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Information Connections among Multiple Investors: Evolutionary Local Patterns Revealed by Motifs

Scientific reports, 2017-10, Vol.7 (1), p.14034-13, Article 14034 [Peer Reviewed Journal]

2017. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2017 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-017-14141-1 ;PMID: 29070827

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  • Title:
    Information Connections among Multiple Investors: Evolutionary Local Patterns Revealed by Motifs
  • Author: Guan, Qing ; An, Haizhong ; Liu, Nairong ; An, Feng ; Jiang, Meihui
  • Subjects: Evolution ; GENERAL AND MISCELLANEOUS ; Investments ; Science & Technology - Other Topics ; Securities markets ; Stock exchanges ; Stockholders
  • Is Part Of: Scientific reports, 2017-10, Vol.7 (1), p.14034-13, Article 14034
  • Description: The concept of motifs provides a fresh perspective for studying local patterns, which is useful for understanding the essence of a network structure. However, few previous studies have focused on the evolutionary characteristics of weighted motifs while further considering participants' differences. We study how information connections differ among multiple investors. The evolutionary 10-year trend of weighted 3-motifs in China's energy stock markets is explored for the networks of co-holding behaviors among shareholders, who are classified as companies, funds and individuals. Our works allow us to detect the preferential local patterns distributed among different agents as their fluctuate involvement in networks. We find that the diversity of shareholders contributes to the statistical significance of local patterns, while homophily always exist among individuals. Modules of information connections are stable among reserved investors, which is especially apparent among companies. Individuals prefer to keep their connections with companies and funds. Unsteady modules happen owing to strengthen links among funds during the time that they are main participants in stock markets. More details about multiple investors informationally connected in evolutionary local patterns can be detected by our work.
  • Publisher: England: Nature Publishing Group
  • Language: English
  • Identifier: ISSN: 2045-2322
    EISSN: 2045-2322
    DOI: 10.1038/s41598-017-14141-1
    PMID: 29070827
  • Source: PubMed Central
    ProQuest Central
    DOAJ Directory of Open Access Journals
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