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The influence of social network structure on stock price disclosure

Author

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  • Wang, Zhaoyuan
  • Liu, Shancun
  • Yang, Haijun

Abstract

We propose a new heterogeneous agent model of a dynamic continuous double auction stock market embedding multiple social network to investigate the influence of different network structures on stock price disclosure. According to the four network formation algorithms (preferential connection, random connection, weighted random connection and random reconnection), we construct scale-free random network, weighted random network and small-world network respectively. We find that the small-world characteristic of social network speed up the diffusion of private information in market, and then improve market efficiency and promote price discovery. Furthermore, to some extent, simulation results indicate that the network structure can explain the occurrence of anomalies like underreaction and overreaction in the financial market.

Suggested Citation

  • Wang, Zhaoyuan & Liu, Shancun & Yang, Haijun, 2019. "The influence of social network structure on stock price disclosure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 533(C).
    • Handle: RePEc:eee:phsmap:v:533:y:2019:i:c:s0378437119311653
    DOI: 10.1016/j.physa.2019.122064
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    Citations

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    Cited by:

    1. Rocco Caferra & Gabriele Tedeschi & Andrea Morone, 2023. "Agents interaction and price dynamics: evidence from the laboratory," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(2), pages 251-274, April.
    2. Claudine Salgado & Guilherme Schneider & Cristiano M. Costa, 2022. "Does board interlock affect CEO compensation? Evidence from companies listed in the Brazilian stock exchange," International Journal of Disclosure and Governance, Palgrave Macmillan, vol. 19(4), pages 444-465, December.

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