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A new measure of earnings forecast uncertainty

  • Sheng, Xuguang
  • Thevenot, Maya

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.

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Article provided by Elsevier in its journal Journal of Accounting and Economics.

Volume (Year): 53 (2012)
Issue (Month): 1 ()
Pages: 21-33

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Handle: RePEc:eee:jaecon:v:53:y:2012:i:1:p:21-33
Contact details of provider: Web page: http://www.elsevier.com/locate/jae

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  1. Kajal Lahiri & Xuguang Sheng, 2009. "Measuring Forecast Uncertainty by Disagreement: The Missing Link," Discussion Papers 09-06, University at Albany, SUNY, Department of Economics.
  2. 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.
  3. Degeorge, Fran├žois & Patel, U & Zeckhauser, Richard, 1998. "Earnings Management to Exceed Thresholds," CEPR Discussion Papers 1790, C.E.P.R. Discussion Papers.
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  8. 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.
  9. 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.
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