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Informed Investors and the Internet

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  • Amir Rubin
  • Eran Rubin

Abstract

During the last decade the Internet has become an increasingly important source for gathering company related information. We employ Wikipedia editing frequency as an instrument that captures the degree in which the population is engaged with the processing of company‐related information. We find that firms whose information is processed by the population more frequently are associated with lower analysts' forecast errors, smaller analysts' forecast dispersions, and significant changes in bid‐ask spreads on analysts' recommendation days. These results indicate that information processing over the Internet is related to the degree to which investors and analysts are informed about companies.

Suggested Citation

  • Amir Rubin & Eran Rubin, 2010. "Informed Investors and the Internet," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 37(7‐8), pages 841-865, July.
    • Handle: RePEc:bla:jbfnac:v:37:y:2010:i:7-8:p:841-865
    DOI: 10.1111/j.1468-5957.2010.02187.x
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    3. Li, Xiao & Shen, Dehua & Zhang, Wei, 2018. "Do Chinese internet stock message boards convey firm-specific information?," Pacific-Basin Finance Journal, Elsevier, vol. 49(C), pages 1-14.
    4. Nian Li & Chunling Li & Runsen Yuan & Muhammad Asif Khan & Xiaoran Sun & Nosherwan Khaliq, 2021. "Investor Attention and Corporate Innovation Performance: Evidence from Web Search Volume Index of Chinese Listed Companies," Mathematics, MDPI, vol. 9(9), pages 1-23, April.
    5. Liu, Yang & Han, Liyan & Yin, Libo, 2019. "News implied volatility and long-term foreign exchange market volatility," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 126-142.
    6. Peltomäki, Jarkko & Graham, Michael & Hasselgren, Anton, 2018. "Investor attention to market categories and market volatility: The case of emerging markets," Research in International Business and Finance, Elsevier, vol. 44(C), pages 532-546.
    7. Aouadi, Amal & Arouri, Mohamed & Roubaud, David, 2018. "Information demand and stock market liquidity: International evidence," Economic Modelling, Elsevier, vol. 70(C), pages 194-202.
    8. Yang, Xiaolan & Zhu, Yu & Cheng, Teng Yuan, 2020. "How the individual investors took on big data: The effect of panic from the internet stock message boards on stock price crash," Pacific-Basin Finance Journal, Elsevier, vol. 59(C).
    9. Ackert, Lucy F. & Jiang, Lei & Lee, Hoan Soo & Liu, Jie, 2016. "Influential investors in online stock forums," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 39-46.
    10. Matthias Bank & Martin Larch & Georg Peter, 2011. "Google search volume and its influence on liquidity and returns of German stocks," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 25(3), pages 239-264, September.
    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. Melody Y. Huang & Randall R. Rojas & Patrick D. Convery, 2020. "Forecasting stock market movements using Google Trend searches," Empirical Economics, Springer, vol. 59(6), pages 2821-2839, December.
    13. Chen, Xing & Wu, Chongfeng, 2022. "Retail investor attention and information asymmetry: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 75(C).
    14. Takeda, Fumiko & Wakao, Takumi, 2014. "Google search intensity and its relationship with returns and trading volume of Japanese stocks," Pacific-Basin Finance Journal, Elsevier, vol. 27(C), pages 1-18.
    15. Dolores Moreno-Herrero & Manuel Salas-Velasco & José Sánchez-Campillo, 2017. "Individual Pension Plans in Spain: How Expected Change in Future Income and Liquidity Constraints Shape the Behavior of Households," Journal of Family and Economic Issues, Springer, vol. 38(4), pages 596-613, December.
    16. Shen, Dehua & Tong, Zezheng & Goodell, John W., 2024. "Do online message boards convey cryptocurrency-specific information?," International Review of Financial Analysis, Elsevier, vol. 91(C).
    17. Hervé, Fabrice & Zouaoui, Mohamed & Belvaux, Bertrand, 2019. "Noise traders and smart money: Evidence from online searches," Economic Modelling, Elsevier, vol. 83(C), pages 141-149.
    18. Chen, Linda H. & Dyl, Edward A. & Jiang, George J. & Juneja, Januj A., 2015. "Risk, illiquidity or marketability: What matters for the discounts on private equity placements?," Journal of Banking & Finance, Elsevier, vol. 57(C), pages 41-50.
    19. Bechly, Paul Lorin, 2019. "An Examination of Demographic Differences in Obtaining Investment and Financial Planning Information," OSF Preprints vn8yj, Center for Open Science.
    20. Moussa, Faten & Delhoumi, Ezzeddine & Ouda, Olfa Ben, 2017. "Stock return and volatility reactions to information demand and supply," Research in International Business and Finance, Elsevier, vol. 39(PA), pages 54-67.
    21. Tang, Wenbin & Zhu, Lili, 2017. "How security prices respond to a surge in investor attention: Evidence from Google Search of ADRs," Global Finance Journal, Elsevier, vol. 33(C), pages 38-50.
    22. Agarwal, Shweta & Kumar, Shailendra & Goel, Utkarsh, 2019. "Stock market response to information diffusion through internet sources: A literature review," International Journal of Information Management, Elsevier, vol. 45(C), pages 118-131.
    23. Vlastakis, Nikolaos & Markellos, Raphael N., 2012. "Information demand and stock market volatility," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1808-1821.
    24. Gang Chu & Xiao Li & Dehua Shen & Yongjie Zhang, 2021. "Stock Crashes and Jumps Reactions to Information Demand and Supply: An Intraday Analysis," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(3), pages 397-427, September.
    25. Chen, Xing & Diao, Xundi & Wu, Chongfeng, 2022. "Heterogeneous investor attention and post earnings announcement drift: Evidence from China," Economic Modelling, Elsevier, vol. 110(C).

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