IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0314966.html
   My bibliography  Save this article

Comprehensive financial health assessment using Advanced machine learning techniques: Evidence based on private companies listed on ChiNext

Author

Listed:
  • Wen Zhu
  • Meiling Li
  • Chengcheng Wu
  • Shanqiu Liu

Abstract

This study develops a specific and measurable framework for assessing the financial health (FH) of privately-owned companies listed on ChiNext, aimed at identifying financially sound enterprises and helping investors avoid losses caused by financial fraud or earnings management. The research proposes and tests four hypotheses related to key financial indicators and one overarching hypothesis regarding the model’s performance. Using gradient boosting machines and random forests, the model achieves high accuracy and robustness against overfitting through iterative learning. The framework incorporates four pairs of financial indicators and two non-financial indicators into four classifiers, significantly outperforming the Altman Z-score model in predicting financial soundness. Among 75 private companies with special treatment by the Securities Regulatory Commission in Shanghai and Shenzhen in 2022, 72 were correctly identified as sub-healthy or unhealthy, achieving an accuracy rate of 96%. This study demonstrates time-bound practical value by validating the model with 2022 data and highlights its relevance for cross-market applications. The results provide achievable solutions for enterprise managers and policymakers in financial decision-making and risk management.

Suggested Citation

  • Wen Zhu & Meiling Li & Chengcheng Wu & Shanqiu Liu, 2024. "Comprehensive financial health assessment using Advanced machine learning techniques: Evidence based on private companies listed on ChiNext," PLOS ONE, Public Library of Science, vol. 19(12), pages 1-26, December.
    • Handle: RePEc:plo:pone00:0314966
    DOI: 10.1371/journal.pone.0314966
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0314966
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0314966&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0314966?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. Adriana Csikosova & Maria Janoskova & Katarina Culkova, 2019. "Limitation of Financial Health Prediction in Companies from Post-Communist Countries," JRFM, MDPI, vol. 12(1), pages 1-14, January.
    2. Jones, Jj, 1991. "Earnings Management During Import Relief Investigations," Journal of Accounting Research, Wiley Blackwell, vol. 29(2), pages 193-228.
    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. Luca Menicacci, 2022. "Financial reporting and book-tax conformity: A review of the issues," FINANCIAL REPORTING, FrancoAngeli Editore, vol. 2022(1), pages 41-77.
    2. Butler, Marty & Leone, Andrew J. & Willenborg, Michael, 2004. "An empirical analysis of auditor reporting and its association with abnormal accruals," Journal of Accounting and Economics, Elsevier, vol. 37(2), pages 139-165, June.
    3. Tao Chen & Shuwen Pi & Qing Sophie Wang, 2025. "Artificial Intelligence and Corporate Investment Efficiency: Evidence from Chinese Listed Companies," Working Papers in Economics 25/05, University of Canterbury, Department of Economics and Finance.
    4. Masahiro Enomoto, 2018. "Effects of Corporate Governance on the Relationship between Accounting Quality and Trade Credit: Evidence from Japan," Discussion Paper Series DP2018-12, Research Institute for Economics & Business Administration, Kobe University, revised Dec 2023.
    5. Li, Chunyu & Lou, Chenxin & Luo, Dan & Xing, Kai, 2021. "Chinese corporate distress prediction using LASSO: The role of earnings management," International Review of Financial Analysis, Elsevier, vol. 76(C).
    6. Navarro-García, Juan Carlos & Madrid-Guijarro, Antonia, 2016. "Real economic activity and accounting information in Spanish construction and real estate firms," Revista de Contabilidad - Spanish Accounting Review, Elsevier, vol. 19(1), pages 21-30.
    7. Pavol Durana & Lucia Michalkova & Andrej Privara & Josef Marousek & Milos Tumpach, 2021. "Does the life cycle affect earnings management and bankruptcy?," Oeconomia Copernicana, Institute of Economic Research, vol. 12(2), pages 425-461, June.
    8. Chen, Wenrui & Chen, Zhiwu & Qin, Ling & Shan, Yaowen & Xu, Weihang, 2024. "Strategic alliance, agency problems, and labor investment efficiency," Economic Modelling, Elsevier, vol. 139(C).
    9. Shan Lu & Peng Wu & Lei Gao & Richard Gifford, 2023. "Are State-Owned Enterprises Equally Reliable Information Suppliers? An Examination of the Impacts of State Ownership on Earnings Management Strategies of Chinese Enterprises," Mathematics, MDPI, vol. 11(4), pages 1-26, February.
    10. Abhijit Barua & Joseph Legoria & Jacquelyn Sue Moffitt, 2006. "Accruals Management to Achieve Earnings Benchmarks: A Comparison of Pre‐managed Profit and Loss Firms," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 33(5‐6), pages 653-670, June.
    11. Kim, Sang-Joon & Bae, John & Oh, Hannah, 2019. "Financing strategically: The moderation effect of marketing activities on the bifurcated relationship between debt level and firm valuation of small and medium enterprises," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 663-681.
    12. Hanish Rajpal & Pawan Jain, 2018. "Auditor’s Characteristics and Earnings Management in India," Accounting and Finance Research, Sciedu Press, vol. 7(4), pages 1-43, November.
    13. Jens Hagendorff & Sonya Lim & Duc Duy Nguyen, 2023. "Lender Trust and Bank Loan Contracts," Management Science, INFORMS, vol. 69(3), pages 1758-1779, March.
    14. Alessandro Paolo Rigamonti & Giulio Greco & Mariarita Pierotti & Alessandro Capocchi, 2024. "Macroeconomic uncertainty and earnings management: evidence from commodity firms," Review of Quantitative Finance and Accounting, Springer, vol. 62(4), pages 1615-1649, May.
    15. Ronelle Burger & Canh Thien Dang & Trudy Owens, 2017. "Better performing NGOs do report more accurately: Evidence from investigating Ugandan NGO financial accounts," Discussion Papers 2017-10, University of Nottingham, CREDIT.
    16. Craig J. Chapman & Thomas J. Steenburgh, 2011. "An Investigation of Earnings Management Through Marketing Actions," Management Science, INFORMS, vol. 57(1), pages 72-92, January.
    17. Anna Görlitz & Michael Dobler, 2023. "Financial accounting for deferred taxes: a systematic review of empirical evidence," Management Review Quarterly, Springer, vol. 73(1), pages 113-165, February.
    18. Hu, Juncheng, 2021. "Do facilitation payments affect earnings management? Evidence from China," Journal of Corporate Finance, Elsevier, vol. 68(C).
    19. DuCharme, Larry L. & Malatesta, Paul H. & Sefcik, Stephan E., 2004. "Earnings management, stock issues, and shareholder lawsuits," Journal of Financial Economics, Elsevier, vol. 71(1), pages 27-49, January.
    20. Ludovic Vigneron & Yves Mard, 2016. "Earnings management across publicly traded and privately held French SMEs," International Journal of Entrepreneurship and Small Business, Inderscience Enterprises Ltd, vol. 29(3), pages 416-440.

    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:plo:pone00:0314966. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.