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To the Moon: Analyzing Collective Trading Events on the Wings of Sentiment Analysis

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Listed:
  • Tim Matthies
  • Thomas Lohden
  • Stephan Leible
  • Jun-Patrick Raabe

Abstract

This research investigates the growing trend of retail investors participating in certain stocks by organizing themselves on social media platforms, particularly Reddit. Previous studies have highlighted a notable association between Reddit activity and the volatility of affected stocks. This study seeks to expand the analysis to Twitter, which is among the most impactful social media platforms. To achieve this, we collected relevant tweets and analyzed their sentiment to explore the correlation between Twitter activity, sentiment, and stock volatility. The results reveal a significant relationship between Twitter activity and stock volatility but a weak link between tweet sentiment and stock performance. In general, Twitter activity and sentiment appear to play a less critical role in these events than Reddit activity. These findings offer new theoretical insights into the impact of social media platforms on stock market dynamics, and they may practically assist investors and regulators in comprehending these phenomena better.

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  • Tim Matthies & Thomas Lohden & Stephan Leible & Jun-Patrick Raabe, 2023. "To the Moon: Analyzing Collective Trading Events on the Wings of Sentiment Analysis," Papers 2308.09968, arXiv.org.
    • Handle: RePEc:arx:papers:2308.09968
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    File URL: http://arxiv.org/pdf/2308.09968
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    References listed on IDEAS

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    1. John Y. Campbell, 2016. "Restoring Rational Choice: The Challenge of Consumer Financial Regulation," American Economic Review, American Economic Association, vol. 106(5), pages 1-30, May.
    2. Garman, Mark B & Klass, Michael J, 1980. "On the Estimation of Security Price Volatilities from Historical Data," The Journal of Business, University of Chicago Press, vol. 53(1), pages 67-78, January.
    3. Audrino, Francesco & Sigrist, Fabio & Ballinari, Daniele, 2020. "The impact of sentiment and attention measures on stock market volatility," International Journal of Forecasting, Elsevier, vol. 36(2), pages 334-357.
    4. Zheludev, Ilya & Smith, Robert & Aste, Tomaso, 2014. "When can social media lead financial markets?," LSE Research Online Documents on Economics 57376, London School of Economics and Political Science, LSE Library.
    5. Th'arsis Tuani Pinto Souza & Olga Kolchyna & Philip C. Treleaven & Tomaso Aste, 2015. "Twitter Sentiment Analysis Applied to Finance: A Case Study in the Retail Industry," Papers 1507.00784, arXiv.org, revised Jul 2015.
    6. Suwan (Cheng) Long & Brian Lucey & Ying Xie & Larisa Yarovaya, 2023. "“I just like the stock”: The role of Reddit sentiment in the GameStop share rally," The Financial Review, Eastern Finance Association, vol. 58(1), pages 19-37, February.
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