Abstract
The creation of bankruptcy prediction models is in the last years a topic, which much attention has been dedicated to. Researchers and economists in many countries have created prediction models which are useful for failure prediction of companies in that country. These prediction models used various financial ratios or other predictors to reach the best bankruptcy prediction. The effort of researchers leads to build a strongly prediction model that is able to predict a bankruptcy of companies or can, with some probability level, classify the companies into a group of prosperous or a group of non-prosperous ones. Previous works have shown that these models are then less effective in application in another country or in another time. Our work will lead to a creation of bankruptcy prediction model for Slovak companies. One of the first steps in this process is to choose an appropriate set of predictors, such as financial ratios of companies or characteristics of the environment, in which the company operates. For this purpose we do the preliminary statistical analysis of financial ratios of real Slovak companies. This analysis is made separately in different regions of Slovak Republic in order to analyze which regions are sufficiently similar in their characteristics and therefore could be analyzed together and, on the contrary, which regions are so different that we have to analyze them separately. Then, we can apply cluster analysis on basic statistical characteristics of financial ratios and get the clusters of Slovak regions that are for predicting bankruptcy appropriate to be analyzed together. This result will be very useful during the process of failure prediction model development in the future.
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References
Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. Journal of Finance, 23(4), 589–609.
Altman, E. I., & Sabato, G. (2005). Modeling credit risk for SMEs: Evidence from the US market. Abacus, 43(3), 332–356.
Anandarajan, M., Lee, P., & Anandarajan, A. (2004). Bankruptcy prediction using neural network, business intelligence techniques: A perspective from accounting and finance. Heidelberg: Springer-Verlag.
Bandyopadhyay, A. (2006). Predicting probability of default of Indian corporate bonds – logistic and Z-score model approaches. The Journal of Risk Finance, 7(3), 255–272.
Bartosova, V., Hraskova, D., & Paliderova, M. (2014). Basic rules and methodological framework of the financial analysis of the group of companies in the Slovak Republic. Advances in Education Research, 61, 86–91.
Beaver, W. (1966). Financial ratios as predictors of failure. Journal of Accounting Research, 4, 71–102.
Bellovary, J. L., Giacomino, D. E., & Akers, M. D. (2007). A review of bankruptcy prediction studies: 1930 to present. Journal of Financial Education, 33, 1–43.
Chung, K. C., Tan, S. S., & Holdsworth, D. K. (2008). Insolvency prediction model using multivariate discriminant analysis and artificial neural network for the finance industry in New Zealand. International Journal of Business and Management, 3(1), 19–28.
Dimitras, A., 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, 90(3), 487–513.
Fulmer, J. G., Jr., Moon, J. E., Gavin, T. A., & Erwin, M. J. (1984). A bankruptcy classification model for small firms. Journal of Commercial Bank Lending, 25–37.
Kocisova, K., & Misankova, M. (2014). Prediction of default by the use of Merton’s model and black and cox model. Advances in Education Research, 51, 563–568.
Lieu, P., Lin, C., & Yu, H. (2008). Financial early-warning models on cross-holding groups. Journal of Industrial Management & Data Systems, 108(8), 1060–1080.
Lin, L., & Piesse, J. (2004). Identification of corporate distress in UK industrials – a conditional probability analysis approach. Journal of Applied Financial Economics, 14(2), 73–82.
Misankova, M., & Kral, P. (2015). Application of CreditRisk+ for the calculation of credit risk. Proceedings of 10th International Scientific Conference Financial management of Firms and Financial Institutions (pp. 807–814). Ostrava: Czech Republic.
Misankova, M., Spuchlakova, E., & Frajtova-Michalikova, K. (2015). Determination of default probability by loss given default. Procedia Economics and Finance, 26, 411–417.
Ohlson, J. A. (1980). Financial ratios and the probabilistic prediction of bankruptcy. Journal of Accounting Research, 18, 109–131.
Shams, M. F., Sheikhi, M., & Sheikhi, Z. (2011). Financial distress prediction: Comparisons of logit models using receiver operating characteristic (ROC) curve analysis. African Journal of Business Management, 5(30), 12164–12173.
Shirata, C. Y. (1995). Read the sign of business failure. Journal of Risk and Management, 23, 117–138.
Shumway, T. (2001). Forecasting bankruptcy more accurately: A simple hazard model. Journal of Business, 74(1), 101–124.
Springate, G., Sands, E., & Var, T. (1983). Predicting business failures. CGA Magazine, 17, 24–27.
Sun, J., & Li, H. (2012). Financial distress prediction using support vector machines: Ensemble vs. individual. Applied Soft Computing, 12(8), 2254–2265.
Valaskova, K., & Zvarikova, K. (2014). Prediction of credit risk by selected theoretical rating models. Advances in Social and Behavioral Sciences, 5, 160–166.
Zmijewski, M. E. (1984). Methodological issues related to the estimation of financial distress prediction models. Journal of Accounting Research, 22, 59–86.
Acknowledgment
This research was financially supported by the Slovak Research and Development Agency—Grant No. APVV-14-0841: Comprehensive Prediction Model of the Financial Health of Slovak Companies.
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Svabova, L., Kliestik, T. (2018). Analysis of Predictors in Bankruptcy Prediction Models for Slovak Companies. In: Karasavvoglou, A., Goić, S., Polychronidou, P., Delias, P. (eds) Economy, Finance and Business in Southeastern and Central Europe. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-319-70377-0_23
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