IDEAS home Printed from https://ideas.repec.org/a/eee/finana/v67y2020ics1057521919304818.html
   My bibliography  Save this article

Social media effect, investor recognition and the cross-section of stock returns

Author

Listed:
  • Meng, Xiangtong
  • Zhang, Wei
  • Li, Youwei
  • Cao, Xing
  • Feng, Xu

Abstract

Investor recognition affects cross-sectional stock returns. In informationally incomplete markets, investors have limited recognition of all securities, and their holding of stocks with low recognition requires compensation for being imperfectly diversified. Using the number of posts on the Chinese social media platform Guba to measure investor recognition of stocks, this paper provides a direct test of Merton's investor recognition hypothesis. We find a significant social media premium in the Chinese stock market. We further find that including a social media factor based on this premium significantly improves the explanatory power of Fama-French factor models of cross-sectional stock returns, and these results are robust when we control for the mass media effect and liquidity effect. Finally, we find that investment strategies based on the social media factor earn sizable risk-adjusted returns, which signifies the importance of the social media premium in portfolio management.

Suggested Citation

  • Meng, Xiangtong & Zhang, Wei & Li, Youwei & Cao, Xing & Feng, Xu, 2020. "Social media effect, investor recognition and the cross-section of stock returns," International Review of Financial Analysis, Elsevier, vol. 67(C).
    • Handle: RePEc:eee:finana:v:67:y:2020:i:c:s1057521919304818
    DOI: 10.1016/j.irfa.2019.101432
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1057521919304818
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.irfa.2019.101432?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Bali, Turan G. & Cakici, Nusret & Whitelaw, Robert F., 2011. "Maxing out: Stocks as lotteries and the cross-section of expected returns," Journal of Financial Economics, Elsevier, vol. 99(2), pages 427-446, February.
    3. Hunt Allcott & Matthew Gentzkow, 2017. "Social Media and Fake News in the 2016 Election," NBER Working Papers 23089, National Bureau of Economic Research, Inc.
    4. Pastor, Lubos & Stambaugh, Robert F., 2003. "Liquidity Risk and Expected Stock Returns," Journal of Political Economy, University of Chicago Press, vol. 111(3), pages 642-685, June.
    5. Tobias Adrian & Erkko Etula & Tyler Muir, 2014. "Financial Intermediaries and the Cross-Section of Asset Returns," Journal of Finance, American Finance Association, vol. 69(6), pages 2557-2596, December.
    6. Guo, Bin & Zhang, Wei & Zhang, Yongjie & Zhang, Han, 2017. "The five-factor asset pricing model tests for the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 43(C), pages 84-106.
    7. 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.
    8. David Hirshleifer, 2001. "Investor Psychology and Asset Pricing," Journal of Finance, American Finance Association, vol. 56(4), pages 1533-1597, August.
    9. Han, Xing & Li, Youwei, 2017. "Can investor sentiment be a momentum time-series predictor? Evidence from China," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 212-239.
    10. John M. Griffin & Nicholas H. Hirschey & Patrick J. Kelly, 2011. "How Important Is the Financial Media in Global Markets?," The Review of Financial Studies, Society for Financial Studies, vol. 24(12), pages 3941-3992.
    11. Leung, Henry & Ton, Thai, 2015. "The impact of internet stock message boards on cross-sectional returns of small-capitalization stocks," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 37-55.
    12. Kewei Hou & Chen Xue & Lu Zhang, 2015. "Editor's Choice Digesting Anomalies: An Investment Approach," The Review of Financial Studies, Society for Financial Studies, vol. 28(3), pages 650-705.
    13. Gregory S. Miller & Douglas J. Skinner, 2015. "The Evolving Disclosure Landscape: How Changes in Technology, the Media, and Capital Markets Are Affecting Disclosure," Journal of Accounting Research, Wiley Blackwell, vol. 53(2), pages 221-239, May.
    14. 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.
    15. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    16. John D Turner & Qing Ye & Clive B Walker, 2018. "Media Coverage and Stock Returns on the London Stock Exchange, 1825–70," Review of Finance, European Finance Association, vol. 22(4), pages 1605-1629.
    17. Gibbons, Michael R & Ross, Stephen A & Shanken, Jay, 1989. "A Test of the Efficiency of a Given Portfolio," Econometrica, Econometric Society, vol. 57(5), pages 1121-1152, September.
    18. Zhi Da & Qianqiu Liu & Ernst Schaumburg, 2011. "Decomposing short-term return reversal," Staff Reports 513, Federal Reserve Bank of New York.
    19. 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.
    20. 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.
    21. Jegadeesh, Narasimhan & Titman, Sheridan, 1993. "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency," Journal of Finance, American Finance Association, vol. 48(1), pages 65-91, March.
    22. Nicky J. Ferguson & Dennis Philip & Herbert Y. T. Lam & Jie Michael Guo, 2015. "Media Content and Stock Returns: The Predictive Power of Press," Multinational Finance Journal, Multinational Finance Journal, vol. 19(1), pages 1-31, March.
    23. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    24. Baker, Malcolm & Wurgler, Jeffrey & Yuan, Yu, 2012. "Global, local, and contagious investor sentiment," Journal of Financial Economics, Elsevier, vol. 104(2), pages 272-287.
    25. Brad M. Barber & Terrance Odean, 2008. "All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors," The Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 785-818, April.
    26. Alexander Shapiro, 2002. "The Investor Recognition Hypothesis in a Dynamic General Equilibrium: Theory and Evidence," The Review of Financial Studies, Society for Financial Studies, vol. 15(1), pages 97-141, March.
    27. Gustavo Grullon, 2004. "Advertising, Breadth of Ownership, and Liquidity," The Review of Financial Studies, Society for Financial Studies, vol. 17(2), pages 439-461.
    28. Harrison Hong & Jeremy C. Stein, 2007. "Disagreement and the Stock Market," Journal of Economic Perspectives, American Economic Association, vol. 21(2), pages 109-128, Spring.
    29. Miller, Edward M, 1977. "Risk, Uncertainty, and Divergence of Opinion," Journal of Finance, American Finance Association, vol. 32(4), pages 1151-1168, September.
    30. Jose A. Scheinkman & Wei Xiong, 2003. "Overconfidence and Speculative Bubbles," Journal of Political Economy, University of Chicago Press, vol. 111(6), pages 1183-1219, December.
    31. 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.
    32. Timm O. Sprenger & Philipp G. Sandner & Andranik Tumasjan & Isabell M. Welpe, 2014. "News or Noise? Using Twitter to Identify and Understand Company-specific News Flow," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 41(7-8), pages 791-830, September.
    33. Hongquan Zhu & Lingling Jiang, 2017. "Investor recognition and stock returns: evidence from China," China Finance Review International, Emerald Group Publishing Limited, vol. 8(2), pages 199-215, December.
    34. repec:bla:jfinan:v:59:y:2004:i:3:p:1259-1294 is not listed on IDEAS
    35. Bodnaruk, Andriy & Ostberg, Per, 2009. "Does investor recognition predict returns?," Journal of Financial Economics, Elsevier, vol. 91(2), pages 208-226, February.
    36. Hunt Allcott & Matthew Gentzkow, 2017. "Social Media and Fake News in the 2016 Election," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 211-236, Spring.
    37. Hiroyuki Aman & Norihiro Kasuga & Hiroshi Moriyasu, 2018. "Mass media effects on trading activities: television broadcasting evidence from Japan," Applied Economics, Taylor & Francis Journals, vol. 50(42), pages 4522-4539, September.
    38. Green, T. Clifton & Jame, Russell, 2013. "Company name fluency, investor recognition, and firm value," Journal of Financial Economics, Elsevier, vol. 109(3), pages 813-834.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wu, Chunying & Xiong, Xiong & Gao, Ya & Zhang, Jin, 2022. "Does social media coverage deter firms from withholding bad news? Evidence from stock price crash risk," International Review of Financial Analysis, Elsevier, vol. 84(C).
    2. Wu, Chunying & Xiong, Xiong & Gao, Ya, 2022. "The role of different information sources in information spread: Evidence from three media channels in China," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 327-341.
    3. Geng, Yuedan & Ye, Qiang & Jin, Yu & Shi, Wen, 2022. "Crowd wisdom and internet searches: What happens when investors search for stocks?," International Review of Financial Analysis, Elsevier, vol. 82(C).
    4. Ganggang Guo & Yulei Rao & Feida Zhu & Fang Xu, 2020. "Innovative deep matching algorithm for stock portfolio selection using deep stock profiles," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-31, November.
    5. Wu, Chunying & Xiong, Xiong & Gao, Ya & Zhang, Jin, 2022. "Does social media distort price discovery? Evidence from rumor clarifications," Research in International Business and Finance, Elsevier, vol. 62(C).
    6. 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).
    7. Jun Xie & Junyi Chen, 2021. "Corporate philanthropy, public awareness, and the cost of equity capital: Evidence from China," Annals of Economics and Finance, Society for AEF, vol. 22(1), pages 153-194, May.
    8. Ho, Kung-Cheng & Shen, Xixi & Yan, Cheng & Hu, Xiang, 2023. "Influence of green innovation on disclosure quality: Mediating role of media attention," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    9. Zhang, Xiaotao & Li, Guoran & Li, Yishuo & Zou, Gaofeng & Wu, Ji George, 2023. "Which is more important in stock market forecasting: Attention or sentiment?," International Review of Financial Analysis, Elsevier, vol. 89(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dong, Dayong & Wu, Keke & Fang, Jianchun & Gozgor, Giray & Yan, Cheng, 2022. "Investor attention factors and stock returns: Evidence from China," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    2. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, December.
    3. Chen, Tsung-Yu & Chao, Ching-Hsiang & Wu, Zhen-Xing, 2021. "Does the turnover effect matter in emerging markets? Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 67(C).
    4. Kewei Hou & Chen Xue & Lu Zhang, 2017. "Replicating Anomalies," NBER Working Papers 23394, National Bureau of Economic Research, Inc.
    5. Andreou, Panayiotis C. & Kagkadis, Anastasios & Philip, Dennis & Tuneshev, Ruslan, 2018. "Differences in options investors’ expectations and the cross-section of stock returns," Journal of Banking & Finance, Elsevier, vol. 94(C), pages 315-336.
    6. Liu, Sha & Han, Jingguang, 2020. "Media tone and expected stock returns," International Review of Financial Analysis, Elsevier, vol. 70(C).
    7. Turan G. Bali & Robert F. Engle & Yi Tang, 2017. "Dynamic Conditional Beta Is Alive and Well in the Cross Section of Daily Stock Returns," Management Science, INFORMS, vol. 63(11), pages 3760-3779, November.
    8. Stefan Nagel, 2013. "Empirical Cross-Sectional Asset Pricing," Annual Review of Financial Economics, Annual Reviews, vol. 5(1), pages 167-199, November.
    9. Ahmad, Fawad & Oriani, Raffaele, 2022. "Investor attention, information acquisition, and value premium: A mispricing perspective," International Review of Financial Analysis, Elsevier, vol. 79(C).
    10. Du, Hanyu & Hao, Jing & He, Feng & Xi, Wenze, 2022. "Media sentiment and cross-sectional stock returns in the Chinese stock market," Research in International Business and Finance, Elsevier, vol. 60(C).
    11. Yen‐Cheng Chang & Pei‐Jie Hsiao & Alexander Ljungqvist & Kevin Tseng, 2022. "Testing Disagreement Models," Journal of Finance, American Finance Association, vol. 77(4), pages 2239-2285, August.
    12. Ruenzi, Stefan & Ungeheuer, Michael & Weigert, Florian, 2020. "Joint Extreme events in equity returns and liquidity and their cross-sectional pricing implications," Journal of Banking & Finance, Elsevier, vol. 115(C).
    13. Chen, Xing & Wu, Chongfeng, 2022. "Retail investor attention and information asymmetry: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 75(C).
    14. Wang, Zijun, 2021. "The high volume return premium and economic fundamentals," Journal of Financial Economics, Elsevier, vol. 140(1), pages 325-345.
    15. Atilgan, Yigit & Bali, Turan G. & Demirtas, K. Ozgur & Gunaydin, A. Doruk, 2020. "Left-tail momentum: Underreaction to bad news, costly arbitrage and equity returns," Journal of Financial Economics, Elsevier, vol. 135(3), pages 725-753.
    16. Han, Xing & Li, Kai & Li, Youwei, 2020. "Investor overconfidence and the security market line: New evidence from China," Journal of Economic Dynamics and Control, Elsevier, vol. 117(C).
    17. Leung, Woon Sau & Evans, Kevin P. & Mazouz, Khelifa, 2020. "The R&D anomaly: Risk or mispricing?," Journal of Banking & Finance, Elsevier, vol. 115(C).
    18. Ji Cao & Marc Oliver Rieger & Lei Zhao, 2019. "Safety First, Loss Probability, and the Cross Section of Expected Stock Returns," Working Paper Series 2019-02, University of Trier, Research Group Quantitative Finance and Risk Analysis.
    19. Snigaroff, Robert & Wroblewski, David, 2021. "Earnings and liquidity factors," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 508-523.
    20. Zhong, Angel & Chai, Daniel & Li, Bob & Chiah, Mardy, 2018. "Volume shocks and stock returns: An alternative test," Pacific-Basin Finance Journal, Elsevier, vol. 48(C), pages 1-16.

    More about this item

    Keywords

    Social media; Investor recognition; Asset pricing;
    All these keywords.

    JEL classification:

    • 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
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:finana:v:67:y:2020:i:c:s1057521919304818. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620166 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.