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The appeal of vague financial forecasts

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  • Du, Ning
  • Budescu, David V.
  • Shelly, Marjorie K.
  • Omer, Thomas C.

Abstract

Prior findings suggest managers often choose ranges to communicate uncertainty in future earnings. We analyzed earnings forecasts over 11 years and find higher earnings uncertainty firms are more likely to choose range estimates. We study investors' attitudes to forecast precision and argue investors' evaluations of forecasts can be explained by a sequential non-compensatory two-stage process - First, investors determine whether a point or a range estimate is more appropriate for a particular domain based on the congruence principle. Then, they seek the most precise reasonable range to maximize informativeness. Results from three experiments indicate the preference for (im)precision is non-monotonic - it peaks for low levels of imprecision and diminishes when the range gets wider, and is consistent with participants' desire for congruent and informative estimates, and supports the claim that investors favor forecasts that are as precise as warranted by the information available, but not more precise.

Suggested Citation

  • Du, Ning & Budescu, David V. & Shelly, Marjorie K. & Omer, Thomas C., 2011. "The appeal of vague financial forecasts," Organizational Behavior and Human Decision Processes, Elsevier, vol. 114(2), pages 179-189, March.
  • Handle: RePEc:eee:jobhdp:v:114:y:2011:i:2:p:179-189
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    3. Yuanyuan Liu & Timothy B. Heath & Ayse Onculer, 2020. "The Future Ambiguity Effect: How Narrow Payoff Ranges Increase Future Payoff Appeal," Management Science, INFORMS, vol. 66(8), pages 3754-3770, August.
    4. Chronopoulos, Panagiotis I. & Siougle, Georgia, 2018. "Examination of the information content of management range forecasts," Research in International Business and Finance, Elsevier, vol. 46(C), pages 201-210.
    5. Ord, J. Keith, 2022. "The uncertainty track: Machine learning, statistical modeling, synthesis," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1526-1530.
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    7. Eilifsen, Aasmund & Hamilton, Erin L. & Messier, William F., 2021. "The importance of quantifying uncertainty: Examining the effects of quantitative sensitivity analysis and audit materiality disclosures on investors’ judgments and decisions," Accounting, Organizations and Society, Elsevier, vol. 90(C).
    8. Han, Jun, 2013. "A literature synthesis of experimental studies on management earnings guidance," Journal of Accounting Literature, Elsevier, vol. 31(1), pages 49-70.
    9. Avagyan, Vardan & Camacho, Nuno & Van der Stede, Wim & Stremersch, Stefan, 2022. "Financial projections in innovation selection: the role of scenario presentation, expertise, and risk," LSE Research Online Documents on Economics 112474, London School of Economics and Political Science, LSE Library.
    10. Avagyan, Vardan & Camacho, Nuno & Van der Stede, Wim A. & Stremersch, Stefan, 2022. "Financial projections in innovation selection: The role of scenario presentation, expertise, and risk," International Journal of Research in Marketing, Elsevier, vol. 39(3), pages 907-926.
    11. Saurabh Bansal & Suresh Muthulingam, 2022. "Can precise numbers boost energy efficiency?," Production and Operations Management, Production and Operations Management Society, vol. 31(8), pages 3264-3287, August.
    12. Dorit Efrat-Treister & Hadar Moriah & Anat Rafaeli, 2020. "The effect of waiting on aggressive tendencies toward emergency department staff: Providing information can help but may also backfire," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-18, January.
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    14. Kelton, Andrea Seaton & Montague, Norma R., 2018. "The unintended consequences of uncertainty disclosures made by auditors and managers on nonprofessional investor judgments," Accounting, Organizations and Society, Elsevier, vol. 65(C), pages 44-55.

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