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Modeling Bankruptcy Prediction for Non-Financial Firms: The Case of Pakistan

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  • Abbas, Qaiser
  • Rashid, Abdul

Abstract

This paper aims to identify the financial ratios that are most significant in bankruptcy prediction for the non-financial sector of Pakistan based on a sample of companies which became bankrupt over the 1996-2006 period. Twenty four financial ratios covering four important financial attributes namely profitability, liquidity, leverage, and turnover ratios) were examined for a five-year period prior bankruptcy. The discriminant analysis produced a parsimonious model of three variables viz. sales to total assets, EBIT to current liabilities, and cash flow ratio. Our estimates provide evidence that the firms having Z value below zero fall into the “bankrupt” whereas the firms with Z value above zero fall into the “non-bankrupt” category. The model achieved 76.9% prediction accuracy when it is applied to forecast bankruptcies on the underlying sample.

Suggested Citation

  • Abbas, Qaiser & Rashid, Abdul, 2011. "Modeling Bankruptcy Prediction for Non-Financial Firms: The Case of Pakistan," MPRA Paper 28161, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:28161
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    References listed on IDEAS

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    Cited by:

    1. Atanas Delev, 2016. "Issues and Challenges for Bankruptcy Risk Assessment in Bulgarian Companies," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 3, pages 118-136.
    2. Javed Iqbal & Furrukh Bashir & Rashid Ahmad & Hina Arshad, 2022. "Predicting Bankruptcy through Neural Network:Case of PSX Listed Companies," iRASD Journal of Management, International Research Alliance for Sustainable Development (iRASD), vol. 4(2), pages 299-315, june.

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    More about this item

    Keywords

    Bankruptcy; Z-Score; Non-Financial Firms; Financial Ratios; Pakistan;
    All these keywords.

    JEL classification:

    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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