Hostname: page-component-7b9c58cd5d-9k27k Total loading time: 0 Render date: 2025-03-17T05:35:19.799Z Has data issue: false hasContentIssue false
  • English
  • Français

Inefficiency in Earnings Forecasts: Experimental Evidence of Reactions to Positive vs. Negative Information

Published online by Cambridge University Press:  14 March 2025

Douglas E. Stevens  and
Arlington W. Williams
Douglas E. Stevens*
Affiliation:
Department of Accounting, School of Management, Syracuse University, 900 S. Crouse Avenue, Syracuse, NY 13244-2130, USA
Arlington W. Williams*
Affiliation:
Department of Economics, Indiana University, Wylie Hall 105, Bloomington, IN 47405, USA
*
email: desteven@syr.edu
email: williama@indiana.edu
Get access Rights & Permissions [Opens in a new window]

Abstract

Prior archival studies of analysts’ forecasts have found evidence for systematic underreaction, systematic overreaction, and systematic optimism bias. Easterwood and Nutt (1999) attempt to reconcile the conflicting evidence by testing the robustness of Abarbanell and Bernard's (1992) underreaction results to the nature of the information. Consistent with systematic optimism, forecasts are found to underreact to negative earnings information but overreact to positive information. However, Easterwood and Nutt are unable to distinguish between misreaction caused by incentives unique to analysts with misreaction caused by human decision bias that may be typical of investors. We address this issue by analyzing forecast reactions to positive versus negative information in the controlled experimental setting of Gillette, Stevens, Watts, and Williams (1999). The forecast data reveal systematic underreaction to both positive and negative information, and the underreaction is generally greater for positive information than negative information. This suggests that prior empirical evidence of forecast overreaction to positive information is unlikely to be attributable to human decision bias.

Keywords

earnings forecastslaboratory experimentshuman decision biases

JEL classification

D84: Expectations • Speculations C90: General
Type
Research Article
Information
Experimental Economics , Volume 7 , Issue 1 , February 2004 , pp. 75 - 92
Copyright
Copyright © 2004 Economic Science Association

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abarbanell, J. (1991). “Do Analysts’ Forecasts Incorporate Information in Prior Stock Price Changes?” Journal of Accounting and Economics. 14, 147–165.CrossRefGoogle Scholar
Abarbanell, J. and Bernard, V. (1992). “Tests of Analysts’ Overreaction/Underreaction to Earnings Information as an Explanation for Anomalous Stock Price Behavior.” Journal of Finance. 47, 1181–1207.CrossRefGoogle Scholar
Abarbanell, J. and Lehavy, R. (2000). “Biased Forecasts or Biased Earnings? The Role of Earnings Management in Explaining Apparent Optimism and Inefficiency in Analysts’ Earnings Forecasts.” Working paper, University of North Carolina.Google Scholar
Affleck-Graves, J., Davis, L., and Mendenhall, R. (1990). “Forecasts of Earnings Per Share: Possible Sources of Analyst Superiority and Bias.” Contemporary Accounting Research. 6(2), 501–517.CrossRefGoogle Scholar
Ahmed, A., Lobo, G., and Zhang, X. (2001). “Do Analysts Under-React to Bad News and Over-React to Good News?” Working paper, Syracuse University.CrossRefGoogle Scholar
Ali, A., Klein, A., and Rosenfeld, J. (1992). “Analysts’ Use of Information About Permanent and Transitory Earnings Components in Forecasting Annual EPS.” The Accounting Review. 67, 183–198.Google Scholar
Barberis, N. and Thaler, R. (2002). “A Survey of Behavioral Finance.” Forthcoming in Constantinides, G., Harris, M., and Stulz, R. (eds.), Handbook of the Economics of Finance.CrossRefGoogle Scholar
Bernard, V. (1993). “Stock Price Reactions to Earnings Announcements: A Survey of Recent Anomalous Evidence and Possible Explanations.” In Thaler, R. (ed.), Advances in Behavioral Finance. New York: Russell Sage Foundation.Google Scholar
Biggs, S. (1984). “Financial Analysts’ Information Search in the Assessment of Corporate Earning Power.” Accounting, Organizations and Society. 9, 313–323.CrossRefGoogle Scholar
Bouwman, M., Frishkoff, P., and Frishkoff, P. (1987). “How Do Financial Analysts Make Decisions? A Process Model of the Investment Screening Decision.” Accounting, Organizations and Society. 12, 1–29.CrossRefGoogle Scholar
Brown, L. (1993). “Earnings Forecasting Research: Its Implications for Capital Markets Research.” International Journal of Forecasting. 9, 295–320.CrossRefGoogle Scholar
Brown, L. and Rozeff, M. (1979). “Univariate Time-Series Models of Quarterly Accounting Earnings Per Share: A Proposed Model.” Journal of Accounting Research. 17(Spring), 179–189.CrossRefGoogle Scholar
Calegari, M. and Fargher, N. (1997). “Evidence That Prices Do Not Fully Reflect the Implications of Current Earnings for Future Earnings.” Contemporary Accounting Research. 14(3), 397–433.CrossRefGoogle Scholar
Camerer, C. (1987). “Do Biases in Probability Judgment Matter in Markets? Experimental Evidence.” American Economic Review. 77(5), 981–997.Google Scholar
Camerer, C. (1995). “Individual Decision Making.” In Kagel, J. and Roth, A. (eds.), The Handbook of Experimental Economics. Princeton: Princeton University Press.Google Scholar
Daniel, K., Hirshleifer, D., and Subrahmanyam, A. (1998). “Investor Psychology and Security Market Under- and Overreactions.” The Journal of Finance. 53(6), 1839–1885.CrossRefGoogle Scholar
Darrough, M. and Russell, T. (2000). “A Positive Model of Earnings Forecasts: Top Down Versus Bottom Up.” Working paper, Baruch College, CUNY.CrossRefGoogle Scholar
DeBondt, W. and Thaler, R. (1990). “Do Security Analysts Overreact?” The American Economic Review. 80, 52–57.Google Scholar
Dreman, D. and Berry, M. (1995). “Analyst Forecasting Errors and Their Implications for Security Analysis.” Financial Analysts Journal. 51, 30–40.CrossRefGoogle Scholar
Dwyer, G., Williams, A., Battalio, R., and Mason, T. (1993). “Tests of Rational Expectations in a Stark Setting.” Economic Journal. 103, 586–601.CrossRefGoogle Scholar
Easterwood, J. and Nutt, S. (1999). “Inefficiency in Analysts’ Earnings Forecasts: Systematic Misreaction or Systematic Optimism?” Journal of Finance. 54(5), 1777–1797.CrossRefGoogle Scholar
Elliot, J., Philbrick, D., and Wiedman, C. (1995). “Evidence from Archival Data on the Relation Between Security Analysts’ Forecast Errors and Prior Forecast Revisions.” Contemporary Accounting Research. 11, 919938.CrossRefGoogle Scholar
Francis, J. and Philbrick, D. (1993). “Analysts’ Decisions as Products of a Multi-Task Environment.” Journal of Accounting Research. 31, 216–230.CrossRefGoogle Scholar
Fried, D. and Givoly, D. (1982). “Financial Analysts’ Forecasts of Earnings: A Better Surrogate for Market Expectations.” Journal of Accounting and Economics. 4, 85–107.CrossRefGoogle Scholar
Ganguly, A., Kagel, J., and Moser, D. (1994). “The Effects of Biases in Probability Judgments on Market Prices.” Accounting, Organizations, and Society. 19(8), 675–700.CrossRefGoogle Scholar
Gillette, A., Stevens, D., Watts, S., and Williams, A. (1999). “Price and Volume Reactions to Public Information Releases: An Experimental Approach Incorporating Traders’ Subjective Beliefs.” Contemporary Accounting Research. 16(3), 437–479.CrossRefGoogle Scholar
Hirshleifer, D. (2001). “Investor Psychology and Asset Pricing.” Journal of Finance. 56(4), 1533–1598.Google Scholar
Hong, H. and Stein, J. (1998). “A Unified Theory of Underreaction, Momentum Trading and Overreaction in Asset Markets.” Working Paper, Stanford University.Google Scholar
Kahneman, D. and Tversky, A. (1972). “Subjective Probability: A Judgment of Representativeness.” Cognitive Psychology. 3, 430–454.CrossRefGoogle Scholar
Kahneman, D. and Lovallo, D. (1993). “Timid Choices and Bold Forecasts: A Cognitive Perspective on Risk Taking.” Management Science. 39(1), 17–31.CrossRefGoogle Scholar
Kang, S., O’Brien, J., and Sivaramakrishnan, K. (1994). “Analysts’ Interim Earnings Forecasts: Evidence on the Forecasting Process.” Journal of Accounting Research. 32, 103–112.CrossRefGoogle Scholar
Libby, R., Bloomfield, R., and Nelson, M. (2002). “Experimental Research in Financial Accounting.” Accounting, Organizations, and Society. 27(8), 775–810.CrossRefGoogle Scholar
Lys, T. and Sohn, S. (1990). “The Association Between Revisions of Financial Analysts’ Earnings Forecasts and Security Price Changes.” Journal of Accounting and Economics. 13, 341–364.CrossRefGoogle Scholar
McNichols, M. and O’Brien, P. (1997). “Self-Selection and Analyst Coverage.” Journal of Accounting Research. 35(Suppl.), 167–199.CrossRefGoogle Scholar
Maines, L. and Hand, J. (1996). “Individuals’ Perceptions and Misperceptions of Time Series Properties of Quarterly Earnings.” Accounting Re-view. 71(3), 317–336.Google Scholar
Mear, R. and Firth, M. (1987). “Cue Usage and Self-Insight of Financial Analysts.” Accounting Review. 62, 176–182.Google Scholar
O’Brien, P. (1988). “Analysts’ Forecasts as Earnings Expectations.” Journal of Accounting and Economics. 10, 53–83.CrossRefGoogle Scholar
Schipper, K. (1991). “Analysts’ Forecasts.” Accounting Horizons. 5, 105–121.Google Scholar
Smith, V., Suchanek, G., and Williams, A. (1988). “Bubbles, Crashes, and Endogenous Expectations in Experimental Spot Asset Markets.” Econometrica. 56, 1119–1151.CrossRefGoogle Scholar
Taylor, S. (1991). “Asymmetric Effects of Positive and Negative Events: The Mobilization-Minimization Hypothesis.” Psychological Bulletin. 110(1), 67–85.CrossRefGoogle ScholarPubMed
Tversky, A. and Kahneman, D. (1974). “Judgment Under Uncertainty: Heuristics and Biases.” Science. 185, 1124–1131.CrossRefGoogle ScholarPubMed
Williams, A. (1987). “The Formation of Price Forecasts in Experimental Markets.” Journal of Money, Credit, and Banking. 19, 1–18.CrossRefGoogle Scholar