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Understanding analysts' use of stock returns and other analysts' revisions when forecasting earnings

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  • Clement, Michael B.
  • Hales, Jeffrey
  • Xue, Yanfeng

Abstract

We investigate analysts' use of stock returns and other analysts' forecast revisions in revising their own forecasts after an earnings announcement. We find that analysts respond more strongly to these signals when the signals are more informative about future earnings changes. Although analysts underreact to these signals on average, we find that analysts who are most sensitive to signal informativeness achieve superior forecast accuracy relative to their peers and have a greater influence on the market. The results suggest that the ability to extract information from the actions of others serves as one source of analyst expertise.

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  • Clement, Michael B. & Hales, Jeffrey & Xue, Yanfeng, 2011. "Understanding analysts' use of stock returns and other analysts' revisions when forecasting earnings," Journal of Accounting and Economics, Elsevier, vol. 51(3), pages 279-299, April.
  • Handle: RePEc:eee:jaecon:v:51:y:2011:i:3:p:279-299
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Bert de Bruijn & Philip Hans Franses, 2015. "How Informative are the Unpredictable Components of Earnings Forecasts?," Tinbergen Institute Discussion Papers 15-032/III, Tinbergen Institute.
    2. KiHoon Jimmy Hong & Bin Peng & Xiaohui Zhang, 2015. "Capturing the Impact of Unobserved Sector-Wide Shocks on Stock Returns with Panel Data Model," The Economic Record, The Economic Society of Australia, vol. 91(295), pages 495-508, December.
    3. Bert de Bruijn & Philip Hans Franses, 2013. "Forecasting Earnings Forecasts," Tinbergen Institute Discussion Papers 13-121/III, Tinbergen Institute.
    4. Papastamos, Dimitrios & Matysiak, George & Stevenson, Simon, 2015. "Assessing the accuracy and dispersion of real estate investment forecasts," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 141-152.
    5. repec:bla:acctfi:v:57:y:2017:i:1:p:199-237 is not listed on IDEAS
    6. KiHoon Jimmy Hong & Bin Peng & Xiaohui Zhang, 2014. "Capturing the Impact of Latent Industry-Wide Shocks with Dynamic Panel Model," Research Paper Series 347, Quantitative Finance Research Centre, University of Technology, Sydney.
    7. Hribar, Paul & Melessa, Samuel J. & Small, R. Christopher & Wilde, Jaron H., 2017. "Does managerial sentiment affect accrual estimates? Evidence from the banking industry," Journal of Accounting and Economics, Elsevier, vol. 63(1), pages 26-50.
    8. Dimitrios Papastamos & George Matysiak & Simon Stevenson, 2014. "A Comparative Analysis of the Accuracy and Uncertainty in Real Estate and Macroeconomic Forecasts," Real Estate & Planning Working Papers rep-wp2014-06, Henley Business School, Reading University.
    9. Bert de Bruijn & Philip Hans Franses, 2012. "What drives the Quotes of Earnings Forecasters?," Tinbergen Institute Discussion Papers 12-067/4, Tinbergen Institute.
    10. Cici, Gjergji & Shane, Philip B. & Yang, Yanhua Sunny, 2017. "Do connections with buy-side analysts inform sell-side analyst research?," CFR Working Papers 17-04, University of Cologne, Centre for Financial Research (CFR).
    11. Jung, Jay Heon & Pae, Jinhan & Yoo, Choong-Yuel, 2015. "Do analysts treat winners and losers differently when forecasting earnings?," International Journal of Forecasting, Elsevier, vol. 31(2), pages 531-549.

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