Predicting bankruptcy of agriculture companies : validating selected models

• Autorzy: Karas M. , Reznakova M. , Pokorny P.

Identyfikatory

DOI

10.17512/pjms.2017.15.1.11

Warianty tytułu

PL

Prognozowanie upadłości spółek rolnych : weryfikacja wybranych modeli

• Języki publikacji: EN

Abstrakty

EN

Many bankruptcy prediction models have been published so far, most of them were especially designated for the manufacturing companies. According to several studies, these models are inappropriate for other industries, as such application would be connected with a significantly lower accuracy than could be expected. The aim of this paper is to analyse the current accuracy of four traditional bankruptcy prediction models in the field of agriculture. The results showed that these models are less accurate in this field in comparison with the original results. This motivates the effort of deriving new models that would be specially developed for agriculture business.

PL

Dotychczas opublikowano wiele modeli predykcji bankructwa, większość została przeznaczona dla firm produkcyjnych. Według badań, modele te są nieodpowiednie dla innych gałęzi przemysłu, ponieważ takie zastosowanie wiązałoby się ze znacznie niższą dokładnością, niż można byłoby się spodziewać. Celem niniejszego artykułu jest analiza aktualnej dokładności czterech tradycyjnych modeli predykcji bankructwa w rolnictwie. Wyniki wykazały, że modele te są mniej dokładne w tej dziedzinie w porównaniu z pierwotnymi wynikami. Motywuje to wysiłek do wyprowadzania nowych modeli, które zostałyby specjalnie opracowane dla przedsiębiorstw rolniczych.

Słowa kluczowe

EN

bankruptcy prediction models; ROC curves; agriculture

PL

modele predykcji bankructwa; krzywe ROC; rolnictwo

• Wydawca: Czestochowa University of Technology
• Czasopismo: Polish Journal of Management Studies
• Rocznik: 2017
• Tom: Vol. 15, No. 1
• Strony: 110--120
• Opis fizyczny: Bibliogr. 19 poz., rys., tab.

Twórcy

autor

Karas M.

• Brno University of Technology, Faculty of Business and Management

autor

Reznakova M.

• Brno University of Technology, Faculty of Business and Management

autor

Pokorny P.

• Brno University of Technology, Faculty of Business and Management

Bibliografia

• 1. Altman E.I., 1968, Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy, “The Journal of Finance”, 23.
• 2. Altman E.I., 1983, Corporate financial distress: A complete guide to predicting, avoiding and dealing with bankruptcy, New York: John Wiley and Sons.
• 3. Altman E.I., Sabato G., 2007, Modelling credit risk for SMEs: Evidence from US market, “Abacus”, 43.
• 4. Altman E.I., 2000, Predicting Financial Distress of Companies: Revisiting the Z-score and Zeta® Models, Available at: http://pages.stern.nyu.edu/~ealtman/PredFnclDistr.pdf. Access on: 13.04.2017.
• 5. Bieliková T., Bányiová T., Piterková A., 2014, Prediction Techniques of Agriculture Enterprises Failure, “Procedia Economics and Finance”, 12.
• 6. Čámská D., 2013, Predicting financial distress of companies in the Agricultural sector, [In:] Economic Science for Rural Development, International Scientific Conference, April 25-26, Jelgava, Latvia.
• 7. Grice J.S., Dugan M.T., 2001, The limitations of bankruptcy prediction models: Some cautions for the researchers, “Review of Quantitative Finance and Accounting”, 17.
• 8. Heo J., Yang J.Y., 2014, AdaBoost based bankruptcy forecasting of Korean construction companies, “Applied Soft Computing”, 24 (1).
• 9. Karas M., Režňáková M., 2015, Are the bankruptcy predictors specific for a given time or branch? The evidence from the Czech manufacturing and construction companies, [In:] Finance and the Performance of Firms in Science, Education, and Practice, 7th International Scientific Conference, April 23-24, Zlín, Czech Republic.
• 10. Lin S.H., 2009, A new two-stage hybrid approach of credit risk in banking industry, “Expert Systems with Applications”, 36.
• 11. Lukason O., 2014, Why and how agricultural firms fail: evidence from Estonia, “Bulgarian Journal of Agricultural Science”, 20.
• 12. Neumaier I., Neumaierova I., 2005, Index IN05, [in:] Evropské finanční systémy, June 23-26, Brno, Czech Republic.
• 13. Niemann M., Schmidt J.H., Neukirchen M., 2008, Improving performance of corporate rating prediction models by reducing financial ratio heterogeneity, “Journal of Banking and Finance”, 32.
• 14. Platt D.H., Platt M.B., 1990, Development of a Class of Stable Predictive Variables: The Case of Bankruptcy Prediction, “Journal of Business Finance and Accounting”, 17.
• 15. Režňáková M., Karas M., 2015a, Are the Financial Bankruptcy Predictors Branch’s Specific? The Evidence from the Czech Manufacturing and Agriculture Companies. [In:] International Conference on Applied Business Research, X International Conference, September 14-18, Madrid, Spain.
• 16. Režňáková M., Karas M., 2015b, The Prediction Capabilities of Bankruptcy Models in a Different Environment: An example of the Altman Model under the Conditions in the Visegrad Group Countries, “Journal of Economics”, 63.
• 17. Synek M., Kislingerova E., 2010, Podnikova ekonomika (Business Economics), Praha: C.H. Beck.
• 18. Vavřina J., Hampel D., Janová J., 2013, New approaches for the financial Distress classification in agribusiness, “Acta universitatis agriculturae et silviculturae mendelianae brunensis”, 61.
• 19. Wu Y., Gaunt C., Gray S., 2010, A comparison of alternative bankruptcy prediction models, “Journal of Contemporary Accounting and Economics”, 6.

Uwagi

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).