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Predicting Financial Failure: Empirical Evidence from Publicly – Quoted Firms in Developed and Developing Countries

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  • Yavuz GÜL
  • Serpil ALTINIRMAK

Abstract

This paper analyzes the data of 570 firms from developed and developing countries between 2010 and 2019 in an attempt to create high–accuracy financial failure prediction models. In this sense, we utilize three different methods, namely logistic regression (LR), artificial neural networks (ANN), and decision trees (DT), and compare the classification accuracy performances of these techniques. Using 16 financial ratios as independent variables, ANN is able to generate the most accurate prediction and outperforms the other methods in predicting failure. Otherwise said, ANN yields a correct classification accuracy of 98.1% one year prior to failure while LR and DT achieve accuracy rates of 94.7% and 96.1%, respectively. Furthermore, the empirical results demonstrate that the classification accuracy rate reaches 92.5% by ANN, 91.1% by DT, and 84.4% by logistic regression two years in advance. The findings of current research provide valuable insights into financial failure prediction and may entice practical implications for stakeholders, especially investors and regulatory bodies, by indicating that the use of the ANN approach may be more effective.

Suggested Citation

  • Yavuz GÜL & Serpil ALTINIRMAK, 2025. "Predicting Financial Failure: Empirical Evidence from Publicly – Quoted Firms in Developed and Developing Countries," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, vol. 10(1), pages 107-126.
  • Handle: RePEc:ahs:journl:v:10:y:2025:i:1:p:107-126
    DOI: https://doi.org/10.30784/epfad.1595915
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    More about this item

    Keywords

    Financial Failure; Logistic Regression; Artificial Neural Networks; Decision Trees;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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