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Celebrities and ordinaries in social networks: Who knows more information?

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  • Zhang, Yongjie
  • An, Yahui
  • Feng, Xu
  • Jin, Xi

Abstract

This paper tests the information contained in messages that various types of users post on social networks. Our data come from Sina Weibo, the biggest social network in China. The users are classified as either celebrities or ordinaries. We find that postings from celebrities significantly predict stock returns, whereas postings from ordinaries have no predictive power. Furthermore, postings from celebrities contain more future public information and current private information. Ordinaries’ postings contain only stale information. The event study suggests that ordinaries can be considered as information followers rather than providers. These results are consistent with the informed guru hypothesis.

Suggested Citation

  • Zhang, Yongjie & An, Yahui & Feng, Xu & Jin, Xi, 2017. "Celebrities and ordinaries in social networks: Who knows more information?," Finance Research Letters, Elsevier, vol. 20(C), pages 153-161.
    • Handle: RePEc:eee:finlet:v:20:y:2017:i:c:p:153-161
    DOI: 10.1016/j.frl.2016.09.021
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    as
    1. Hasbrouck, Joel, 1991. "Measuring the Information Content of Stock Trades," Journal of Finance, American Finance Association, vol. 46(1), pages 179-207, March.
    2. Depken II, Craig A. & Zhang, Ying, 2010. "Adverse selection and reputation in a world of cheap talk," The Quarterly Review of Economics and Finance, Elsevier, vol. 50(4), pages 548-558, November.
    3. Sanjiv R. Das & Mike Y. Chen, 2007. "Yahoo! for Amazon: Sentiment Extraction from Small Talk on the Web," Management Science, INFORMS, vol. 53(9), pages 1375-1388, September.
    4. Zoran Ivkovi & Scott Weisbenner, 2007. "Information Diffusion Effects in Individual Investors' Common Stock Purchases: Covet Thy Neighbors' Investment Choices," The Review of Financial Studies, Society for Financial Studies, vol. 20(4), pages 1327-1357.
    5. Engelberg, Joseph E. & Reed, Adam V. & Ringgenberg, Matthew C., 2012. "How are shorts informed?," Journal of Financial Economics, Elsevier, vol. 105(2), pages 260-278.
    6. Roland Benabou & Guy Laroque, 1992. "Using Privileged Information to Manipulate Markets: Insiders, Gurus, and Credibility," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(3), pages 921-958.
    7. Nofer, Michael & Hinz, Oliver, 2014. "Are Crowds on the Internet Wiser than Experts? The Case of a Stock Prediction Community," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 69935, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    8. Mitchell, Mark L & Mulherin, J Harold, 1994. "The Impact of Public Information on the Stock Market," Journal of Finance, American Finance Association, vol. 49(3), pages 923-950, July.
    9. Harrison Hong & Jeffrey D. Kubik & Jeremy C. Stein, 2005. "Thy Neighbor's Portfolio: Word‐of‐Mouth Effects in the Holdings and Trades of Money Managers," Journal of Finance, American Finance Association, vol. 60(6), pages 2801-2824, December.
    10. Bhattacharya, Utpal & Daouk, Hazem & Jorgenson, Brian & Kehr, Carl-Heinrich, 2000. "When an event is not an event: the curious case of an emerging market," Journal of Financial Economics, Elsevier, vol. 55(1), pages 69-101, January.
    11. Timm O. Sprenger & Andranik Tumasjan & Philipp G. Sandner & Isabell M. Welpe, 2014. "Tweets and Trades: the Information Content of Stock Microblogs," European Financial Management, European Financial Management Association, vol. 20(5), pages 926-957, November.
    12. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2005. "Evidence on the speed of convergence to market efficiency," Journal of Financial Economics, Elsevier, vol. 76(2), pages 271-292, May.
    13. Shan, Liwei & Gong, Stephen X., 2012. "Investor sentiment and stock returns: Wenchuan Earthquake," Finance Research Letters, Elsevier, vol. 9(1), pages 36-47.
    14. Dev, Pritha, 2013. "Transfer of information by an informed trader," Finance Research Letters, Elsevier, vol. 10(2), pages 58-71.
    15. 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.
    16. Werner Antweiler & Murray Z. Frank, 2004. "Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards," Journal of Finance, American Finance Association, vol. 59(3), pages 1259-1294, June.
    17. Kim, Soon-Ho & Kim, Dongcheol, 2014. "Investor sentiment from internet message postings and the predictability of stock returns," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 708-729.
    18. Lily Fang & Joel Peress, 2009. "Media Coverage and the Cross‐section of Stock Returns," Journal of Finance, American Finance Association, vol. 64(5), pages 2023-2052, October.
    19. Chai, Edwina F.L. & Lee, Adrian D. & Wang, Jianxin, 2015. "Global information distribution in the gold OTC markets," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 206-217.
    20. Crawford, Vincent P & Sobel, Joel, 1982. "Strategic Information Transmission," Econometrica, Econometric Society, vol. 50(6), pages 1431-1451, November.
    21. Hailiang Chen & Prabuddha De & Yu (Jeffrey) Hu & Byoung-Hyoun Hwang, 2014. "Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media," Review of Financial Studies, Society for Financial Studies, vol. 27(5), pages 1367-1403.
    22. Yu, Fang (Frank), 2008. "Analyst coverage and earnings management," Journal of Financial Economics, Elsevier, vol. 88(2), pages 245-271, May.
    23. Wang, Jianxin & Yang, Minxian, 2011. "Housewives of Tokyo versus the gnomes of Zurich: Measuring price discovery in sequential markets," Journal of Financial Markets, Elsevier, vol. 14(1), pages 82-108, February.
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    3. Cao, Xing & Zhang, Yongjie & Feng, Xu & Meng, Xiangtong, 2021. "Investor interaction and price efficiency: Evidence from social media," Finance Research Letters, Elsevier, vol. 40(C).
    4. Heleen Brans & Bert Scholtens, 2020. "Under his thumb the effect of president Donald Trump’s Twitter messages on the US stock market," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-11, March.
    5. Jin, Xuejun & Zhu, Yu & Huang, Ying Sophie, 2019. "Losing by learning? A study of social trading platform," Finance Research Letters, Elsevier, vol. 28(C), pages 171-179.
    6. Siikanen, Milla & Baltakys, Kęstutis & Kanniainen, Juho & Vatrapu, Ravi & Mukkamala, Raghava & Hussain, Abid, 2018. "Facebook drives behavior of passive households in stock markets," Finance Research Letters, Elsevier, vol. 27(C), pages 208-213.
    7. Yao, Wenyun & Wei, Jiahui & Shen, Yongjian & Deng, Yan & Kutan, Ali M., 2020. "Does celebrity spokesperson signal firm performance? Evidence from a drug scandal in China," Finance Research Letters, Elsevier, vol. 34(C).

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    More about this item

    Keywords

    Gurus; Social network; Information; Online postings; Stock price;
    All these keywords.

    JEL classification:

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

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