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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
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    References listed on IDEAS

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    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, John Wiley & Sons, Ltd., vol. 29(2), pages 193-228.
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