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Institutional investor information network, analyst forecasting and stock price crash risk

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  • Gong, Xiao-Li
  • Liu, Jia

Abstract

In this paper, we construct the information network of fund investors based on the theory of social relationship networks and examine its impact of fund information sharing with analysts on stock price crash risk. Our results show that private information sharing among institutional investors reduces crash risk. Further results show that fund information sharing can alleviate analyst optimism bias and improve analyst forecast accuracy, which further reduces stock price crash risk. Moreover, these identified effects are more pronounced in a bull market than a bear market. Our study contributes to the research on private information transmission in fund information networks, and provides a new perspective for recognizing the relationships among institutional investor behavior, analyst forecasting, and stock price crash risk.

Suggested Citation

  • Gong, Xiao-Li & Liu, Jia, 2023. "Institutional investor information network, analyst forecasting and stock price crash risk," Research in International Business and Finance, Elsevier, vol. 65(C).
    • Handle: RePEc:eee:riibaf:v:65:y:2023:i:c:s0275531923000685
    DOI: 10.1016/j.ribaf.2023.101942
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    Cited by:

    1. Li, Jie & Zhou, Zhong-Qiang & Zhang, Yongjie & Xiong, Xiong, 2023. "Information interaction among institutional investors and stock price crash risk based on multiplex networks," International Review of Financial Analysis, Elsevier, vol. 89(C).
    2. Wang, Bin & Luo, Yan, 2024. "Institutional investors, heterogeneity, and capital structure decisions: Evidence from an emerging market," Research in International Business and Finance, Elsevier, vol. 68(C).

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