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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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    Cited by:

    1. Tsang, Albert & Xiang, Yi & Yu, Li, 2023. "Cross-border regulatory cooperation and analyst forecasts," International Review of Financial Analysis, Elsevier, vol. 90(C).
    2. Han, Jianlei & Pan, Zheyao & Zhang, Guangli, 2017. "Divergence of opinion and long-run performance of private placements: evidence from the auction market," Working Papers 2017-09, University of Tasmania, Tasmanian School of Business and Economics.
    3. Christopher von Koch & Ola Nilsson & Micael Jonsson & Andreas Jansson, 2014. "An Empirical Study of the Method Effect in Analysing the Adoption of IFRS," Accounting and Finance Research, Sciedu Press, vol. 3(2), pages 153-153, May.
    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. Cristi Gleason & Zhejia Ling & Rong Zhao, 2020. "Selective disclosure and the role of Form 8‐K in the post‐Reg FD era," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 47(3-4), pages 365-396, March.
    6. Bert De Bruijn & Philip Hans Franses, 2018. "How Informative Are Earnings Forecasts? †," JRFM, MDPI, vol. 11(3), pages 1-20, July.
    7. Clarence Goh, 2024. "Analysts’ Earnings per Share Forecasts: The Effects of Forecast Uncertainty and Forecast Precision on Investor Judgements," Abacus, Accounting Foundation, University of Sydney, vol. 60(1), pages 172-204, March.
    8. 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.
    9. Bert de Bruijn & Philip Hans Franses, 2013. "Forecasting Earnings Forecasts," Tinbergen Institute Discussion Papers 13-121/III, Tinbergen Institute.
    10. 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.
    11. Xuguang Sheng & Maya Thevenot, 2013. "Differential Interpretation of Public Information: Estimation and Inference," Working Papers 2013-03, American University, Department of Economics.
    12. 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.
    13. Schaberl, Philipp D., 2014. "The influence of disclosure policy on analyst behavior: The case of segment data," Advances in accounting, Elsevier, vol. 30(2), pages 440-451.
    14. 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.
    15. 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, H. O. Stekler Research Program on Forecasting.
    16. Bert de Bruijn & Philip Hans Franses, 2012. "What drives the Quotes of Earnings Forecasters?," Tinbergen Institute Discussion Papers 12-067/4, Tinbergen Institute.

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    More about this item

    Keywords

    Uncertainty; Analyst dispersion; Common information; Private information; BKLS; GARCH;
    All these keywords.

    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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