IDEAS home Printed from https://ideas.repec.org/a/spr/reaccs/v16y2011i3d10.1007_s11142-011-9154-7.html
   My bibliography  Save this article

Discussion of “How well do investors understand loss persistence?”

Author

Listed:
  • Robert J. Resutek

    (Dartmouth College–Tuck School of Business)

Abstract

Li (Rev Acc Stud, 2011) proposes a quarterly earnings prediction model for loss generating firms, shows that it produces better specified future earnings estimates relative to naïve quarterly forecast models, and that it can be used to form a trading strategy that produces economically significant annual hedge returns. I discuss alternative perspectives on Li’s empirical results and suggest directions for future research.

Suggested Citation

  • Robert J. Resutek, 2011. "Discussion of “How well do investors understand loss persistence?”," Review of Accounting Studies, Springer, vol. 16(3), pages 668-678, September.
  • Handle: RePEc:spr:reaccs:v:16:y:2011:i:3:d:10.1007_s11142-011-9154-7
    DOI: 10.1007/s11142-011-9154-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11142-011-9154-7
    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/s11142-011-9154-7?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. 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.
    2. Ľuboš Pástor & Veronesi Pietro, 2003. "Stock Valuation and Learning about Profitability," Journal of Finance, American Finance Association, vol. 58(5), pages 1749-1789, October.
    3. Lewellen, Jonathan, 2010. "Accounting anomalies and fundamental analysis: An alternative view," Journal of Accounting and Economics, Elsevier, vol. 50(2-3), pages 455-466, December.
    4. Kent Daniel & Sheridan Titman, 2006. "Market Reactions to Tangible and Intangible Information," Journal of Finance, American Finance Association, vol. 61(4), pages 1605-1643, August.
    5. Fama, Eugene F. & French, Kenneth R., 2004. "New lists: Fundamentals and survival rates," Journal of Financial Economics, Elsevier, vol. 73(2), pages 229-269, August.
    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. Fama, Eugene F & French, Kenneth R, 1992. "The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-465, June.
    8. Balakrishnan, Karthik & Bartov, Eli & Faurel, Lucile, 2010. "Post loss/profit announcement drift," Journal of Accounting and Economics, Elsevier, vol. 50(1), pages 20-41, May.
    9. Barber, Brad M. & Lyon, John D., 1996. "Detecting abnormal operating performance: The empirical power and specification of test statistics," Journal of Financial Economics, Elsevier, vol. 41(3), pages 359-399, July.
    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. Dain C. Donelson & Robert J. Resutek, 2015. "The predictive qualities of earnings volatility and earnings uncertainty," Review of Accounting Studies, Springer, vol. 20(1), pages 470-500, March.
    2. Kewei Hou & Chen Xue & Lu Zhang, 2017. "Replicating Anomalies," NBER Working Papers 23394, National Bureau of Economic Research, Inc.
    3. 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.
    4. Andreou, Christoforos K. & Lambertides, Neophytos & Panayides, Photis M., 2021. "Distress risk anomaly and misvaluation," The British Accounting Review, Elsevier, vol. 53(5).
    5. Wang, Huijun & Yan, Jinghua & Yu, Jianfeng, 2017. "Reference-dependent preferences and the risk–return trade-off," Journal of Financial Economics, Elsevier, vol. 123(2), pages 395-414.
    6. Guo, Hui & Qiu, Buhui, 2014. "Options-implied variance and future stock returns," Journal of Banking & Finance, Elsevier, vol. 44(C), pages 93-113.
    7. Andrew Y. Chen & Tom Zimmermann, 2022. "Open Source Cross-Sectional Asset Pricing," Critical Finance Review, now publishers, vol. 11(2), pages 207-264, May.
    8. Ling Cen & K. C. John Wei & Liyan Yang, 2017. "Disagreement, Underreaction, and Stock Returns," Management Science, INFORMS, vol. 63(4), pages 1214-1231, April.
    9. Amit Goyal, 2012. "Empirical cross-sectional asset pricing: a survey," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 26(1), pages 3-38, March.
    10. 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).
    11. Hung, Weifeng & Chiao, Chaoshin & Liao, Tung Liang & Huang, Sheng-Tang, 2012. "R&D, risks and overreaction in a market with the absence of the book-to-market effect," International Review of Economics & Finance, Elsevier, vol. 22(1), pages 11-24.
    12. Kevin Ke Li, 2011. "How well do investors understand loss persistence?," Review of Accounting Studies, Springer, vol. 16(3), pages 630-667, September.
    13. Hanauer, Matthias X. & Kalsbach, Tobias, 2023. "Machine learning and the cross-section of emerging market stock returns," Emerging Markets Review, Elsevier, vol. 55(C).
    14. Huang, Alan Guoming, 2009. "The cross section of cashflow volatility and expected stock returns," Journal of Empirical Finance, Elsevier, vol. 16(3), pages 409-429, June.
    15. Guo, Hui & Savickas, Robert, 2010. "Relation between time-series and cross-sectional effects of idiosyncratic variance on stock returns," Journal of Banking & Finance, Elsevier, vol. 34(7), pages 1637-1649, July.
    16. Clifford S. Asness & Andrea Frazzini & Lasse Heje Pedersen, 2019. "Quality minus junk," Review of Accounting Studies, Springer, vol. 24(1), pages 34-112, March.
    17. Jiang, Hao, 2010. "Institutional investors, intangible information, and the book-to-market effect," Journal of Financial Economics, Elsevier, vol. 96(1), pages 98-126, April.
    18. Lam, F.Y. Eric C. & Wei, K.C. John, 2011. "Limits-to-arbitrage, investment frictions, and the asset growth anomaly," Journal of Financial Economics, Elsevier, vol. 102(1), pages 127-149, October.
    19. Jiang, Danling, 2006. "Investor Overreaction, Cross-Sectional Dispersion of Firm Valuations, and Expected Stock Returns," Working Paper Series 2006-8, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    20. Hirshleifer, David & Hsu, Po-Hsuan & Li, Dongmei, 2013. "Innovative efficiency and stock returns," Journal of Financial Economics, Elsevier, vol. 107(3), pages 632-654.

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage
    • G29 - Financial Economics - - Financial Institutions and Services - - - Other
    • M41 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Accounting

    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:16:y:2011:i:3:d:10.1007_s11142-011-9154-7. 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.