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Robust Measures of Earnings Surprises

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  • CHIN‐HAN CHIANG
  • WEI DAI
  • JIANQING FAN
  • HARRISON HONG
  • JUN TU

Abstract

Event studies of market efficiency measure earnings surprises using the consensus error (CE), given as actual earnings minus the average professional forecast. If a subset of forecasts can be biased, the ideal but difficult to estimate parameter‐dependent alternative to CE is a nonlinear filter of individual errors that adjusts for bias. We show that CE is a poor parameter‐free approximation of this ideal measure. The fraction of misses on the same side (FOM), which discards the magnitude of misses, offers a far better approximation. FOM performs particularly well against CE in predicting the returns of U.S. stocks, where bias is potentially large.

Suggested Citation

  • Chin‐Han Chiang & Wei Dai & Jianqing Fan & Harrison Hong & Jun Tu, 2019. "Robust Measures of Earnings Surprises," Journal of Finance, American Finance Association, vol. 74(2), pages 943-983, April.
    • Handle: RePEc:bla:jfinan:v:74:y:2019:i:2:p:943-983
    DOI: 10.1111/jofi.12746
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    1. Zdeněk Zmeškal & Dana Dluhošová & Karolina Lisztwanová & Antonín Pončík & Iveta Ratmanová, 2023. "Distribution Prediction of Decomposed Relative EVA Measure with Levy-Driven Mean-Reversion Processes: The Case of an Automotive Sector of a Small Open Economy," Forecasting, MDPI, vol. 5(2), pages 1-19, May.
    2. Chandan Sharma & Archana Singh & Rajan Yadav, 2023. "Impact of Competition in Credit Rating Industry: Evidence From India," SAGE Open, , vol. 13(1), pages 21582440221, January.
    3. Cahill, Daniel & Ho, Choy Yeing (Chloe) & Yang, Joey W., 2022. "The COVID-19 pandemic: How important is face-to-face interaction for information dissemination?," Global Finance Journal, Elsevier, vol. 54(C).
    4. Ni, Xiaoran & Peng, Qiyuan & Yin, Sirui & Zhang, Ting, 2020. "Attention! Distracted institutional investors and stock price crash," Journal of Corporate Finance, Elsevier, vol. 64(C).
    5. Han, Chulwoo & Kang, Jangkoo & Kim, Sun Yung, 2022. "Betting against analyst target price," Journal of Financial Markets, Elsevier, vol. 59(PB).
    6. Cao, An N.Q. & Heckelei, Thomas & Ionici, Octavian & Robe, Michel A., 2024. "USDA reports affect the stock market, too," Journal of Commodity Markets, Elsevier, vol. 34(C).
    7. Koppenberg, Maximilian & Hirsch, Stefan & Finger, Robert, 2023. "Effects of the debate on glyphosate's carcinogenic risk on pesticide producers' share prices," Ecological Economics, Elsevier, vol. 212(C).
    8. Alan D. Jagolinzer, 2024. "Market and regulatory implications of social identity cohorts: a discussion of crypto influencers," Review of Accounting Studies, Springer, vol. 29(3), pages 2298-2317, September.
    9. John Ammer & John Rogers & Gang Wang & Yang Yu, 2020. "Monetary Policy Expectations, Fund Managers, and Fund Returns: Evidence from China," International Finance Discussion Papers 1285, Board of Governors of the Federal Reserve System (U.S.).
    10. John Ammer & John Rogers & Gang Wang & Yang Yu, 2023. "Chinese Asset Managers’ Monetary Policy Forecasts and Fund Performance," Management Science, INFORMS, vol. 69(1), pages 598-616, January.
    11. Merkley, Kenneth & Michaely, Roni & Pacelli, Joseph, 2020. "Cultural diversity on Wall Street: Evidence from consensus earnings forecasts," Journal of Accounting and Economics, Elsevier, vol. 70(1).
    12. Andrew C. Call & Max Hewitt & Jessica Watkins & Teri Lombardi Yohn, 2021. "Analysts’ annual earnings forecasts and changes to the I/B/E/S database," Review of Accounting Studies, Springer, vol. 26(1), pages 1-36, March.

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