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Predicting financial distress in non-financial sector of Pakistan using PCA and logit

Author

Listed:
  • Ehsanul Hassan
  • Muhammad Awais-E-Yazdan
  • Ramona Birau
  • Peter Wanke
  • Yong Aaron Tan

Abstract

Purpose - This study aims to develop a robust predictive model for anticipating financial distress within Pakistani companies, providing a crucial tool for proactive economic turbulence management. Design/methodology/approach - To achieve this objective, the study examines a comprehensive data set comprising nonfinancial firms listed on the Pakistan Stock Exchange from 2005 to 2022. It investigates 23 financial ratios categorized under profitability, liquidity, leverage, asset efficiency, size and growth. Findings - The study reveals that financial ratio indices are more effective in forecasting financial distress compared to individual ratios. These indices achieve impressive accuracy rates, ranging from a robust 93.90% in the first year leading up to bankruptcy to a commendable 73.71% in the fifth year. Furthermore, the research identifies profitability, liquidity, leverage, asset efficiency, size and growth as pivotal indicators for financial distress prediction. Originality/value - This research underscores the utility and practicality of financial ratio indices, offering a comprehensive perspective on risk assessment and management. In conclusion, this pioneering study provides valuable insights into financial distress prediction, highlighting the enhanced information capture made possible by financial ratio indices. It equips stakeholders in the Pakistan Stock Exchange with an effective means to proactively address financial risks.

Suggested Citation

  • Ehsanul Hassan & Muhammad Awais-E-Yazdan & Ramona Birau & Peter Wanke & Yong Aaron Tan, 2024. "Predicting financial distress in non-financial sector of Pakistan using PCA and logit," International Journal of Islamic and Middle Eastern Finance and Management, Emerald Group Publishing Limited, vol. 17(3), pages 485-508, June.
  • Handle: RePEc:eme:imefmp:imefm-10-2023-0404
    DOI: 10.1108/IMEFM-10-2023-0404
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    More about this item

    Keywords

    The Pakistan stock exchange; Financial distress; Bankruptcy; Financial ratios indices; Principal component analysis; Logistic regression; C53; G32; G33;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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