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Information transmission among multiple investors: a micro-perspective revealed by motifs

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Abstract

The concept of motifs provides a new perspective for studying local patterns, which is useful for understanding the nature of a network structure. In this study, the types and evolution of the motifs of the shareholder co-ownership network, constructed based on common shareholding data from 2007 to 2017, are explored from a micro-perspective. Although with a low proportion, the closed motifs were found to be important motifs with statistical significance in the network. Furthermore, the motifs containing financial investment company shareholders tend to disappear on both short (quarterly) and long (annual) time scales. In contrast, the motifs containing general corporate shareholders tend to remain unchanged. Finally, the abnormal abrupt changes in the proportions of important motifs in the real network relative to the random network before and after the financial crisis are calculated. The number of Motif 4 containing state-owned companies, general companies, and individual investors decreases abnormally during the financial crisis. This research is of great significance for understanding information interaction among multiple investors.

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Notes

  1. Lifting the sedan chair, a proprietary term in the stock market, refers to the fact that the buyer anticipates that a certain stock will rise, and therefore buys a large amount of stock, which leads to an increase in the stock price. But the result is that other people (generally referred to as the banker) sell at a high position and make a profit, and eventually the buyer is locked up.

  2. The 3-node motif structure is the most common subgraph form in the network [7]. If the number of nodes is less than 3, there are too few subgraph types, which is not conducive to mining local information of the network. If there are too many nodes, the number of possible motif structures increases exponentially, which increases the complexity of motif recognition. At the same time, the motif structure of more than 4 nodes can be generated by the superposition and combination of different 3-node motif structures. In a word, the 3-node motif structure can satisfy the mining of local features of the network. The "motif structure" in this study refers to the "3-node motif structure" unless otherwise specified.

  3. The important motif structure is a subset of the motif structure, which refers to the motif structure whose proportion in the real network is significantly higher than that in the random network.

  4. As of the end of 2006, 1301 companies had completed the split share reform, accounting for 97% of the total number of listed companies. In order to exclude the influence of shareholder structure and equity nature on the results, the starting point of the data in this paper is the first quarter of 2007.

  5. The CSI 300 index consists of 300 of the largest and most liquid A-shares. The index is designed to reflect the overall performance of China’s A-share market.

  6. The number of random network in this paper is 1000.

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Acknowledgements

This article is funded by the National Natural Science Foundation of China (U1811462, 71771170, 71790594), Youth Foundation for Humanities and Social Sciences Research of the Ministry of Education (20YJC790062), Open Project of Jiangsu Key Laboratory of Financial Engineering (NSK2021-18), Jiangsu Planning Office of Philosophy and Social Science (20GLC007) and the Applied Economics of Nan**g Audit University of the Priority Academic Program Development Phase III of Jiangsu Higher Education Institutions (Office of Jiangsu Provincial People’s Government, No. [2018]87).

Funding

This article is funded by the National Natural Science Foundation of China (U1811462, 71771170, 71790594), Youth Foundation for Humanities and Social Sciences Research of the Ministry of Education (20YJC790062), Open Project of Jiangsu Key Laboratory of Financial Engineering (NSK2021-18), Jiangsu Planning Office of Philosophy and Social Science (20GLC007) and the Applied Economics of Nan**g Audit University of the Priority Academic Program. Development Phase III of Jiangsu Higher Education Institutions (Office of Jiangsu Provincial People’s Government, No. [2018]87).

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Authors and Affiliations

  1. School of Finance, Nan**g Audit University, Nan**g, 211815, Jiangsu, China

    Jie Li

  2. Key Laboratory of Financial Engineering, Nan**g Audit University, Nan**g, 211815, Jiangsu, China

    Jie Li

  3. College of Management and Economics, Tian** University, Tian**, 300072, China

    Yongjie Zhang

  4. School of Government Audit, Nan**g Audit University, Nan**g, 211815, Jiangsu, China

    Lidan Wang

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  1. Jie Li
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Correspondence to Lidan Wang.

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Li, J., Zhang, Y. & Wang, L. Information transmission among multiple investors: a micro-perspective revealed by motifs. Nonlinear Dyn 108, 2833–2850 (2022). https://doi.org/10.1007/s11071-022-07307-8

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