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A new measure of earnings forecast uncertainty

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  • Sheng, Xuguang
  • Thevenot, Maya

Abstract

Relying on the well-established theoretical result that uncertainty has a common and an idiosyncratic component, we propose a new measure of earnings forecast uncertainty as the sum of dispersion among analysts and the variance of mean forecast errors estimated by a GARCH model. The new measure is based on both common and private information available to analysts at the time they make their forecasts. Hence, it alleviates some of the limitations of other commonly used proxies for forecast uncertainty in the literature. Using analysts' earnings forecasts, we find direct evidence of the new measure's superior performance.

Suggested Citation

  • Sheng, Xuguang & Thevenot, Maya, 2012. "A new measure of earnings forecast uncertainty," Journal of Accounting and Economics, Elsevier, vol. 53(1), pages 21-33.
    • Handle: RePEc:eee:jaecon:v:53:y:2012:i:1:p:21-33
    DOI: 10.1016/j.jacceco.2011.11.001
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    References listed on IDEAS

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    1. Karl B. Diether & Christopher J. Malloy & Anna Scherbina, 2002. "Differences of Opinion and the Cross Section of Stock Returns," Journal of Finance, American Finance Association, vol. 57(5), pages 2113-2141, October.
    2. X. Frank Zhang, 2006. "Information Uncertainty and Stock Returns," Journal of Finance, American Finance Association, vol. 61(1), pages 105-137, February.
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    4. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    5. Kajal Lahiri & Xuguang Sheng, 2010. "Measuring forecast uncertainty by disagreement: The missing link," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 514-538.
    6. Michael Clement & Richard Frankel & Jeffrey Miller, 2003. "Confirming Management Earnings Forecasts, Earnings Uncertainty, and Stock Returns," Journal of Accounting Research, Wiley Blackwell, vol. 41(4), pages 653-679, September.
    7. Timothy C. Johnson, 2004. "Forecast Dispersion and the Cross Section of Expected Returns," Journal of Finance, American Finance Association, vol. 59(5), pages 1957-1978, October.
    8. Abarbanell, Jeffery & Lehavy, Reuven, 2003. "Biased forecasts or biased earnings? The role of reported earnings in explaining apparent bias and over/underreaction in analysts' earnings forecasts," Journal of Accounting and Economics, Elsevier, vol. 36(1-3), pages 105-146, December.
    9. Orie E. Barron, 2002. "High-Technology Intangibles and Analysts' Forecasts," Journal of Accounting Research, Wiley Blackwell, vol. 40(2), pages 289-312, May.
    10. Abarbanell, Jeffery S. & Lanen, William N. & Verrecchia, Robert E., 1995. "Analysts' forecasts as proxies for investor beliefs in empirical research," Journal of Accounting and Economics, Elsevier, vol. 20(1), pages 31-60, July.
    11. Doukas, John A. & Kim, Chansog (Francis) & Pantzalis, Christos, 2006. "Divergence of Opinion and Equity Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 41(03), pages 573-606, September.
    12. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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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. Xuguang Sheng & Maya Thevenot, 2013. "Differential Interpretation of Public Information: Estimation and Inference," Working Papers 2013-03, American University, Department of Economics.
    3. Sam Han & Justin Yiqiang Jin & Tony Kang & Gerald Lobo, 2014. "Managerial Ownership and Financial Analysts’ Information Environment," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 41(3-4), pages 328-362, April.
    4. Xuguang Sheng & Orie Barron & Maya Thevenot, 2012. "Information Environment and the Cost of Capital: A New Approach," Working Papers 2012-12, American University, Department of Economics.
    5. Sanjay W. Bissessur & David Veenman, 2016. "Analyst information precision and small earnings surprises," Review of Accounting Studies, Springer, vol. 21(4), pages 1327-1360, December.
    6. Sheng, Xuguang (Simon) & Thevenot, Maya, 2015. "Quantifying differential interpretation of public information using financial analysts’ earnings forecasts," International Journal of Forecasting, Elsevier, vol. 31(2), pages 515-530.
    7. repec:eee:advacc:v:30:y:2014:i:2:p:440-451 is not listed on IDEAS
    8. Bert de Bruijn & Philip Hans Franses, 2013. "Forecasting Earnings Forecasts," Tinbergen Institute Discussion Papers 13-121/III, Tinbergen Institute.
    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. Orie Barron & Xuguang Sheng & Maya Thevenot, 2013. "Information Environment and The Cost of Capital," Working Papers 2013-003, The George Washington University, Department of Economics, Research Program on Forecasting.

    More about this item

    Keywords

    Uncertainty; Analyst dispersion; Common information; Private information; BKLS; GARCH;

    JEL classification:

    • M41 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Accounting
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics

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