IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v86y2025ipes1544612325020057.html

Beyond the last surprise: Reviving PEAD with machine learning and historical earnings

Author

Listed:
  • Kaczmarek, Tomasz
  • Zaremba, Adam

Abstract

How much information about future returns is hidden in a stock’s earnings surprises history? To answer this, we use elastic net models that extract information from multiple quarters of standardized unexpected earnings (SUE). We find that accounting for earnings patterns from the distant past substantially improves return forecasts: Sharpe ratios nearly double, and alphas remain significant even after controlling for one-quarter SUE and streak effects. While the traditional post-earnings-announcement drift (PEAD) anomaly has weakened, our approach effectively revives it. Gains are especially strong among large-cap stocks, where the latest surprises are quickly priced in, but older ones remain overlooked.

Suggested Citation

  • Kaczmarek, Tomasz & Zaremba, Adam, 2025. "Beyond the last surprise: Reviving PEAD with machine learning and historical earnings," Finance Research Letters, Elsevier, vol. 86(PE).
    • Handle: RePEc:eee:finlet:v:86:y:2025:i:pe:s1544612325020057
    DOI: 10.1016/j.frl.2025.108751
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612325020057
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2025.108751?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Cakici, Nusret & Zaremba, Adam, 2022. "Salience theory and the cross-section of stock returns: International and further evidence," Journal of Financial Economics, Elsevier, vol. 146(2), pages 689-725.
    2. Mingyi Hung & Xi Li & Shiheng Wang, 2015. "Post-Earnings-Announcement Drift in Global Markets: Evidence from an Information Shock," The Review of Financial Studies, Society for Financial Studies, vol. 28(4), pages 1242-1283.
    3. Fink, Josef, 2021. "A review of the Post-Earnings-Announcement Drift," Journal of Behavioral and Experimental Finance, Elsevier, vol. 29(C).
    4. Bernard, Victor L. & Thomas, Jacob K., 1990. "Evidence that stock prices do not fully reflect the implications of current earnings for future earnings," Journal of Accounting and Economics, Elsevier, vol. 13(4), pages 305-340, December.
    5. 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.
    6. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    7. Kewei Hou & Chen Xue & Lu Zhang, 2020. "Replicating Anomalies," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2019-2133.
    8. Bernard, Vl & Thomas, Jk, 1989. "Post-Earnings-Announcement Drift - Delayed Price Response Or Risk Premium," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 27, pages 1-36.
    9. Ball, R & Brown, P, 1968. "Empirical Evaluation Of Accounting Income Numbers," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 6(2), pages 159-178.
    10. Martineau, Charles, 2021. "Rest in Peace Post-Earnings Announcement Drift," SocArXiv z7k3p, Center for Open Science.
    11. repec:osf:socarx:z7k3p_v1 is not listed on IDEAS
    12. Avramov, Doron & Chordia, Tarun & Jostova, Gergana & Philipov, Alexander, 2013. "Anomalies and financial distress," Journal of Financial Economics, Elsevier, vol. 108(1), pages 139-159.
    13. Roger K. Loh & Mitch Warachka, 2012. "Streaks in Earnings Surprises and the Cross-Section of Stock Returns," Management Science, INFORMS, vol. 58(7), pages 1305-1321, July.
    14. Stambaugh, Robert F. & Yu, Jianfeng & Yuan, Yu, 2012. "The short of it: Investor sentiment and anomalies," Journal of Financial Economics, Elsevier, vol. 104(2), pages 288-302.
    15. Du, Xiuli & Ao, Zhu & Chai, Yiwei & Ge, Shilong, 2023. "Economic policy uncertainty, investor attention and post-earnings announcement drift," International Review of Financial Analysis, Elsevier, vol. 87(C).
    16. Hui Zou & Trevor Hastie, 2005. "Addendum: Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(5), pages 768-768, November.
    17. Theis Ingerslev Jensen & Bryan Kelly & Lasse Heje Pedersen, 2023. "Is There a Replication Crisis in Finance?," Journal of Finance, American Finance Association, vol. 78(5), pages 2465-2518, October.
    18. Joshua Livnat & Richard R. Mendenhall, 2006. "Comparing the Post–Earnings Announcement Drift for Surprises Calculated from Analyst and Time Series Forecasts," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 44(1), pages 177-205, March.
    19. Meursault, Vitaly & Liang, Pierre Jinghong & Routledge, Bryan R. & Scanlon, Madeline Marco, 2023. "PEAD.txt: Post-Earnings-Announcement Drift Using Text," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 58(6), pages 2299-2326, September.
    20. Lan, Qiujun & Xie, Yuxuan & Mi, Xianhua & Zhang, Chunyu, 2024. "Post earnings announcement drift: A simple earnings surprise measure, the medium effect of investor attention and investing strategy," International Review of Financial Analysis, Elsevier, vol. 95(PB).
    21. Kim, Dongcheol & Kim, Myungsun, 2003. "A Multifactor Explanation of Post-Earnings Announcement Drift," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 38(2), pages 383-398, June.
    22. Kim, Jeong-Bon & Li, Liuchuang & Yu, Zhongbo & Zhang, Hao, 2019. "Local versus non-local effects of Chinese media and post-earnings announcement drift," Journal of Banking & Finance, Elsevier, vol. 106(C), pages 82-92.
    23. David Hirshleifer & Sonya Seongyeon Lim & Siew Hong Teoh, 2009. "Driven to Distraction: Extraneous Events and Underreaction to Earnings News," Journal of Finance, American Finance Association, vol. 64(5), pages 2289-2325, October.
    24. Hollstein, Fabian, 2022. "The world of anomalies: Smaller than we think?," Journal of International Money and Finance, Elsevier, vol. 129(C).
    25. Hui Zou & Trevor Hastie, 2005. "Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(2), pages 301-320, April.
    26. Alexander Barinov & Shawn Saeyeul Park & Çelim Yıldızhan, 2024. "Firm complexity and post-earnings announcement drift," Review of Accounting Studies, Springer, vol. 29(1), pages 527-579, March.
    27. Xi Li & Mingyi Hung & Shiheng Wang, 2015. "Post-Earnings-Announcement Drift in Global Markets: Evidence from an Information Shock," HKUST IEMS Working Paper Series 2015-17, HKUST Institute for Emerging Market Studies, revised Mar 2015.
    28. Zhang, Sijia & Gregoriou, Andros & Wu, He, 2024. "Asymmetric post earnings announcement drift and order flow imbalance: The impact on stock market returns," International Review of Financial Analysis, Elsevier, vol. 94(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Doron Avramov & Guy Kaplanski & Avanidhar Subrahmanyam, 2022. "Postfundamentals Price Drift in Capital Markets: A Regression Regularization Perspective," Management Science, INFORMS, vol. 68(10), pages 7658-7681, October.
    2. Fink, Josef, 2021. "A review of the Post-Earnings-Announcement Drift," Journal of Behavioral and Experimental Finance, Elsevier, vol. 29(C).
    3. repec:grz:wpsses:2020-04 is not listed on IDEAS
    4. repec:osf:socarx:z7k3p_v1 is not listed on IDEAS
    5. Stephen Karolyi & Thomas Ruchti & Phong Truong, 2025. "Number Processing Constraints and Earnings News," Management Science, INFORMS, vol. 71(3), pages 2413-2442, March.
    6. Lan, Qiujun & Xie, Yuxuan & Mi, Xianhua & Zhang, Chunyu, 2024. "Post earnings announcement drift: A simple earnings surprise measure, the medium effect of investor attention and investing strategy," International Review of Financial Analysis, Elsevier, vol. 95(PB).
    7. Yu Zhu & Xiao Liu & Olivia R. Liu Sheng, 2025. "Post-Earnings-Announcement Drift Prediction: Leveraging Postevent Investor Responses with Multitask Learning," Information Systems Research, INFORMS, vol. 36(4), pages 2191-2212, December.
    8. Martineau, Charles, 2021. "Rest in Peace Post-Earnings Announcement Drift," SocArXiv z7k3p, Center for Open Science.
    9. Ho, Tuan Q. & Nguyen, Y. & Tran, Hieu, 2024. "The impact of insider ownership and institutional ownership on post-earnings-announcement-drift: Evidence from Vietnam," Research in International Business and Finance, Elsevier, vol. 70(PB).
    10. Xin Chen & Wei He & Libin Tao & Jianfeng Yu, 2023. "Attention and Underreaction-Related Anomalies," Management Science, INFORMS, vol. 69(1), pages 636-659, January.
    11. Cakici, Nusret & Fieberg, Christian & Metko, Daniel & Zaremba, Adam, 2025. "Factor momentum versus price momentum: Insights from international markets," Journal of Banking & Finance, Elsevier, vol. 170(C).
    12. repec:grz:wpsses:2020-03 is not listed on IDEAS
    13. Li, Zhuo & Wen, Fenghua & Huang, Zhijian James, 2023. "Asymmetric response to earnings news across different sentiment states: The role of cognitive dissonance," Journal of Corporate Finance, Elsevier, vol. 78(C).
    14. Cakici, Nusret & Shahzad, Syed Jawad Hussain & Będowska-Sójka, Barbara & Zaremba, Adam, 2024. "Machine learning and the cross-section of cryptocurrency returns," International Review of Financial Analysis, Elsevier, vol. 94(C).
    15. Fink, Josef & Palan, Stefan & Theissen, Erik, 2024. "Earnings Autocorrelation and the Post-Earnings-Announcement Drift: Experimental Evidence," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 59(6), pages 2799-2837, September.
    16. Guanming He, 2021. "Credit rating, post‐earnings‐announcement drift, and arbitrage from transient institutions," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 48(7-8), pages 1434-1467, July.
    17. Tao Chen & Robert K. Larson & Han Mo, 2024. "Investor Herding and Price Informativeness in Global Markets: Evidence from Earnings Announcements," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 25(1), pages 92-110, January.
    18. Lin, Mei-Chen, 2024. "Salience, psychological anchors, and stock return predictability," Pacific-Basin Finance Journal, Elsevier, vol. 88(C).
    19. Chen, Linda H. & Jiang, George J. & Zhu, Kevin X., 2018. "Total attention: The effect of macroeconomic news on market reaction to earnings news," Journal of Banking & Finance, Elsevier, vol. 97(C), pages 142-156.
    20. Liu, Mengxi (Maggie) & Chan, Kam Fong & Faff, Robert, 2022. "What can we learn from firm-level jump-induced tail risk around earnings announcements?," Journal of Banking & Finance, Elsevier, vol. 138(C).
    21. Blankespoor, Elizabeth & deHaan, Ed & Marinovic, Iván, 2020. "Disclosure processing costs, investors’ information choice, and equity market outcomes: A review," Journal of Accounting and Economics, Elsevier, vol. 70(2).
    22. Juwon Jang & Eunju Lee, 2021. "Do record earnings affect market reactions to earnings news?," Review of Quantitative Finance and Accounting, Springer, vol. 56(4), pages 1259-1287, May.
    23. Jiang, George J. & Zhu, Kevin X., 2017. "Information Shocks and Short-Term Market Underreaction," Journal of Financial Economics, Elsevier, vol. 124(1), pages 43-64.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • G00 - Financial Economics - - General - - - General
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:finlet:v:86:y:2025:i:pe:s1544612325020057. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.