IDEAS home Printed from https://ideas.repec.org/a/wly/coacre/v38y2021i1p518-544.html
   My bibliography  Save this article

Sentiment, Loss Firms, and Investor Expectations of Future Earnings

Author

Listed:
  • Edward J. Riedl
  • Estelle Y. Sun
  • Guannan Wang

Abstract

This study investigates the mispricing of market‐wide investor sentiment by exploring the relation between sentiment and investor expectations of future earnings. Prior research argues that sentiment‐driven mispricing should be most pronounced for hard‐to‐value firms, such as those reporting losses (Baker and Wurgler 2006). Using investor expectations of future earnings, we provide empirical results consistent with this behavioral finance theory. We predict and find that investors perceive losses to be more (less) persistent during periods of low (high) sentiment; that (in contrast) investors perceive profit persistence to be lower (higher) during periods of low (high) sentiment; and that the effects appear stronger for loss firms relative to profit firms. We also document predictable cross‐sectional variation within losses (with the mispricing mitigated for losses associated with activities expected to generate future benefits), R&D, growth, large negative special items, and severe financial distress. Overall, our results document a new and important channel—investor expectations of future earnings—to explain sentiment‐driven mispricing. Confiance des investisseurs, sociétés affichant des pertes et attentes des investisseurs quant aux résultats futurs Les auteurs s'interrogent sur les erreurs d’évaluation de la confiance des investisseurs dans l'ensemble du marché en analysant la relation entre la confiance et les attentes des investisseurs quant aux résultats futurs. Selon de précédentes études, les erreurs d’évaluation découlant de la confiance devraient être particulièrement marquées dans le cas des sociétés difficiles à évaluer, comme celles qui déclarent des pertes (Baker et Wurgler 2006). Les constatations empiriques qui se dégagent de l'utilisation des attentes des investisseurs quant aux résultats futurs sont conformes à cette théorie de la finance comportementale. Les auteurs formulent et confirment les hypothèses suivantes : les investisseurs perçoivent les pertes comme étant plus (moins) persistantes durant les périodes où la confiance est faible (élevée) ; les investisseurs perçoivent par ailleurs la persistance des profits comme étant faible (élevée) durant les périodes où la confiance est faible (élevée) ; et ces observations semblent plus marquées dans le cas des sociétés affichant des pertes que dans celui des sociétés affichant des profits. Les auteurs documentent également une variation transversale prévisible en ce qui a trait aux pertes, l'erreur d’évaluation étant moindre pour les pertes associées aux activités susceptibles d'engendrer ultérieurement des avantages : R&D, croissance, éléments exceptionnels négatifs importants et difficultés financières graves. Dans l'ensemble, les résultats qu'obtiennent les auteurs viennent étayer l'idée nouvelle et importante selon laquelle les attentes des investisseurs quant aux résultats futurs peuvent expliquer les erreurs d’évaluation découlant de la confiance.

Suggested Citation

  • Edward J. Riedl & Estelle Y. Sun & Guannan Wang, 2021. "Sentiment, Loss Firms, and Investor Expectations of Future Earnings," Contemporary Accounting Research, John Wiley & Sons, vol. 38(1), pages 518-544, March.
  • Handle: RePEc:wly:coacre:v:38:y:2021:i:1:p:518-544
    DOI: 10.1111/1911-3846.12618
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/1911-3846.12618
    Download Restriction: no

    File URL: https://libkey.io/10.1111/1911-3846.12618?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
    ---><---

    References listed on IDEAS

    as
    1. Jördis Hengelbrock & Erik Theissen & Christian Westheide, 2013. "Market Response to Investor Sentiment," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 40(7-8), pages 901-917, September.
    2. Dilip Abreu & Markus K. Brunnermeier, 2003. "Bubbles and Crashes," Econometrica, Econometric Society, vol. 71(1), pages 173-204, January.
    3. Lin, Hsiou-wei & McNichols, Maureen F., 1998. "Underwriting relationships, analysts' earnings forecasts and investment recommendations," Journal of Accounting and Economics, Elsevier, vol. 25(1), pages 101-127, February.
    4. Edward J. Riedl & Suraj Srinivasan, 2010. "Signaling Firm Performance Through Financial Statement Presentation: An Analysis Using Special Items," Contemporary Accounting Research, John Wiley & Sons, vol. 27(1), pages 8-8, March.
    5. Amitabh Dugar & Siva Nathan, 1995. "The Effect of Investment Banking Relationships on Financial Analysts' Earnings Forecasts and Investment Recommendations," Contemporary Accounting Research, John Wiley & Sons, vol. 12(1), pages 131-160, September.
    6. Frederic S. Mishkin, 1983. "A Rational Expectations Approach to Macroeconometrics: Testing Policy Ineffectiveness and Efficient-Markets Models," NBER Books, National Bureau of Economic Research, Inc, number mish83-1, March.
    7. Peter D. Easton & Gregory A. Sommers, 2007. "Effect of Analysts' Optimism on Estimates of the Expected Rate of Return Implied by Earnings Forecasts," Journal of Accounting Research, Wiley Blackwell, vol. 45(5), pages 983-1015, December.
    8. Gregory W. Brown & Michael T. Cliff, 2005. "Investor Sentiment and Asset Valuation," The Journal of Business, University of Chicago Press, vol. 78(2), pages 405-440, March.
    9. Kaplanski, Guy & Levy, Haim, 2017. "Analysts and sentiment: A causality study," The Quarterly Review of Economics and Finance, Elsevier, vol. 63(C), pages 315-327.
    10. Edward J. Riedl & Suraj Srinivasan, 2010. "Signaling Firm Performance Through Financial Statement Presentation: An Analysis Using Special Items," Contemporary Accounting Research, John Wiley & Sons, vol. 27(1), pages 289-332, March.
    11. Malcolm Baker & Jeffrey Wurgler, 2007. "Investor Sentiment in the Stock Market," Journal of Economic Perspectives, American Economic Association, vol. 21(2), pages 129-152, Spring.
    12. Arthur Kraft & Andrew J. Leone & Charles E. Wasley, 2007. "Regression‐Based Tests of the Market Pricing of Accounting Numbers: The Mishkin Test and Ordinary Least Squares," Journal of Accounting Research, Wiley Blackwell, vol. 45(5), pages 1081-1114, December.
    13. Jeffrey J. Coulton & Tami Dinh & Andrew B. Jackson & Tom Smith, 2016. "The impact of sentiment on price discovery," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 56(3), pages 669-694, September.
    14. Frederic S. Mishkin, 1983. "Introduction to "A Rational Expectations Approach to Macroeconometrics: Testing Policy Ineffectiveness and Efficient-Markets Models"," NBER Chapters, in: A Rational Expectations Approach to Macroeconometrics: Testing Policy Ineffectiveness and Efficient-Markets Models, pages 1-6, National Bureau of Economic Research, Inc.
    15. Marcus Burger & Asher Curtis, 2017. "Aggregate Margin Debt and the Divergence of Price from Accounting Fundamentals," Contemporary Accounting Research, John Wiley & Sons, vol. 34(3), pages 1418-1445, September.
    16. David Burgstahler & James Jiambalvo & Terry Shevlin, 2002. "Do Stock Prices Fully Reflect the Implications of Special Items for Future Earnings?," Journal of Accounting Research, Wiley Blackwell, vol. 40(3), pages 585-612, June.
    17. D. Craig Nichols & James M. Wahlen & Matthew M. Wieland, 2017. "Pricing and Mispricing of Accounting Fundamentals in the Time†Series and in the Cross Section," Contemporary Accounting Research, John Wiley & Sons, vol. 34(3), pages 1378-1417, September.
    18. Geczy, Christopher C. & Musto, David K. & Reed, Adam V., 2002. "Stocks are special too: an analysis of the equity lending market," Journal of Financial Economics, Elsevier, vol. 66(2-3), pages 241-269.
    19. Jones, Charles M. & Lamont, Owen A., 2002. "Short-sale constraints and stock returns," Journal of Financial Economics, Elsevier, vol. 66(2-3), pages 207-239.
    20. Francis, J & Hanna, JD & Vincent, L, 1996. "Causes and effects of discretionary asset write-offs," Journal of Accounting Research, Wiley Blackwell, vol. 34, pages 117-134.
    21. Franzen, Laurel & Radhakrishnan, Suresh, 2009. "The value relevance of R&D across profit and loss firms," Journal of Accounting and Public Policy, Elsevier, vol. 28(1), pages 16-32.
    22. Alexander Kurov, 2008. "Investor Sentiment, Trading Behavior and Informational Efficiency in Index Futures Markets," The Financial Review, Eastern Finance Association, vol. 43(1), pages 107-127, February.
    23. Nittai K. Bergman & Sugata Roychowdhury, 2008. "Investor Sentiment and Corporate Disclosure," Journal of Accounting Research, Wiley Blackwell, vol. 46(5), pages 1057-1083, December.
    24. 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.
    25. Paul Hribar & John McInnis, 2012. "Investor Sentiment and Analysts' Earnings Forecast Errors," Management Science, INFORMS, vol. 58(2), pages 293-307, February.
    26. Michael Lemmon & Evgenia Portniaguina, 2006. "Consumer Confidence and Asset Prices: Some Empirical Evidence," The Review of Financial Studies, Society for Financial Studies, vol. 19(4), pages 1499-1529.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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).
    2. Feng Gu & Baruch Lev & Chenqi Zhu, 2023. "All losses are not alike: Real versus accounting-driven reported losses," Review of Accounting Studies, Springer, vol. 28(3), pages 1141-1189, September.
    3. Ho, Kung-Cheng & Yang, Lu & Luo, Sijia, 2022. "Information disclosure ratings and continuing overreaction: Evidence from the Chinese capital market," Journal of Business Research, Elsevier, vol. 140(C), pages 638-656.

    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. Sami Keskek & James N. Myers & Linda A. Myers, 2020. "Investors' Misweighting of Firm‐Level Information and the Market's Expectations of Earnings," Contemporary Accounting Research, John Wiley & Sons, vol. 37(3), pages 1828-1853, September.
    2. Corredor, Pilar & Ferrer, Elena & Santamaria, Rafael, 2014. "Is cognitive bias really present in analyst forecasts? The role of investor sentiment," International Business Review, Elsevier, vol. 23(4), pages 824-837.
    3. Thomas J. Lopez & Craig A. Sisneros & Trevor Sorensen, 2020. "The market pricing of negative special items through time: an unintended consequence of regulation change?," Review of Quantitative Finance and Accounting, Springer, vol. 54(2), pages 753-777, February.
    4. Keval Amin & Erica Harris, 2022. "The Effect of Investor Sentiment on Nonprofit Donations," Journal of Business Ethics, Springer, vol. 175(2), pages 427-450, January.
    5. John Garcia, 2021. "Analyst herding and firm-level investor sentiment," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 35(4), pages 461-494, December.
    6. Lu, Hsueh-Tien, 2018. "Voluntary disclosure and the pricing of earnings components," Journal of Behavioral and Experimental Finance, Elsevier, vol. 20(C), pages 64-73.
    7. Markus Buxbaum & Wolfgang Schultze & Samuel L. Tiras, 2023. "Do analysts’ target prices stabilize the stock market?," Review of Quantitative Finance and Accounting, Springer, vol. 61(3), pages 763-816, October.
    8. Gongmeng Chen & Michael Firth & Daniel Ning Gao, 2011. "The Information Content of Earnings Components: Evidence from the Chinese Stock Market," European Accounting Review, Taylor & Francis Journals, vol. 20(4), pages 669-692, May.
    9. Mahmoudi, Nader & Docherty, Paul & Melia, Adrian, 2022. "Firm-level investor sentiment and corporate announcement returns," Journal of Banking & Finance, Elsevier, vol. 144(C).
    10. Szymon Lis, 2022. "Investor Sentiment in Asset Pricing Models: A Review," Working Papers 2022-14, Faculty of Economic Sciences, University of Warsaw.
    11. Mei-Chen Lin & J. Jimmy Yang, 2023. "Do lottery characteristics matter for analysts’ forecast behavior?," Review of Quantitative Finance and Accounting, Springer, vol. 61(3), pages 1057-1091, October.
    12. Corredor, Pilar & Ferrer, Elena & Santamaria, Rafael, 2019. "The role of sentiment and stock characteristics in the translation of analysts’ forecasts into recommendations," The North American Journal of Economics and Finance, Elsevier, vol. 49(C), pages 252-272.
    13. Shen, Junyan & Yu, Jianfeng & Zhao, Shen, 2017. "Investor sentiment and economic forces," Journal of Monetary Economics, Elsevier, vol. 86(C), pages 1-21.
    14. Zhou, Xuemei & Liu, Qiang & Guo, Shuxin, 2021. "Do overnight returns explain firm-specific investor sentiment in China?," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 451-477.
    15. 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.
    16. Hung, Pi-Hsia, 2016. "Investor sentiment, order submission, and investment performance on the Taiwan Stock Exchange," Pacific-Basin Finance Journal, Elsevier, vol. 39(C), pages 124-140.
    17. Constantinos Antoniou & John A. Doukas & Avanidhar Subrahmanyam, 2016. "Investor Sentiment, Beta, and the Cost of Equity Capital," Management Science, INFORMS, vol. 62(2), pages 347-367, February.
    18. Miwa, Kotaro & Ueda, Kazuhiro, 2016. "Analysts’ preference for growth investing and vulnerability to market-wide sentiment," The Quarterly Review of Economics and Finance, Elsevier, vol. 61(C), pages 40-52.
    19. Lutz, Chandler, 2015. "The impact of conventional and unconventional monetary policy on investor sentiment," Journal of Banking & Finance, Elsevier, vol. 61(C), pages 89-105.
    20. Chung, San-Lin & Hung, Chi-Hsiou & Yeh, Chung-Ying, 2012. "When does investor sentiment predict stock returns?," Journal of Empirical Finance, Elsevier, vol. 19(2), pages 217-240.

    More about this item

    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:wly:coacre:v:38:y:2021:i:1:p:518-544. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1111/(ISSN)1911-3846 .

    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.