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Forewarning Bankruptcy: An Indigenous Model for Pakistan

Author

Listed:
  • Muhammad Shahzad Ijaz

    (UIMS-PMAS-University of Arid Agriculture Rawalpindi)

  • Ahmed Imran Hunjra

    (UIMS-PMAS-University of Arid Agriculture Rawalpindi)

  • Rauf I Azam

    (University of Education, Lahore)

Abstract

Predicting financial health of enterprises is crucial for companies and banks (who lend money to them), as well as to all stakeholders. State Bank of Pakistan (SBP) has taken measures to implement Basel Accord framework for minimizing credit risk since its implementation in 2005. In this regard, there was a need for the development of corporate financial distress and bankruptcy prediction model which is specific to Pakistani companies to serve as a reliable tool for the assessment of financial health. In this paper we have proposed a model after a comprehensive analysis for objective prediction of financial health of companies. The proposed model has been tested for a sample of one hundred companies from non-financial sector of PSX listed companies, among which fifty were bankrupt and fifty financially healthy. Twenty-nine financial and accounting variables were used as input to model development procedure. The results suggest that the proposed model is capable of making a correct forecast of financial health of these companies.

Suggested Citation

  • Muhammad Shahzad Ijaz & Ahmed Imran Hunjra & Rauf I Azam, 2017. "Forewarning Bankruptcy: An Indigenous Model for Pakistan," Business & Economic Review, Institute of Management Sciences, Peshawar, Pakistan, vol. 9(4), pages 259-286, December.
    • Handle: RePEc:bec:imsber:v:9:y:2017:i:4:p:259-286
    DOI: dx.doi.org/10.22547/BER/9.4.12
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    References listed on IDEAS

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    1. ANDREICA Madalina Ecaterina & ANDREICA Mugurel Ionut & ANDREICA Marin, 2009. "Using financial ratios to identify Romanian distressed companies," Economia. Seria Management, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 12(1 Special), pages 46-55, July.
    2. Gentry, Ja & Newbold, P & Whitford, Dt, 1985. "Classifying Bankrupt Firms With Funds Flow Components," Journal of Accounting Research, Wiley Blackwell, vol. 23(1), pages 146-160.
    3. Brooks,Chris, 2008. "RATS Handbook to Accompany Introductory Econometrics for Finance," Cambridge Books, Cambridge University Press, number 9780521896955, September.
    4. Yang, Z. R. & Platt, Marjorie B. & Platt, Harlan D., 1999. "Probabilistic Neural Networks in Bankruptcy Prediction," Journal of Business Research, Elsevier, vol. 44(2), pages 67-74, February.
    5. Agarwal, Vineet & Taffler, Richard, 2008. "Comparing the performance of market-based and accounting-based bankruptcy prediction models," Journal of Banking & Finance, Elsevier, vol. 32(8), pages 1541-1551, August.
    6. Deakin, Eb, 1972. "Discriminant Analysis Of Predictors Of Business Failure," Journal of Accounting Research, Wiley Blackwell, vol. 10(1), pages 167-179.
    7. Hernandez Tinoco, Mario & Wilson, Nick, 2013. "Financial distress and bankruptcy prediction among listed companies using accounting, market and macroeconomic variables," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 394-419.
    8. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 71-111.
    9. Edmister, Robert O., 1972. "An Empirical Test of Financial Ratio Analysis for Small Business Failure Prediction," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 7(2), pages 1477-1493, March.
    10. Pamela K. Coats & L. Franklin Fant, 1993. "Recognizing Financial Distress Patterns Using a Neural Network Tool," Financial Management, Financial Management Association, vol. 22(3), Fall.
    11. Dambolena, Ismael G & Khoury, Sarkis J, 1980. "Ratio Stability and Corporate Failure," Journal of Finance, American Finance Association, vol. 35(4), pages 1017-1026, September.
    12. Libby, R, 1975. "Accounting Ratios And Prediction Of Failure - Some Behavioral Evidence," Journal of Accounting Research, Wiley Blackwell, vol. 13(1), pages 150-161.
    13. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    14. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    15. Zmijewski, Me, 1984. "Methodological Issues Related To The Estimation Of Financial Distress Prediction Models," Journal of Accounting Research, Wiley Blackwell, vol. 22, pages 59-82.
    16. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure - Reply," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 123-127.
    17. Westgaard, Sjur & van der Wijst, Nico, 2001. "Default probabilities in a corporate bank portfolio: A logistic model approach," European Journal of Operational Research, Elsevier, vol. 135(2), pages 338-349, December.
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    More about this item

    Keywords

    PSX; Financial distress; Bankruptcy prediction; Financial ratios;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • M41 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Accounting
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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