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An evaluation of Altman's Z-score using cash flow ratio to predict corporate failure amid the recent financial crisis: Evidence from the UK

Author

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  • Almamy, Jeehan
  • Aston, John
  • Ngwa, Leonard N.

Abstract

This paper investigates the extension of the Z-score model in predicting the health of UK companies; using discriminant analysis, and performance ratios to test which ratios are statistically significant in predicting the health of UK companies from 2000 to 2013. The purpose of this study is to contribute towards Altman's (1968) original Z-score model by adding a new variable. We found that, cash flow when combined with the original Z-score variable is highly significant in predicting the health of UK companies. A J-UK model was developed to test the health of UK companies. When compared to the Z-score model, the predictive power of the model was 82.9%, which is consistent with Taffler's (1982) UK model. Furthermore, to test the predictive power of the model before, during and after the financial crisis period; results show that J-UK model had higher accuracy to predict the health of UK companies than the Z-score UK model. Thus, the extension of Altman's Z score model leads to better results and assists users such as researchers, managers, regulators and other practitioners to manage their risk profile more effectively.

Suggested Citation

  • Almamy, Jeehan & Aston, John & Ngwa, Leonard N., 2016. "An evaluation of Altman's Z-score using cash flow ratio to predict corporate failure amid the recent financial crisis: Evidence from the UK," Journal of Corporate Finance, Elsevier, vol. 36(C), pages 278-285.
    • Handle: RePEc:eee:corfin:v:36:y:2016:i:c:p:278-285
    DOI: 10.1016/j.jcorpfin.2015.12.009
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    References listed on IDEAS

    as
    1. 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.
    2. Rüdiger Fahlenbrach & Robert Prilmeier & René M. Stulz, 2012. "This Time Is the Same: Using Bank Performance in 1998 to Explain Bank Performance during the Recent Financial Crisis," Journal of Finance, American Finance Association, vol. 67(6), pages 2139-2185, December.
    3. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 71-111.
    4. Altman, Edward I. & Haldeman, Robert G. & Narayanan, P., 1977. "ZETATM analysis A new model to identify bankruptcy risk of corporations," Journal of Banking & Finance, Elsevier, vol. 1(1), pages 29-54, June.
    5. Dietrich, Andreas & Wanzenried, Gabrielle, 2011. "Determinants of bank profitability before and during the crisis: Evidence from Switzerland," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(3), pages 307-327, July.
    6. John M. Griffin & Michael L. Lemmon, 2002. "Book‐to‐Market Equity, Distress Risk, and Stock Returns," Journal of Finance, American Finance Association, vol. 57(5), pages 2317-2336, October.
    7. Grice, John Stephen & Dugan, Michael T, 2001. "The Limitations of Bankruptcy Prediction Models: Some Cautions for the Researcher," Review of Quantitative Finance and Accounting, Springer, vol. 17(2), pages 151-166, September.
    8. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    9. Dimitras, A. I. & Zanakis, S. H. & Zopounidis, C., 1996. "A survey of business failures with an emphasis on prediction methods and industrial applications," European Journal of Operational Research, Elsevier, vol. 90(3), pages 487-513, May.
    10. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    11. Ilia D. Dichev, 1998. "Is the Risk of Bankruptcy a Systematic Risk?," Journal of Finance, American Finance Association, vol. 53(3), pages 1131-1147, June.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Z-score; Prediction models; UK companies; Cash flow ratio; Corporate failure; Univariate analysis;
    All these keywords.

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G3 - Financial Economics - - Corporate Finance and Governance
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G30 - Financial Economics - - Corporate Finance and Governance - - - General
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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