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

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....

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Autores principales: Guan, Qing, An, Haizhong, Liu, Nairong, An, Feng, Jiang, Meihui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5656643/
https://www.ncbi.nlm.nih.gov/pubmed/29070827
http://dx.doi.org/10.1038/s41598-017-14141-1
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author Guan, Qing
An, Haizhong
Liu, Nairong
An, Feng
Jiang, Meihui
author_facet Guan, Qing
An, Haizhong
Liu, Nairong
An, Feng
Jiang, Meihui
author_sort Guan, Qing
collection PubMed
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.
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spelling pubmed-56566432017-10-31 Information Connections among Multiple Investors: Evolutionary Local Patterns Revealed by Motifs Guan, Qing An, Haizhong Liu, Nairong An, Feng Jiang, Meihui Sci Rep Article 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. Nature Publishing Group UK 2017-10-25 /pmc/articles/PMC5656643/ /pubmed/29070827 http://dx.doi.org/10.1038/s41598-017-14141-1 Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Guan, Qing
An, Haizhong
Liu, Nairong
An, Feng
Jiang, Meihui
Information Connections among Multiple Investors: Evolutionary Local Patterns Revealed by Motifs
title Information Connections among Multiple Investors: Evolutionary Local Patterns Revealed by Motifs
title_full Information Connections among Multiple Investors: Evolutionary Local Patterns Revealed by Motifs
title_fullStr Information Connections among Multiple Investors: Evolutionary Local Patterns Revealed by Motifs
title_full_unstemmed Information Connections among Multiple Investors: Evolutionary Local Patterns Revealed by Motifs
title_short Information Connections among Multiple Investors: Evolutionary Local Patterns Revealed by Motifs
title_sort information connections among multiple investors: evolutionary local patterns revealed by motifs
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5656643/
https://www.ncbi.nlm.nih.gov/pubmed/29070827
http://dx.doi.org/10.1038/s41598-017-14141-1
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