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Information networks in the stock market based on the distance of the multi-attribute dimensions between listed companies

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  • Liu, Qian
  • Li, Huajiao
  • Liu, Xueyong
  • Jiang, Meihui

Abstract

In the stock market, there are widespread information connections between economic agents. Listed companies can obtain mutual information about investment decisions from common shareholders, and the extent of sharing information often determines the relationships between listed companies. Because different shareholder compositions and investment shares lead to different formations of the company’s governance mechanisms, we map the investment relationships between shareholders to the multi-attribute dimensional spaces of the listed companies (each shareholder investment in a company is a company dimension). Then, we construct the listed company’s information network based on co-shareholder relationships. The weights for the edges in the information network are measured with the Euclidean distance between the listed companies in the multi-attribute dimension space. We define two indices to analyze the information network’s features. We conduct an empirical study that analyzes Chinese listed companies’ information networks. The results from the analysis show that with the diversification and decentralization of shareholder investments, almost all Chinese listed companies exchanged information through common shareholder relationships, and there is a gradual reduction in information sharing capacity between listed companies that have common shareholders. This network analysis has benefits for risk management and portfolio investments.

Suggested Citation

  • Liu, Qian & Li, Huajiao & Liu, Xueyong & Jiang, Meihui, 2018. "Information networks in the stock market based on the distance of the multi-attribute dimensions between listed companies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 505-513.
    • Handle: RePEc:eee:phsmap:v:496:y:2018:i:c:p:505-513
    DOI: 10.1016/j.physa.2017.12.134
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    References listed on IDEAS

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    Cited by:

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