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How online discussion board activity affects stock trading: the case of GameStop

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Listed:
  • André Betzer

    (University of Wuppertal)

  • Jan Philipp Harries

    (University of Wuppertal)

Abstract

In January 2021, the stock price of NASDAQ-listed GameStop Corporation surged more than twenty-fold for no discernible economic reason. Many observers attributed this broadly covered rise to retail investors, organizing themselves in Reddit’s WallStreetBets community. While Social Media-organized trading is not a new phenomenon, the magnitude of the resulting swings in the share price and surge in trading volume of GameStop is unprecedented. Using financial data, as well as an extensive dataset of Reddit posts, we provide empirical evidence for the relationship of Reddit posts and GameStop (retail) trading. While we find a significant and positive relationship between Reddit posts and various trading measures in the following 30-min window in accordance with an attention-based mechanism, our results offer no indication for the informativeness of Reddit posts and hint at a complex and probably nonlinear interdependence between Social-media and trading activity, preventing proof of a one-directional, causal effect.

Suggested Citation

  • André Betzer & Jan Philipp Harries, 2022. "How online discussion board activity affects stock trading: the case of GameStop," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 36(4), pages 443-472, December.
  • Handle: RePEc:kap:fmktpm:v:36:y:2022:i:4:d:10.1007_s11408-022-00407-w
    DOI: 10.1007/s11408-022-00407-w
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    References listed on IDEAS

    as
    1. Han, Bing & Kumar, Alok, 2013. "Speculative Retail Trading and Asset Prices," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 48(2), pages 377-404, April.
    2. Gao, Lei & Han, Yufeng & Zhengzi Li, Sophia & Zhou, Guofu, 2018. "Market intraday momentum," Journal of Financial Economics, Elsevier, vol. 129(2), pages 394-414.
    3. Barrot, Jean-Noel & Kaniel, Ron & Sraer, David, 2016. "Are retail traders compensated for providing liquidity?," Journal of Financial Economics, Elsevier, vol. 120(1), pages 146-168.
    4. Christopher N. Avery & Judith A. Chevalier & Richard J. Zeckhauser, 2016. "The "CAPS" Prediction System and Stock Market Returns," Review of Finance, European Finance Association, vol. 20(4), pages 1363-1381.
    5. Sun, Licheng & Najand, Mohammad & Shen, Jiancheng, 2016. "Stock return predictability and investor sentiment: A high-frequency perspective," Journal of Banking & Finance, Elsevier, vol. 73(C), pages 147-164.
    6. Rawley Heimer, 2016. "Peer Pressure: Social Interaction and the Disposition Effect," Working Papers (Old Series) 1618, Federal Reserve Bank of Cleveland.
    7. Ekkehart Boehmer & Charles M. Jones & Xiaoyan Zhang & Xinran Zhang, 2021. "Tracking Retail Investor Activity," Journal of Finance, American Finance Association, vol. 76(5), pages 2249-2305, October.
    8. Ozik, Gideon & Sadka, Ronnie & Shen, Siyi, 2021. "Flattening the Illiquidity Curve: Retail Trading During the COVID-19 Lockdown," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 56(7), pages 2356-2388, November.
    9. J. Bradford De Long & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1989. "The Size and Incidence of the Losses from Noise Trading," Journal of Finance, American Finance Association, vol. 44(3), pages 681-696, July.
    10. Zhi Da & Joseph Engelberg & Pengjie Gao, 2011. "In Search of Attention," Journal of Finance, American Finance Association, vol. 66(5), pages 1461-1499, October.
    11. Malcolm Baker & Jeffrey Wurgler, 2007. "Investor Sentiment in the Stock Market," Journal of Economic Perspectives, American Economic Association, vol. 21(2), pages 129-152, Spring.
    12. Ahmad, Khurshid & Han, JingGuang & Hutson, Elaine & Kearney, Colm & Liu, Sha, 2016. "Media-expressed negative tone and firm-level stock returns," Journal of Corporate Finance, Elsevier, vol. 37(C), pages 152-172.
    13. Umar, Zaghum & Gubareva, Mariya & Yousaf, Imran & Ali, Shoaib, 2021. "A tale of company fundamentals vs sentiment driven pricing: The case of GameStop," Journal of Behavioral and Experimental Finance, Elsevier, vol. 30(C).
    14. Brad M. Barber & Terrance Odean, 2000. "Trading Is Hazardous to Your Wealth: The Common Stock Investment Performance of Individual Investors," Journal of Finance, American Finance Association, vol. 55(2), pages 773-806, April.
    15. Daniel, Kent & Hirshleifer, David & Teoh, Siew Hong, 2002. "Investor psychology in capital markets: evidence and policy implications," Journal of Monetary Economics, Elsevier, vol. 49(1), pages 139-209, January.
    16. Guégan, Dominique & Renault, Thomas, 2021. "Does investor sentiment on social media provide robust information for Bitcoin returns predictability?," Finance Research Letters, Elsevier, vol. 38(C).
    17. Brad M. Barber & Terrance Odean, 2008. "All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors," Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 785-818, April.
    18. Daniel Bradley & Jan Hanousek & Russell Jame & Zicheng Xiao, 2021. "Place your bets? The market consequences of investment advice on Reddit’s Wallstreetbets," MENDELU Working Papers in Business and Economics 2021-76, Mendel University in Brno, Faculty of Business and Economics.
    19. Behrendt, Simon & Schmidt, Alexander, 2018. "The Twitter myth revisited: Intraday investor sentiment, Twitter activity and individual-level stock return volatility," Journal of Banking & Finance, Elsevier, vol. 96(C), pages 355-367.
    20. Dyl, Edward A. & Maberly, Edwin D., 1992. "Odd-Lot Transactions around the Turn of the Year and the January Effect," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 27(4), pages 591-604, December.
    21. Rawley Z. Heimer, 2016. "Peer Pressure: Social Interaction and the Disposition Effect," Review of Financial Studies, Society for Financial Studies, vol. 29(11), pages 3177-3209.
    22. Philippe van der Beck & Coralie Jaunin, 2021. "The Equity Market Implications of the Retail Investment Boom," Swiss Finance Institute Research Paper Series 21-12, Swiss Finance Institute.
    23. David Hirshleifer, 2020. "Presidential Address: Social Transmission Bias in Economics and Finance," Journal of Finance, American Finance Association, vol. 75(4), pages 1779-1831, August.
    24. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    25. Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, June.
    26. 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.
    27. 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.
    28. Eric K. Kelley & Paul C. Tetlock, 2013. "How Wise Are Crowds? Insights from Retail Orders and Stock Returns," Journal of Finance, American Finance Association, vol. 68(3), pages 1229-1265, June.
    29. Crawford, Steven S. & Gray, Wesley R. & Kern, Andrew E., 2017. "Why Do Fund Managers Identify and Share Profitable Ideas?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 52(5), pages 1903-1926, October.
    30. J. Anthony Cookson & Marina Niessner, 2020. "Why Don't We Agree? Evidence from a Social Network of Investors," Journal of Finance, American Finance Association, vol. 75(1), pages 173-228, February.
    31. 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.
    32. Alok Kumar & Charles M.C. Lee, 2006. "Retail Investor Sentiment and Return Comovements," Journal of Finance, American Finance Association, vol. 61(5), pages 2451-2486, October.
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    More about this item

    Keywords

    GameStop; Retail trading; Trade volume; Market structure;
    All these keywords.

    JEL classification:

    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets

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