IDEAS home Printed from https://ideas.repec.org/a/spr/fininn/v8y2022i1d10.1186_s40854-022-00346-5.html
   My bibliography  Save this article

Tone of language, financial disclosure, and earnings management: a textual analysis of form 20-F

Author

Listed:
  • Shuangyan Li

    (Xi’an Jiaotong University)

  • Guangrui Wang

    (Hanwang Technology Co., Ltd.)

  • Yongli Luo

    (Archie W. Dunham College of Business at Houston Baptist University)

Abstract

This study investigates the relationship between the tone of financial disclosures and managers’ earnings management behavior using Form 20-F filings of Chinese firms listed in the U.S. during 2002–2014. The results show that the proportion of positive, uncertain, or modal words used in financial disclosures is positively related to corporate earnings management, implying that managers attempt to conceal earnings management behavior by manipulating the tone of their financial reports. In addition, robustness tests are conducted using an alternative proxy for earnings management that considers the effects of the financial crisis and separately examines the information and non-information technology industries. The results suggest that the tone used in financial disclosures has informative value, and textual analysis can be an effective tool for identifying earnings management.

Suggested Citation

  • Shuangyan Li & Guangrui Wang & Yongli Luo, 2022. "Tone of language, financial disclosure, and earnings management: a textual analysis of form 20-F," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-24, December.
  • Handle: RePEc:spr:fininn:v:8:y:2022:i:1:d:10.1186_s40854-022-00346-5
    DOI: 10.1186/s40854-022-00346-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1186/s40854-022-00346-5
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1186/s40854-022-00346-5?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. 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.
    2. Shan, Yuan George, 2019. "Do corporate governance and disclosure tone drive voluntary disclosure of related-party transactions in China?," Journal of International Accounting, Auditing and Taxation, Elsevier, vol. 34(C), pages 30-48.
    3. Jiang, Fuwei & Lee, Joshua & Martin, Xiumin & Zhou, Guofu, 2019. "Manager sentiment and stock returns," Journal of Financial Economics, Elsevier, vol. 132(1), pages 126-149.
    4. Tim Loughran & Bill Mcdonald, 2016. "Textual Analysis in Accounting and Finance: A Survey," Journal of Accounting Research, Wiley Blackwell, vol. 54(4), pages 1187-1230, September.
    5. Xiao Wu, Dong & Yao, Xiao & Luan Guo, Jian, 2021. "Is Textual Tone Informative or Inflated for Firm’s Future Value? Evidence from Chinese Listed Firms," Economic Modelling, Elsevier, vol. 94(C), pages 513-525.
    6. Johannes G. Jaspersen & Marc A. Ragin & Justin R. Sydnor, 2020. "Linking subjective and incentivized risk attitudes: The importance of losses," Journal of Risk and Uncertainty, Springer, vol. 60(2), pages 187-206, April.
    7. Mai, Feng & Tian, Shaonan & Lee, Chihoon & Ma, Ling, 2019. "Deep learning models for bankruptcy prediction using textual disclosures," European Journal of Operational Research, Elsevier, vol. 274(2), pages 743-758.
    8. Dou, Yiwei & Khan, Mozaffar & Zou, Youli, 2016. "Labor unemployment insurance and earnings management," Journal of Accounting and Economics, Elsevier, vol. 61(1), pages 166-184.
    9. Pevzner, Mikhail & Xie, Fei & Xin, Xiangang, 2015. "When firms talk, do investors listen? The role of trust in stock market reactions to corporate earnings announcements," Journal of Financial Economics, Elsevier, vol. 117(1), pages 190-223.
    10. El Diri, Malek & Lambrinoudakis, Costas & Alhadab, Mohammad, 2020. "Corporate governance and earnings management in concentrated markets," Journal of Business Research, Elsevier, vol. 108(C), pages 291-306.
    11. Tim Loughran & Bill Mcdonald, 2014. "Measuring Readability in Financial Disclosures," Journal of Finance, American Finance Association, vol. 69(4), pages 1643-1671, August.
    12. Loughran, Tim & McDonald, Bill, 2013. "IPO first-day returns, offer price revisions, volatility, and form S-1 language," Journal of Financial Economics, Elsevier, vol. 109(2), pages 307-326.
    13. Bian, Shibo & Jia, Dekui & Li, Ruihai & Sun, Wujun & Yan, Zhipeng & Zheng, Yingfei, 2021. "Can management tone predict IPO performance? – Evidence from mandatory online roadshows in China," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    14. Beckmann, Klaus S. & Escobari, Diego A. & Ngo, Thanh, 2019. "The real earnings management of cross-listing firms," Global Finance Journal, Elsevier, vol. 41(C), pages 128-145.
    15. Quanbo Zha & Gang Kou & Hengjie Zhang & Haiming Liang & Xia Chen & Cong-Cong Li & Yucheng Dong, 2020. "Opinion dynamics in finance and business: a literature review and research opportunities," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-22, December.
    16. Bao, Shuji Rosey & Lewellyn, Krista B., 2017. "Ownership structure and earnings management in emerging markets—An institutionalized agency perspective," International Business Review, Elsevier, vol. 26(5), pages 828-838.
    17. Kim, Jaehyeon & Kim, Yongtae & Zhou, Jian, 2017. "Languages and earnings management," Journal of Accounting and Economics, Elsevier, vol. 63(2), pages 288-306.
    18. Xiaolan Yang & Yongli Luo, 2014. "Rumor Clarification and Stock Returns: Do Bull Markets Behave Differently from Bear Markets?," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 50(1), pages 197-209, January.
    19. Hu, Juncheng, 2021. "Do facilitation payments affect earnings management? Evidence from China," Journal of Corporate Finance, Elsevier, vol. 68(C).
    20. Kearney, Colm & Liu, Sha, 2014. "Textual sentiment in finance: A survey of methods and models," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 171-185.
    21. Nguyen Anh Huu & Nguyen Linh Ha & Doan Duong Thuy, 2020. "Ownership Structure and Earnings Management: Empirical Evidence from Vietnam Real Estate Sector," Real Estate Management and Valuation, Sciendo, vol. 28(2), pages 37-51, June.
    22. Kris Boudt & James Thewissen, 2019. "Jockeying for Position in CEO Letters: Impression Management and Sentiment Analytics," Financial Management, Financial Management Association International, vol. 48(1), pages 77-115, March.
    23. Ni, Xiaoran, 2020. "Does stakeholder orientation matter for earnings management: Evidence from non-shareholder constituency statutes," Journal of Corporate Finance, Elsevier, vol. 62(C).
    24. Ingrid E. Fisher & Margaret R. Garnsey & Mark E. Hughes, 2016. "Natural Language Processing in Accounting, Auditing and Finance: A Synthesis of the Literature with a Roadmap for Future Research," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 23(3), pages 157-214, July.
    25. Lang, Mark & Stice-Lawrence, Lorien, 2015. "Textual analysis and international financial reporting: Large sample evidence," Journal of Accounting and Economics, Elsevier, vol. 60(2), pages 110-135.
    26. Blau, Benjamin M. & DeLisle, Jared R. & Price, S. McKay, 2015. "Do sophisticated investors interpret earnings conference call tone differently than investors at large? Evidence from short sales," Journal of Corporate Finance, Elsevier, vol. 31(C), pages 203-219.
    27. Bodnaruk, Andriy & Loughran, Tim & McDonald, Bill, 2015. "Using 10-K Text to Gauge Financial Constraints," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 50(4), pages 623-646, August.
    28. Tim Loughran & Bill Mcdonald, 2011. "When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks," Journal of Finance, American Finance Association, vol. 66(1), pages 35-65, February.
    29. Li, Feng, 2008. "Annual report readability, current earnings, and earnings persistence," Journal of Accounting and Economics, Elsevier, vol. 45(2-3), pages 221-247, August.
    30. Price, S. McKay & Doran, James S. & Peterson, David R. & Bliss, Barbara A., 2012. "Earnings conference calls and stock returns: The incremental informativeness of textual tone," Journal of Banking & Finance, Elsevier, vol. 36(4), pages 992-1011.
    31. Jegadeesh, Narasimhan & Wu, Di, 2013. "Word power: A new approach for content analysis," Journal of Financial Economics, Elsevier, vol. 110(3), pages 712-729.
    32. Luo, Yongli & Fang, Fang & Esqueda, Omar A., 2012. "The overseas listing puzzle: Post-IPO performance of Chinese stocks and ADRs in the U.S. market," Journal of Multinational Financial Management, Elsevier, vol. 22(5), pages 193-211.
    33. Li, Ting & Zaiats, Nataliya, 2017. "Information environment and earnings management of dual class firms around the world," Journal of Banking & Finance, Elsevier, vol. 74(C), pages 1-23.
    34. Kothari, S.P. & Leone, Andrew J. & Wasley, Charles E., 2005. "Performance matched discretionary accrual measures," Journal of Accounting and Economics, Elsevier, vol. 39(1), pages 163-197, February.
    35. James S. Ang & Zhiqian Jiang & Chaopeng Wu, 2016. "Good Apples, Bad Apples: Sorting Among Chinese Companies Traded in the U.S," Journal of Business Ethics, Springer, vol. 134(4), pages 611-629, April.
    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. Katsafados, Apostolos G. & Leledakis, George N. & Pyrgiotakis, Emmanouil G. & Androutsopoulos, Ion & Fergadiotis, Manos, 2024. "Machine learning in bank merger prediction: A text-based approach," European Journal of Operational Research, Elsevier, vol. 312(2), pages 783-797.
    2. Tim Loughran & Bill Mcdonald, 2016. "Textual Analysis in Accounting and Finance: A Survey," Journal of Accounting Research, Wiley Blackwell, vol. 54(4), pages 1187-1230, September.
    3. Liu, Pu & Nguyen, Hazel T., 2020. "CEO characteristics and tone at the top inconsistency," Journal of Economics and Business, Elsevier, vol. 108(C).
    4. Renato Camodeca & Alex Almici & Umberto Sagliaschi, 2018. "Sustainability Disclosure in Integrated Reporting: Does It Matter to Investors? A Cheap Talk Approach," Sustainability, MDPI, vol. 10(12), pages 1-34, November.
    5. Bian, Shibo & Jia, Dekui & Li, Ruihai & Sun, Wujun & Yan, Zhipeng & Zheng, Yingfei, 2021. "Can management tone predict IPO performance? – Evidence from mandatory online roadshows in China," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    6. Michał Dzieliński & Alexander F. Wagner & Richard J. Zeckhauser, 2017. "Straight Talkers and Vague Talkers: The Effects of Managerial Style in Earnings Conference Calls," NBER Working Papers 23425, National Bureau of Economic Research, Inc.
    7. Richard Frankel & Jared Jennings & Joshua Lee, 2022. "Disclosure Sentiment: Machine Learning vs. Dictionary Methods," Management Science, INFORMS, vol. 68(7), pages 5514-5532, July.
    8. Senave, Elseline & Jans, Mieke J. & Srivastava, Rajendra P., 2023. "The application of text mining in accounting," International Journal of Accounting Information Systems, Elsevier, vol. 50(C).
    9. Yan Luo & Linying Zhou, 2020. "Textual tone in corporate financial disclosures: a survey of the literature," International Journal of Disclosure and Governance, Palgrave Macmillan, vol. 17(2), pages 101-110, September.
    10. Ingrid E. Fisher & Margaret R. Garnsey & Mark E. Hughes, 2016. "Natural Language Processing in Accounting, Auditing and Finance: A Synthesis of the Literature with a Roadmap for Future Research," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 23(3), pages 157-214, July.
    11. Zheyuan Zhang & Huiying Wu & Sammy Xiaoyan Ying & Jiaxing You, 2023. "Corporate Innovation and Disclosure Strategy," Abacus, Accounting Foundation, University of Sydney, vol. 59(1), pages 76-133, March.
    12. Nadine Gatzert & Dinah Heidinger, 2020. "An Empirical Analysis of Market Reactions to the First Solvency and Financial Condition Reports in the European Insurance Industry," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 87(2), pages 407-436, June.
    13. Katsafados, Apostolos G. & Androutsopoulos, Ion & Chalkidis, Ilias & Fergadiotis, Manos & Leledakis, George N. & Pyrgiotakis, Emmanouil G., 2020. "Textual Information and IPO Underpricing: A Machine Learning Approach," MPRA Paper 103813, University Library of Munich, Germany.
    14. Ahsan Habib & Mostafa Monzur Hasan, 2020. "Business strategies and annual report readability," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(3), pages 2513-2547, September.
    15. Dutta, Shantanu & Fuksa, Michel & Macaulay, Ken, 2019. "Determinants of MD&A sentiment in Canada," International Review of Economics & Finance, Elsevier, vol. 60(C), pages 130-148.
    16. John Berns & Patty Bick & Ryan Flugum & Reza Houston, 2022. "Do changes in MD&A section tone predict investment behavior?," The Financial Review, Eastern Finance Association, vol. 57(1), pages 129-153, February.
    17. Andres Algaba & David Ardia & Keven Bluteau & Samuel Borms & Kris Boudt, 2020. "Econometrics Meets Sentiment: An Overview Of Methodology And Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 34(3), pages 512-547, July.
    18. Liu, Sha & Han, Jingguang, 2020. "Media tone and expected stock returns," International Review of Financial Analysis, Elsevier, vol. 70(C).
    19. Yi Yang & Kunpeng Zhang & Yangyang Fan, 2022. "Analyzing Firm Reports for Volatility Prediction: A Knowledge-Driven Text-Embedding Approach," INFORMS Journal on Computing, INFORMS, vol. 34(1), pages 522-540, January.
    20. Schnaubelt, Matthias & Seifert, Oleg, 2020. "Valuation ratios, surprises, uncertainty or sentiment: How does financial machine learning predict returns from earnings announcements?," FAU Discussion Papers in Economics 04/2020, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.

    More about this item

    Keywords

    Tone; Earnings management; Textual analysis; Financial statement;
    All these keywords.

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • M41 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Accounting
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    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:fininn:v:8:y:2022:i:1:d:10.1186_s40854-022-00346-5. 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.