spillover of energy stocks in different periods and clusters based on structural break recognition and network method," Energy, Elsevier, vol. 191(C).
    11. Huang, Chuangxia & Zhao, Xian & Deng, Yunke & Yang, Xiaoguang & Yang, Xin, 2022. "Evaluating influential nodes for the Chinese energy stocks based on jump volatility spillover network," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 81-94.
    12. Liu, Xueyong & An, Haizhong & Li, Huajiao & Chen, Zhihua & Feng, Sida & Wen, Shaobo, 2017. "Features of spillover networks in international financial markets: Evidence from the G20 countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 265-278.
    13. 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.
    14. 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).
    15. An, Pengli & Zhou, Jinsheng & Li, Huajiao & Sun, Bowen & Shi, Yanli, 2018. "The evolutionary similarity of the co-shareholder relationship network from institutional and non-institutional shareholder perspectives," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 439-450.

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