IDEAS home Printed from https://ideas.repec.org/a/spr/reaccs/v30y2025i1d10.1007_s11142-023-09812-6.html
   My bibliography  Save this article

Predictable EPS growth and the performance of value investing

Author

Listed:
  • Richard G. Sloan

    (University of Southern California)

  • Annika Yu Wang

    (Bauer College of Business, University of Houston)

Abstract

Previous research finds that EPS growth rates are difficult to predict and reasons that much of the observed cross-sectional variation in valuation ratios is due to variation in implied future stock returns. Yet the observed cross-sectional relation between valuation ratios and realized future stock returns is weak. We revisit these findings using a refined measure of expected EPS growth rates and document robust evidence of predictability in EPS growth rates. Moreover, we find that this predictable growth extends beyond two years into the future and is strongly reflected in observed valuation ratios. We show that combining valuation ratios with our refined measure of expected EPS growth rates improves forecasts of stock returns, though return predictability remains weak. Thus, we conclude that most of the variation in valuation ratios is driven by predictable EPS growth.

Suggested Citation

  • Richard G. Sloan & Annika Yu Wang, 2025. "Predictable EPS growth and the performance of value investing," Review of Accounting Studies, Springer, vol. 30(1), pages 33-78, March.
    • Handle: RePEc:spr:reaccs:v:30:y:2025:i:1:d:10.1007_s11142-023-09812-6
    DOI: 10.1007/s11142-023-09812-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11142-023-09812-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11142-023-09812-6?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 search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. R. David Mclean & Jeffrey Pontiff, 2016. "Does Academic Research Destroy Stock Return Predictability?," Journal of Finance, American Finance Association, vol. 71(1), pages 5-32, February.
    4. Jerald E. Pinto & Thomas R. Robinson & John D. Stowe, 2019. "Equity valuation: A survey of professional practice," Review of Financial Economics, John Wiley & Sons, vol. 37(2), pages 219-233, April.
    5. Patricia M. Dechow & Ryan D. Erhard & Richard G. Sloan & And Mark T. Soliman, 2021. "Implied Equity Duration: A Measure of Pandemic Shutdown Risk," Journal of Accounting Research, Wiley Blackwell, vol. 59(1), pages 243-281, March.
    6. 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.
    7. Lakonishok, Josef & Shleifer, Andrei & Vishny, Robert W, 1994. "Contrarian Investment, Extrapolation, and Risk," Journal of Finance, American Finance Association, vol. 49(5), pages 1541-1578, December.
    8. Ball, Ray & Gerakos, Joseph & Linnainmaa, Juhani T. & Nikolaev, Valeri, 2020. "Earnings, retained earnings, and book-to-market in the cross section of expected returns," Journal of Financial Economics, Elsevier, vol. 135(1), pages 231-254.
    9. Rouen, Ethan & So, Eric C. & Wang, Charles C.Y., 2021. "Core earnings: New data and evidence," Journal of Financial Economics, Elsevier, vol. 142(3), pages 1068-1091.
    10. Lawrence Kryzanowski & Sana Mohsni, 2014. "Persistence and current determinants of the future earnings growth rates of firms," The European Journal of Finance, Taylor & Francis Journals, vol. 20(2), pages 181-200, February.
    11. Mitchell A. Petersen, 2009. "Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches," The Review of Financial Studies, Society for Financial Studies, vol. 22(1), pages 435-480, January.
    12. U-Wen Kok & Jason Ribando & Richard Sloan, 2017. "Facts about Formulaic Value Investing," Financial Analysts Journal, Taylor & Francis Journals, vol. 73(2), pages 81-99, April.
    13. Penman, SH, 1996. "The articulation of price-earnings ratios and market-to-book ratios and the evaluation of growth," Journal of Accounting Research, Wiley Blackwell, vol. 34(2), pages 235-259.
    14. Louis K. C. Chan & Jason Karceski & Josef Lakonishok, 2003. "The Level and Persistence of Growth Rates," Journal of Finance, American Finance Association, vol. 58(2), pages 643-684, April.
    15. Mark T. Bradshaw & Richard G. Sloan, 2002. "GAAP versus The Street: An Empirical Assessment of Two Alternative Definitions of Earnings," Journal of Accounting Research, Wiley Blackwell, vol. 40(1), pages 41-66, March.
    16. Shumway, Tyler, 1997. "The Delisting Bias in CRSP Data," Journal of Finance, American Finance Association, vol. 52(1), pages 327-340, March.
    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. Hou, Kewei & Xue, Chen & Zhang, Lu, 2017. "Replicating Anomalies," Working Paper Series 2017-10, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    2. Papanastasopoulos, Georgios & Thomakos, Dimitrios & Wang, Tao, 2011. "Information in balance sheets for future stock returns: Evidence from net operating assets," International Review of Financial Analysis, Elsevier, vol. 20(5), pages 269-282.
    3. Tobek, Ondrej & Hronec, Martin, 2021. "Does it pay to follow anomalies research? Machine learning approach with international evidence," Journal of Financial Markets, Elsevier, vol. 56(C).
    4. 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.
    5. Jozef Barunik & Martin Hronec & Ondrej Tobek, 2024. "Predicting the distributions of stock returns around the globe in the era of big data and learning," Papers 2408.07497, arXiv.org.
    6. Kryzanowski, Lawrence & Mohsni, Sana, 2015. "Earnings forecasts and idiosyncratic volatilities," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 107-123.
    7. Zhi Da & Ravi Jagannathan & Jianfeng Shen, 2012. "Building Castles in the Air: Evidence from Industry IPO Waves," NBER Working Papers 18555, National Bureau of Economic Research, Inc.
    8. Kevin Aretz & Marc Aretz, 2016. "Which stocks drive the size, value, and momentum anomalies and for how long? Evidence from a statistical leverage analysis," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 30(1), pages 19-61, February.
    9. Chau Duong & Gioia Pescetto & Daniel Santamaria, 2014. "How value-glamour investors use financial information: UK evidence of investors' confirmation bias," The European Journal of Finance, Taylor & Francis Journals, vol. 20(6), pages 524-549, June.
    10. Kaplanski, Guy, 2023. "The race to exploit anomalies and the cost of slow trading," Journal of Financial Markets, Elsevier, vol. 62(C).
    11. Wang, Feifei & Yan, Xuemin Sterling, 2021. "Downside risk and the performance of volatility-managed portfolios," Journal of Banking & Finance, Elsevier, vol. 131(C).
    12. 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.
    13. Eero Pätäri & Timo Leivo, 2017. "A Closer Look At Value Premium: Literature Review And Synthesis," Journal of Economic Surveys, Wiley Blackwell, vol. 31(1), pages 79-168, February.
    14. Gardner, Jesse & Sloan, Richard G. & Yoon, Joon Sang, 2024. "Distinguishing between recurring and nonrecurring components of earnings using unobserved components modeling," Journal of Accounting and Economics, Elsevier, vol. 78(1).
    15. Cederburg, Scott & O’Doherty, Michael S. & Wang, Feifei & Yan, Xuemin (Sterling), 2020. "On the performance of volatility-managed portfolios," Journal of Financial Economics, Elsevier, vol. 138(1), pages 95-117.
    16. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, December.
    17. Andrew Y. Chen & Tom Zimmermann, 2022. "Open Source Cross-Sectional Asset Pricing," Critical Finance Review, now publishers, vol. 11(2), pages 207-264, May.
    18. Hoang, Khoa & Huang, Ronghong & Truong, Helen, 2023. "Resurrecting the market factor: A case of data mining across international markets," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
    19. Gikas Hardouvelis & Georgios Papanastasopoulos & Dimitrios Thomakos & Tao Wang, 2012. "External Financing, Growth and Stock Returns," European Financial Management, European Financial Management Association, vol. 18(5), pages 790-815, November.
    20. Linnenluecke, Martina K. & Chen, Xiaoyan & Ling, Xin & Smith, Tom & Zhu, Yushu, 2017. "Research in finance: A review of influential publications and a research agenda," Pacific-Basin Finance Journal, Elsevier, vol. 43(C), pages 188-199.

    More about this item

    Keywords

    Earnings; Growth; Value; Analyst forecasts;
    All these keywords.

    JEL classification:

    • M41 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Accounting
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

    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:spr:reaccs:v:30:y:2025:i:1:d:10.1007_s11142-023-09812-6. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.