Information Connections among Multiple Investors: Evolutionary Local Patterns Revealed by Motifs
| العنوان: | Information Connections among Multiple Investors: Evolutionary Local Patterns Revealed by Motifs |
|---|---|
| المؤلفون: | Haizhong An, Nairong Liu, Qing Guan, Feng An, Meihui Jiang |
| المصدر: | Scientific Reports, Vol 7, Iss 1, Pp 1-13 (2017) Scientific Reports |
| بيانات النشر: | Nature Publishing Group, 2017. |
| سنة النشر: | 2017 |
| مصطلحات موضوعية: | 050208 finance, Multidisciplinary, business.industry, 05 social sciences, lcsh:R, Network structure, lcsh:Medicine, Machine learning, computer.software_genre, 01 natural sciences, Article, Homophily, Microeconomics, Shareholder, 0502 economics and business, 0103 physical sciences, lcsh:Q, Artificial intelligence, 010306 general physics, business, lcsh:Science, computer, Stock (geology) |
| الوصف: | 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. |
| اللغة: | English |
| تدمد: | 2045-2322 |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2754f656bdd68966451ec3bf54b386e7Test http://link.springer.com/article/10.1038/s41598-017-14141-1Test |
| حقوق: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....2754f656bdd68966451ec3bf54b386e7 |
| قاعدة البيانات: | OpenAIRE |
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