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Investor Attention on the Social Web

Author

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  • Xian Li
  • James A. Hendler
  • John L. Teall

Abstract

We study investor attention through practitioners' tweeting behaviors. We develop formalisms of “cognitive niches,” heuristics from adaptive cognitive control, to account for the selectivity of investor attention. Using asset-specific tweets as direct measures of investor attention, we find evidence supporting contextual cognitive control, depending on asset types, investors' experience and investing approaches. We quantify attention contagion arising from the “social proof” heuristic, whereby the drawing power of the crowd in directing investor attention exceeds that of firm fundamentals. Finally, we demonstrate that different natures of investor attention (active or passive) reveals distinct patterns of trading volume, returns and volatility.

Suggested Citation

  • Xian Li & James A. Hendler & John L. Teall, 2016. "Investor Attention on the Social Web," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 17(1), pages 45-59, January.
    • Handle: RePEc:taf:hbhfxx:v:17:y:2016:i:1:p:45-59
    DOI: 10.1080/15427560.2015.1095752
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    Cited by:

    1. Arnold, Marc & Pelster, Matthias & Subrahmanyam, Marti G., 2022. "Attention triggers and investors’ risk-taking," Journal of Financial Economics, Elsevier, vol. 143(2), pages 846-875.
    2. Dash, Saumya Ranjan & Maitra, Debasish, 2019. "The relationship between emerging and developed market sentiment: A wavelet-based time-frequency analysis," Journal of Behavioral and Experimental Finance, Elsevier, vol. 22(C), pages 135-150.
    3. He, Xue-Zhong & Li, Kai & Santi, Caterina & Shi, Lei, 2022. "Social interaction, volatility clustering, and momentum," Journal of Economic Behavior & Organization, Elsevier, vol. 203(C), pages 125-149.
    4. Stallkamp, Maximilian & Hunt, Richard A. & Schotter, Andreas P.J., 2022. "Scaling, fast and slow: The internationalization of digital ventures," Journal of Business Research, Elsevier, vol. 146(C), pages 95-106.
    5. Gaoshan Wang & Guangjin Yu & Xiaohong Shen, 2020. "The Effect of Online Investor Sentiment on Stock Movements: An LSTM Approach," Complexity, Hindawi, vol. 2020, pages 1-11, December.
    6. Zhang, Yongjie & Chu, Gang & Shen, Dehua, 2021. "The role of investor attention in predicting stock prices: The long short-term memory networks perspective," Finance Research Letters, Elsevier, vol. 38(C).
    7. Alberto Barroso Del Toro & Laura Vivas Crisol & Xavier Tort-Martorell, 2022. "The Sustainability Narrative: A Multi Study Using Event Studies to Analyse the American Energy Companies Shareholder’s Reaction to Sustainability News," IJERPH, MDPI, vol. 19(23), pages 1-17, November.
    8. Wang, Chen & Shen, Dehua & Li, Youwei, 2022. "Aggregate Investor Attention and Bitcoin Return: The Long Short-term Memory Networks Perspective," Finance Research Letters, Elsevier, vol. 49(C).

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