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Forecasting abnormal stock returns and trading volume using investor sentiment: Evidence from online search

  • Joseph, Kissan
  • Babajide Wintoki, M.
  • Zhang, Zelin
Registered author(s):

    We examine the ability of online ticker searches (e.g. XOM for Exxon Mobil) to forecast abnormal stock returns and trading volumes. Specifically, we argue that online ticker searches serve as a valid proxy for investor sentiment -- a set of beliefs about cash flows and investment risks that are not necessarily justified by the facts at hand -- which is generally associated with less sophisticated, retail investors. Based on prior research on investor sentiment, we expect online search intensity to forecast stock returns and trading volume, and also expect that highly volatile stocks, which are more difficult to arbitrage, will be more sensitive to search intensity than less volatile stocks. In a sample of S&P 500 firms over the period 2005-2008, we find that, over a weekly horizon, online search intensity reliably predicts abnormal stock returns and trading volumes, and that the sensitivity of returns to search intensity is positively related to the difficulty of a stock being arbitraged. More broadly, our study highlights the potential of employing online search data for other forecasting applications.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0169207011000021
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    Article provided by Elsevier in its journal International Journal of Forecasting.

    Volume (Year): 27 (2011)
    Issue (Month): 4 (October)
    Pages: 1116-1127

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    Handle: RePEc:eee:intfor:v:27:y:2011:i:4:p:1116-1127
    Contact details of provider: Web page: http://www.elsevier.com/locate/ijforecast

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    1. 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.
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    6. Schmeling, Maik, 2007. "Institutional and individual sentiment: Smart money and noise trader risk?," International Journal of Forecasting, Elsevier, vol. 23(1), pages 127-145.
    7. 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.
    8. Shleifer, Andrei & Summers, Lawrence H, 1990. "The Noise Trader Approach to Finance," Journal of Economic Perspectives, American Economic Association, vol. 4(2), pages 19-33, Spring.
    9. Carhart, Mark M, 1997. " On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    10. Barber, Brad M. & Odean, Terrance & Zhu, Ning, 2009. "Systematic noise," Journal of Financial Markets, Elsevier, vol. 12(4), pages 547-569, November.
    11. 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.
    12. Malcolm Baker & Jeffrey Wurgler, 2006. "Investor Sentiment and the Cross-Section of Stock Returns," Journal of Finance, American Finance Association, vol. 61(4), pages 1645-1680, 08.
    13. Gustavo Grullon, 2004. "Advertising, Breadth of Ownership, and Liquidity," Review of Financial Studies, Society for Financial Studies, vol. 17(2), pages 439-461.
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