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Expectation disarray: Analysts' growth forecast anomaly in China

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  • Liu, Laura Xiaolei
  • Zhu, Yandi
  • Zhang, Xinyu
  • Zhang, Yingguang

Abstract

Analysts' growth forecasts positively predict stock returns in China, opposite to the results found in the US. Strategies that buy stocks with high growth forecasts and sell those with low growth forecasts earn annual abnormal returns of up to 20% (with t-values exceeding three). These results are stronger for longer-horizon forecasts and ex-ante more informative forecasts. In addition, the deviation of analysts' forecasts from unbiased forecasts based on statistical models positively predicts abnormal returns. Although the relationship between analysts' forecasts and returns in China is opposite to that in the US, these forecasts positively predict actual growth and are often too extreme, as in the US. Our results suggest that investors in China overlook valuable information contained in analysts' forecasts.

Suggested Citation

  • Liu, Laura Xiaolei & Zhu, Yandi & Zhang, Xinyu & Zhang, Yingguang, 2023. "Expectation disarray: Analysts' growth forecast anomaly in China," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
    • Handle: RePEc:eee:pacfin:v:82:y:2023:i:c:s0927538x23002639
    DOI: 10.1016/j.pacfin.2023.102192
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    1. Jean‐Philippe Bouchaud & Philipp Krüger & Augustin Landier & David Thesmar, 2019. "Sticky Expectations and the Profitability Anomaly," Journal of Finance, American Finance Association, vol. 74(2), pages 639-674, April.
    2. 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.
    3. So, Eric C., 2013. "A new approach to predicting analyst forecast errors: Do investors overweight analyst forecasts?," Journal of Financial Economics, Elsevier, vol. 108(3), pages 615-640.
    4. Han, Chunmao & Shi, Yongdong, 2022. "Chinese stock anomalies and investor sentiment," Pacific-Basin Finance Journal, Elsevier, vol. 73(C).
    5. De Bondt, Werner F M & Thaler, Richard H, 1990. "Do Security Analysts Overreact?," American Economic Review, American Economic Association, vol. 80(2), pages 52-57, May.
    6. Da, Zhi & Warachka, Mitch, 2011. "The disparity between long-term and short-term forecasted earnings growth," Journal of Financial Economics, Elsevier, vol. 100(2), pages 424-442, May.
    7. La Porta, Rafael, 1996. "Expectations and the Cross-Section of Stock Returns," Journal of Finance, American Finance Association, vol. 51(5), pages 1715-1742, December.
    8. Han, Xing & Li, Youwei, 2017. "Can investor sentiment be a momentum time-series predictor? Evidence from China," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 212-239.
    9. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    10. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    11. Kewei Hou & Chen Xue & Lu Zhang, 2020. "Replicating Anomalies," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2019-2133.
    12. Andrew Ang & Robert J. Hodrick & Yuhang Xing & Xiaoyan Zhang, 2006. "The Cross‐Section of Volatility and Expected Returns," Journal of Finance, American Finance Association, vol. 61(1), pages 259-299, February.
    13. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    14. Fama, Eugene F & MacBeth, James D, 1973. "Risk, Return, and Equilibrium: Empirical Tests," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 607-636, May-June.
    15. Jegadeesh, Narasimhan & Titman, Sheridan, 1993. "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency," Journal of Finance, American Finance Association, vol. 48(1), pages 65-91, March.
    16. Pedro Bordalo & Nicola Gennaioli & Rafael La Porta & Andrei Shleifer, 2019. "Diagnostic Expectations and Stock Returns," Journal of Finance, American Finance Association, vol. 74(6), pages 2839-2874, December.
    17. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    18. Guo, Li & Li, Frank Weikai & John Wei, K.C., 2020. "Security analysts and capital market anomalies," Journal of Financial Economics, Elsevier, vol. 137(1), pages 204-230.
    19. repec:bla:jfinan:v:59:y:2004:i:3:p:1083-1124 is not listed on IDEAS
    20. Jules H van Binsbergen & Xiao Han & Alejandro Lopez-Lira, 2023. "Man versus Machine Learning: The Term Structure of Earnings Expectations and Conditional Biases," The Review of Financial Studies, Society for Financial Studies, vol. 36(6), pages 2361-2396.
    21. Scott Richardson & Siew Hong Teoh & Peter D. Wysocki, 2004. "The Walk†down to Beatable Analyst Forecasts: The Role of Equity Issuance and Insider Trading Incentives," Contemporary Accounting Research, John Wiley & Sons, vol. 21(4), pages 885-924, December.
    22. Tim de Silva & David Thesmar, 2021. "Noise in Expectations: Evidence from Analyst Forecasts," NBER Working Papers 28963, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Stock return; Analyst forecast; China; Expectation;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

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