Central European Business Review 2014, 3(2):14-17 | DOI: 10.18267/j.cebr.80

Long-term Predictive Ability of Bankruptcy Models in the Czech Republic: Evidence from 2007-2012

Ondřej Machek
Ondřej Machek, Ph.D., Assistant Professor, Department of Business Economics, Faculty of Business Administration, University of Economics, Prague, 13067 Prague 3, Czech Republic, ondrej.machek@vse.cz

Bankruptcy models are a common tool of financial analysis to predict the financial distress of companies. However, in the recent years, the instability and risk of the overall economic environment have underlined the need for accurate tools to predict bankruptcy and assess the overall performance of companies. In this article, we analyze the ex-ante predictive ability of selected bankruptcy and solvency models commonly used in financial analysis: Kralicek quick test, Taffler model, the IN99 and IN05 indexes, and Altman Z'-score models in the case of Czech companies from 2007 to 2012. We determined the percentage of cases when these models correctly predicted failures of companies up to five years in advance, and found that the IN05 and IN99 credibility indexes provided the best results, as well as the Altman Z'-score model. However, the predictive ability of the Taffler model and Kralicek quicktest has only been limited.

Keywords: bankruptcy prediction; Altman Z'-score; Taffler model; Kralicek quick test; IN05; IN99
JEL classification: G30, G33

Received: February 27, 2014; Revised: June 1, 2014; Published: June 30, 2014  Show citation

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Machek, O. (2014). Long-term Predictive Ability of Bankruptcy Models in the Czech Republic: Evidence from 2007-2012. Central European Business Review3(2), 14-17. doi: 10.18267/j.cebr.80
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References

  1. Agarwal, V., Taffler, R. J. (2007). Twenty-five years of the Taffler z-score model: Does it really have predictive ability? Accounting and Business Research, 37 (4): 285-300. Go to original source...
  2. Altman, E. I. (1968). Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy. Journal of Finance, 23 (4): 589-603. Go to original source...
  3. Altman, E. I. (2012). Predicting Financial Distress of Companies: Revisiting the Z-Score and ZETA (R) Models, in Handbook of Research in Empirical Finance, ed. Elgar, E., Brooks, C., Cheltenham: Edward Elgar, 7-36.
  4. Čámská, D. (2012). National View of Bankruptcy Models, in International Days of Statistics and Economics, ed. Pavelka, T., Löster, T., Slaný : Melandrium, 268-278.
  5. Collins, R. A. (1980). An empirical comparison of bankruptcy prediction models. Financial Management, 9 (2): 52-57. Go to original source...
  6. Kralicek, P. (1991). Grundlagen der Finanzwirtschaft: Bilanzen, Gewinn und Verlustrechnung, Cashflow. Kalkulationsgrundlagen, Fruehwarnsysteme, Finanzplannung. Wien: Ueberrauter, 1991.
  7. Krause, J. (2013). Risk management in companies and the importance of selected measures for overcoming the crisis. WSEAS Transactions on Business and Economics, 10(3): 133-141.
  8. Maňasová, Z. (2007). Úpadky podniků v České republice a možnosti jejich včasné predikce. Disertation thesis. Prague: University of Economics.
  9. Neumaierová, I, Neumaier, I. (2014). INFA Performance Indicator Diagnostic System. Central European Business Review, 3 (1): 35-41. Go to original source...
  10. Smrčka, L., Schönfeld, J. (2014). Several conclusions from research of insolvency cases in the Czech Republic. Central European Business Review, 3 (1): 13-19. Go to original source...
  11. Taffler R. J., Tisshaw, H. (1977). Going, going, gone - four factors which predict. Accountancy, 88: 50-54.
  12. Tyll, L. (2011). Outsourcing v krizi. Finanční řízení & controlling v praxi, 2(12): 32-35.
  13. Wang, Y., Campbell, M. (2010). Do Bankruptcy Models Really Have Predictive Ability? Evidence using China Publicly Listed Companies. International Management Review, 6(2).

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