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Investor network: Implications for information diffusion and asset prices

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  • Chung, San-Lin
  • Liu, Wenchien
  • Liu, Wen-Rang
  • Tseng, Kevin

Abstract

In this study, we examine the information diffusion of firms in investor networks. Using a unique investor account-level dataset from the Taiwan Stock Exchange from 2005 to 2014, we identify the information diffusion of firms as their centralization in investor networks. Consistent with the theory of investor information networks, we find that central investors trade earlier and are more profitable than peripheral investors. Furthermore, they have greater access to superior, private information based on actual M&A events. More importantly, we find that centralized firms (i.e., firms with more central investors' networks) experience less delay in prices, and therefore demand lower price delay premiums than peripheral firms. These results suggest that investor networks speed up the incorporation of new information into asset prices, and cause the strength of information diffusion to have a great impact on stock returns.

Suggested Citation

  • Chung, San-Lin & Liu, Wenchien & Liu, Wen-Rang & Tseng, Kevin, 2018. "Investor network: Implications for information diffusion and asset prices," Pacific-Basin Finance Journal, Elsevier, vol. 48(C), pages 186-209.
  • Handle: RePEc:eee:pacfin:v:48:y:2018:i:c:p:186-209
    DOI: 10.1016/j.pacfin.2018.02.004
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    References listed on IDEAS

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    1. Kewei Hou, 2007. "Industry Information Diffusion and the Lead-lag Effect in Stock Returns," The Review of Financial Studies, Society for Financial Studies, vol. 20(4), pages 1113-1138.
    2. Paolo Colla & Antonio Mele, 2010. "Information Linkages and Correlated Trading," The Review of Financial Studies, Society for Financial Studies, vol. 23(1), pages 203-246, January.
    3. Kewei Hou & Tobias J. Moskowitz, 2005. "Market Frictions, Price Delay, and the Cross-Section of Expected Returns," The Review of Financial Studies, Society for Financial Studies, vol. 18(3), pages 981-1020.
    4. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    5. Andrew Ang & Robert J. Hodrick & Yuhang Xing & Xiaoyan Zhang, 2006. "The Cross‐Section of Volatility and Expected Returns," Journal of Finance, American Finance Association, vol. 61(1), pages 259-299, February.
    6. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    7. Newey, Whitney K & West, Kenneth D, 1987. "Hypothesis Testing with Efficient Method of Moments Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 28(3), pages 777-787, October.
    8. Lo, Andrew W & MacKinlay, A Craig, 1990. "When Are Contrarian Profits Due to Stock Market Overreaction?," The Review of Financial Studies, Society for Financial Studies, vol. 3(2), pages 175-205.
    9. Ozsoylev, Han N. & Walden, Johan, 2011. "Asset pricing in large information networks," Journal of Economic Theory, Elsevier, vol. 146(6), pages 2252-2280.
    10. Merton, Robert C, 1987. "A Simple Model of Capital Market Equilibrium with Incomplete Information," Journal of Finance, American Finance Association, vol. 42(3), pages 483-510, July.
    11. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    12. Xing Huang, 2015. "Thinking Outside the Borders: Investors' Underreaction to Foreign Operations Information," The Review of Financial Studies, Society for Financial Studies, vol. 28(11), pages 3109-3152.
    13. Han N. Ozsoylev & Johan Walden & M. Deniz Yavuz & Recep Bildik, 2014. "Investor Networks in the Stock Market," The Review of Financial Studies, Society for Financial Studies, vol. 27(5), pages 1323-1366.
    14. Fama, Eugene F & MacBeth, James D, 1973. "Risk, Return, and Equilibrium: Empirical Tests," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 607-636, May-June.
    15. Henk Berkman & Paul D. Koch & P. Joakim Westerholm, 2014. "Informed Trading through the Accounts of Children," Journal of Finance, American Finance Association, vol. 69(1), pages 363-404, February.
    16. Bing Han & Liyan Yang, 2013. "Social Networks, Information Acquisition, and Asset Prices," Management Science, INFORMS, vol. 59(6), pages 1444-1457, June.
    17. Brennan, Michael J & Jegadeesh, Narasimhan & Swaminathan, Bhaskaran, 1993. "Investment Analysis and the Adjustment of Stock Prices to Common Information," The Review of Financial Studies, Society for Financial Studies, vol. 6(4), pages 799-824.
    18. Brad M. Barber & Yi-Tsung Lee & Yu-Jane Liu & Terrance Odean, 2009. "Just How Much Do Individual Investors Lose by Trading?," The Review of Financial Studies, Society for Financial Studies, vol. 22(2), pages 609-632, February.
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    Cited by:

    1. Han, Rui-Qi & Li, Ming-Xia & Chen, Wei & Zhou, Wei-Xing & Stanley, H. Eugene, 2019. "Structural properties of statistically validated empirical information networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 747-756.
    2. Wang, Hu & Li, Shouwei & Ma, Yuyin, 2021. "Herding in Open-end Funds: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    3. Ren-Yuan Lyu & Ren-Raw Chen & San-Lin Chung & Yilu Zhou, 2024. "Systemic Risk and Bank Networks: A Use of Knowledge Graph with ChatGPT," FinTech, MDPI, vol. 3(2), pages 1-28, May.
    4. khan Feroz, Noushad & Hassan, Gazi & Cameron, Michael P., 2022. "To what extent do network effects moderate the relationship between social media propagated news and investors’ perceptions?," Research in Economics, Elsevier, vol. 76(3), pages 170-188.

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    More about this item

    Keywords

    Investor network; Information diffusion; Price delay; Asset prices;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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