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Twenty‐five years of the Taffler z‐score model: Does it really have predictive ability?

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  • Vineet Agarwal
  • Richard Taffler

Abstract

Although copious statistical failure prediction models are described in the literature, appropriate tests of whether such methodologies really work in practice are lacking. Validation exercises typically use small samples of non‐failed firms and are not true tests of ex ante predictive ability, the key issue of relevance to model users. This paper provides the operating characteristics of the well‐known Taffler (1983) UK‐based z‐score model for the first time and evaluates its performance over the 25‐year period since it was originally developed. The model is shown to have clear predictive ability over this extended time period and dominates more naïve prediction approaches. This study also illustrates the economic value to a bank of using such methodologies for default risk assessment purposes. Prima facie, such results also demonstrate the predictive ability of the published accounting numbers and associated financial ratios used in the z‐score model calculation.

Suggested Citation

  • Vineet Agarwal & Richard Taffler, 2007. "Twenty‐five years of the Taffler z‐score model: Does it really have predictive ability?," Accounting and Business Research, Taylor & Francis Journals, vol. 37(4), pages 285-300.
  • Handle: RePEc:taf:acctbr:v:37:y:2007:i:4:p:285-300
    DOI: 10.1080/00014788.2007.9663313
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    Cited by:

    1. Elsayed, Mohamed & Elshandidy, Tamer, 2020. "Do narrative-related disclosures predict corporate failure? Evidence from UK non-financial publicly quoted firms," International Review of Financial Analysis, Elsevier, vol. 71(C).
    2. Illueca, Manuel & Norden, Lars & Pacelli, Joseph & Udell, Gregory F., 2022. "Countercyclical prudential buffers and bank risk-taking," Journal of Financial Intermediation, Elsevier, vol. 51(C).
    3. Pasquale De Luca, 2017. "The Company Fundamental Analysis and the Default Risk Ratio," International Journal of Business and Management, Canadian Center of Science and Education, vol. 12(10), pages 1-79, September.
    4. Wu, Chloe Yu-Hsuan & Hsu, Hwa-Hsien & Haslam, Jim, 2016. "Audit committees, non-audit services, and auditor reporting decisions prior to failure," The British Accounting Review, Elsevier, vol. 48(2), pages 240-256.
    5. Fuentes González, Fabián & Webb, Janette & Sharmina, Maria & Hannon, Matthew & Braunholtz-Speight, Timothy & Pappas, Dimitrios, 2022. "Local energy businesses in the United Kingdom: Clusters and localism determinants based on financial ratios," Energy, Elsevier, vol. 239(PB).
    6. Şaban Çelik & Bora Aktan & Bruce Burton, 2022. "Firm dynamics and bankruptcy processes: A new theoretical model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 567-591, April.
    7. Rick Cuijpers & Erik Peek, 2010. "Reporting Frequency, Information Precision and Private Information Acquisition," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 37(1‐2), pages 27-59, January.
    8. Tomasz Korol, 2020. "Assessment of Trajectories of Non-bankrupt and Bankrupt Enterprises," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 1113-1135.
    9. Chen, An-Sing & Chu, Hsiang-Hui & Hung, Pi-Hsia & Cheng, Miao-Sih, 2020. "Financial risk and acquirers' stockholder wealth in mergers and acquisitions," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    10. Serrano-Cinca, Carlos & Gutiérrez-Nieto, Begoña & Bernate-Valbuena, Martha, 2019. "The use of accounting anomalies indicators to predict business failure," European Management Journal, Elsevier, vol. 37(3), pages 353-375.
    11. Şaban Çelik, 2013. "Micro Credit Risk Metrics: A Comprehensive Review," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 20(4), pages 233-272, October.
    12. Foo See Liang & Shaak Pathak, 2019. "Understanding the Connection of Performance and Z-Scores for Manufacturing Firms in South Korea," Journal of Asian Development, Macrothink Institute, vol. 5(3), pages 37-46, November.
    13. T.G. Saji, 2018. "Financial Distress and Stock Market Failures: Lessons from Indian Realty Sector," Vision, , vol. 22(1), pages 50-60, March.
    14. Candida Bussoli & Mariateresa Cuoccio & Claudio Giannotti, 2021. "Discriminant Analysis and Firms’ Bankruptcy: Evidence from European SMEs," International Journal of Business and Management, Canadian Center of Science and Education, vol. 14(12), pages 164-164, July.
    15. Salwa Kessioui & Michalis Doumpos & Constantin Zopounidis, 2023. "A Bibliometric Overview of the State-of-the-Art in Bankruptcy Prediction Methods and Applications," World Scientific Book Chapters, in: Emilios Galariotis & Alexandros Garefalakis & Christos Lemonakis & Marios Menexiadis & Constantin Zo (ed.), Governance and Financial Performance Current Trends and Perspectives, chapter 6, pages 123-153, World Scientific Publishing Co. Pte. Ltd..
    16. Ji, Yu & Shi, Lina & Zhang, Shunming, 2022. "Digital finance and corporate bankruptcy risk: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 72(C).
    17. Maren Forier & Nadine Lybaert & Maarten Corten & Niels Appermont & Tensie Steijvers, 2023. "The flip side of the coin: how entrepreneurship-oriented insolvency laws can complicate access to debt financing for growth firms," European Journal of Law and Economics, Springer, vol. 56(3), pages 461-495, December.
    18. Lewis, Yimai & Bozos, Konstantinos, 2019. "Mitigating post-acquisition risk: the interplay of cross-border uncertainties," Journal of World Business, Elsevier, vol. 54(5), pages 1-1.

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