Bankruptcy Prediction Model Development and its Implications on Financial Performance in Slovakia

Adamko, P., & Svabova, L. (2016). Prediction of the risk of bankruptcy of Slovak companies. Proceedings of the 8th International Scientific Conference on Managing and Modelling of Financial Risks, 15-20 Search in Google Scholar

Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. Journal of Finance, 23(4), 589-609. https://doi.org/10.2307/2978933 Search in Google Scholar

Amankwah-Amoah, J., Khan, Z., & Wood, G. (2021). COVID-19 and business failures: The paradoxes of experience, scale, and scope for theory and practice. European Management Journal, 39(2), 179-184. https://doi.org/10.1016/j.emj.2020.09.002 Search in Google Scholar

Araghi, M. K., & Makvandi, S. (2013). Comparing logit, probit and multiple discriminant analysis models in predicting bankruptcy of companies. Asian Journal of Finance & Accounting, 5(1). https://doi.org/10.5296/ajfa.v5i1.2977 Search in Google Scholar

Beaver, W. H. (1966). Financial ratios as predictors of failure. Journal of Accounting Research, 4, 71-111. https://doi.org/10.2307/2490171 Search in Google Scholar

Bellovary, J. L., Giacomino, D. E., & Akers, M. D. (2007). A review of bankruptcy prediction studies: 1930 to present. Journal of Financial Education, 33, 1-42. Search in Google Scholar

Bilderbeek, J. (1979). Empirical study of the predictive ability of financial ratios in the Netherlands. Zeitschrift fur Betriebswirtschaft, 49(5), 388-407. Search in Google Scholar

Blum, M. (1974). Failing company discriminant analysis. Journal of Accounting Research, 12(1), 1-25. https://doi.org/10.2307/2490525 Search in Google Scholar

Boda, M., & Uradnicek, V. (2019). Predicting financial distress of Slovak agricultural enterprises. Ekonomicky Casopis, 67(4), 426-452. Search in Google Scholar

Boratynska, L. (2021). A new approach for risk of corporate bankruptcy assessment during the COVID-19 pandemic. Journal of Risk and Financial Management, 14(12), 590. https://doi.org/10.3390/jrfm14120590 Search in Google Scholar

Bozkurt, I., & Kaya, M.V. (2023). Foremost features affecting financial distress and bankruptcy in the acute stage of COVID-19 crisis. Applied Economics Letters, 30(8), 1112-1123. https://doi.org/10.1080/13504851.2022.2036681 Search in Google Scholar

Brygala, M. (2022). Consumer bankruptcy prediction using balanced and imbalanced data. Risks, 10(2), 24. https://doi.org/10.3390/risks10020024 Search in Google Scholar

Chen, H. J., Huang, S. Y., & Lin, C. S. (2009). Alternative diagnosis of corporate bankruptcy: A neuro fuzzy approach. Expert Systems with Applications, 36(4), 7710-7720. https://doi.org/10.1016/j.eswa.2008.09.023 Search in Google Scholar

Chrastinova, Z. (1998). Methods of economic creditworthiness evaluation and prediction of financial situation of agricultural holdings. Bratislava: VUEPP. Search in Google Scholar

Ciampi, F., Giannozzi, A., Marzi, G., & Altman, E. (2021). Rethinking SME default prediction: A systematic literature review and future perspectives. Scientometrics, 126(3), 2141-2188. https://doi.org/10.1007/s11192-020-03856-0 Search in Google Scholar

Daniel, T. E. (1968). Discriminant analysis for the prediction of business failures [Doctoral thesis, University of Alabama]. The University of Alabama. https://ir.ua.edu/handle/123456789/10106 Search in Google Scholar

Deakin, E. B. (1972). A discriminant analysis of predictors of business failure. Journal of Accounting Research, 10(1), 167-179. https://doi.org/10.2307/2490225 Search in Google Scholar

Delina, R., & Packova, M. (2013). Prediction bankruptcy models validation in Slovak business environment. E & M Ekonomie a Management, 16(3), 101-113. Search in Google Scholar

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, 90(3), 487-513. https://doi.org/10.1016/0377-2217(95)00070-4 Search in Google Scholar

Fitzpatrick, F. (1932) A comparison of ratios of successful industrial enterprises with those of failed firms. Certified Public Accountant, 6, 727-731. Search in Google Scholar

Gavurova, B., Janke, F., Packova, M., & Pridavok, M. (2017). Analysis of impact of using the trend variables on bankruptcy prediction models performance. Ekonomicky Casopis, 65(4), 370-383. Search in Google Scholar

Gregova, E., Valaskova, K., Adamko, P., Tumpach, M., & Jaros, J. (2020). Predicting financial distress of slovak enterprises: Comparison of selected traditional and learning algorithms methods. Sustainability, 12(10). https://doi.org/10.3390/su12103954 Search in Google Scholar

Gurcik, L. (2002). G-index-the financial situation prognosis method of agricultural enterprises. Agricultural Economics, 48, 373-378. https://doi.org/10.17221/5338-AGRICECON Search in Google Scholar

Horvathova, J., Mokrisova, M., & Petruska, I. (2021). Selected methods of predicting financial health of companies: neural networks versus discriminant analysis. Information, 12(12). https://doi.org/10.3390/info12120505 Search in Google Scholar

Hu, Y. C. (2020). A multivariate grey prediction model with grey relational analysis for bankruptcy prediction problems. Soft Computing, 24(6), 4259-4268. https://doi.org/10.1007/s00500-019-04191-0 Search in Google Scholar

Hurtosova, J. (2009). Development of rating model as a tool to assess the enterprise credibility [Doctoral thesis, University of Economics in Bratislava]. University of Economics in Bratislava. Search in Google Scholar

Ingram, F. J., & Frazier, E. L. (1982). Alternative multivariate tests in limited dependent variable models: An empirical assessment. Journal of Financial and Quantitative Analysis, 17(2), 227-240. https://doi.org/10.2307/2330848 Search in Google Scholar

Kliestik, T., Valaskova, K., Lazaroiu, G., Kovacova, M., & Vrbka, J. (2020). Remaining financially healthy and competitive: The role of financial predictors. Journal of Competitiveness, 12(1), 74-92. https://doi.org/10.7441/joc.2020.01.05 Search in Google Scholar

Kordlar, A. E., & Nikbakht, N. (2011). Comparing bankruptcy prediction models in Iran. Business Intelligence Journal, 4(2), 335-342. Search in Google Scholar

Kou, G., Xu, Y., Peng, Y., Shen, F., Chen, Y., Chang, K., & Kou, S. (2021). Bankruptcy prediction for SMEs using transactional data and two-stage multiobjective feature selection. Decision Support Systems, 140. https://doi.org/10.1016/j.dss.2020.113429 Search in Google Scholar

Kovacova, M., & Kliestik, T. (2017). Logit and Probit application for the prediction of bankruptcy in Slovak companies. Equilibrium. Quarterly Journal of Economics and Economic Policy, 12(4), 775–791. https://doi.org/10.24136/eq.v12i4.40 Search in Google Scholar

Kovacova, M., Valaskova, K., Durana, P., & Kliestikova, J. (2019). Innovation management of the bankruptcy: case study of visegrad group countries. Marketing and Management of Innovations, (4), 241-251. doi: 10.21272/mmi.2019.4-19 Open DOISearch in Google Scholar

Kubicova, J., & Faltus, S. (2014). Tax debt as an indicator of companies' default: The case of Slovakia. Journal of Applied Economics and Business, 2(4), 59-74. Search in Google Scholar

Laitinen, E. K. (1991). Financial ratios and different failure processes. Journal of Business Finance & Accounting, 18(5), 649-673. https://doi.org/10.1111/j.1468-5957.1991.tb00231.x Search in Google Scholar

Lennox, C. (1999). Identifying failing companies: A re-evaluation of the logit, probit and DA approaches. Journal of Economics and Business, 51(4), 347-364. https://doi.org/10.1016/S0148-6195(99)00009-0 Search in Google Scholar

Lussier, R. N., Corman, J., & Corman, J. (1996). A business success versus failure prediction model for entrepreneurs with 0-10 employees. Journal of Small Business Strategy, 7(1), 21–36. Search in Google Scholar

Matejic, T., Knezevic, S., Arsic, V.B., Obradovic, T., Milojevic, S., Adamovic, M., Mitrovic, A., Milasinovic, M., Somonovic, D., Milosevic, G., & Spiler, M. (2022). Assessing the impact of the covid-19 crisis on hotel industry bankruptcy risk through novel forecasting models. Sustanability, 14(8), 4680. https://doi.org/10.3390/su14084680 Search in Google Scholar

Mihalovic, M. (2016). Performance comparison of multiple discriminant analysis and logit models in bankruptcy prediction. Economics & Sociology, 9(4), 101. https://doi.org/10.14254/2071-789X.2016/9-4/6 Search in Google Scholar

Min, J. H., & Lee, Y. C. (2005). Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters. Expert Systems with Applications, 28(4), 603-614. https://doi.org/10.1016/j.eswa.2004.12.008 Search in Google Scholar

Mirza, N., Rahat, B., Naqvi, B., & Rizvi, S.K.A. (2023). Impact of Covid-19 on corporate solvency and possible policy responses in the EU. Quarterly Review of Economics and Finance, 87, 181-190. https://doi.org/10.1016/j.qref.2020.09.002 Search in Google Scholar

Odom, M. D., & Sharda, R. (1990). A neural network model for bankruptcy prediction. Proceedings of the IJCNN International Joint Conference on Neural Networks, 2, 163-168. https://doi.org/10.1109/IJCNN.1990.137710 Search in Google Scholar

Ohlson, J. A. (1980). Financial ratios and the probabilistic prediction of bankruptcy. Journal of Accounting Research, 18(1), 109-131. https://doi.org/10.2307/2490395 Search in Google Scholar

Pacheco, L., Madaleno, M., Correira, P, & Maldonado, I. (2022). Probability of corporate bankruptcy: Application to Portuguese manufacturing industry SMEs. International Journal of Business and Society, 23(2), 1169. https://doi.org/10.33736/ijbs.4863.2022 Search in Google Scholar

Pan, W. (2012). A new fruit fly optimisation algorithm: Taking the financial distress model as an example. Knowledge-Based Systems, 26, 69-74. https://doi.org/10.1016/j.knosys.2011.07.001 Search in Google Scholar

Papik, M., & Papikova, L. (2023). Impacts of crisis on SME bankruptcy prediction models' performance. Expert Systems with Applications, 214, 119072. https://doi.org/10.1016/j.eswa.2022.119072 Search in Google Scholar

Ptak-Chmielewska, A. (2021). Bankruptcy prediction of small- and medium-sized enterprises in Poland based on the LDA and SVM methods. Statistics in Transition New Series, 22(1), 179-195. https://doi.org/10.21307/stattrans-2021-010 Search in Google Scholar

Shi, Y., & Li, X. (2019). An overview of bankruptcy prediction models for corporate firms: A systematic literature review. Intangible Capital, 15(2), 114-127. https://doi.org/10.3926/ic.1354 Search in Google Scholar

Sofrankova, B. (2014). Bankruptcy prediction models and their application in Slovak's Hotel. Exclusive E-Journal, 1-8. Search in Google Scholar

Spisakova, M., Mesaros, P., & Mandicak, T. (2021). Construction waste audit in the framework of sustainable waste management in construction projects—Case study. Buildings, 11(2). https://doi.org/10.3390/buildings11020061 Search in Google Scholar

Sujova, E., Cierna, H., & Stefkova, J. (2021). Ethical credibility risks monitoring in manufacturing companies in Slovakia and V4 countries. Management Systems in Production Engineering. https://doi.org/10.2478/mspe-2021-0038 Search in Google Scholar

Svabova, L., Michalkova, L., Durica, M., & Nica, E. (2020). Business failure prediction for Slovak small and medium-sized companies. Sustainability, 12(11). https://doi.org/10.3390/su12114572 Search in Google Scholar

Tomczak, S.K. (2021). Ratio selection between six sectors in the visegrad group using parametric and nonparametric ANOVA. Energies, 14(21), 7120. https://doi.org/10.3390/en14217120 Search in Google Scholar

Toth, R., Kasa, R., & Lentner, C. (2022). The impact of financial culture on the operation of Hungarian SMEs before and during COVID-19. Risks, 10(7), 135. https://doi.org/10.3390/risks10070135 Search in Google Scholar

Valaskova, K., Durana, P., Adamko, P., & Jaros, J. (2020). Financial compass for Slovak enterprises: Modeling economic stability of agricultural entities. Journal of Risk and Financial Management, 13(5). https://doi.org/10.3390/jrfm13050092 Search in Google Scholar

Valaskova, K., Kliestik, T., & Gajdosikova, D. (2021). Distinctive determinants of financial indebtedness: evidence from Slovak and Czech enterprises. Equilibrium. Quarterly Journal of Economics and Economic Policy, 16(3), 639–659. https://doi.org/10.24136/eq.2021.023 Search in Google Scholar

Valaskova, K., Kliestik, T., Svabova, L., & Adamko, P. (2018). Financial risk measurement and prediction modelling for sustainable development of business entities using regression analysis. Sustainability, 10(7). https://doi.org/10.3390/su10072144 Search in Google Scholar

Varetto, F. (1998). Genetic algorithms applications in the analysis of insolvency risk. Journal of Banking & Finance, 22(10-11), 1421-1439. https://doi.org/10.1016/S0378-4266(98)00059-4 Search in Google Scholar

Wang, B. (2004). Strategy changes and internet firm survival [Doctoral thesis, University of Minnesota]. University of Minnesota. Search in Google Scholar

Zavgren, C. V. (1985). Assessing the vulnerability to failure of American industrial firms: A logistic analysis. Journal of Business Finance & Accounting, 12(1), 19-45. https://doi.org/10.1111/j.1468-5957.1985.tb00077.x Search in Google Scholar

Zhang, Y., Liu, R., Heidari, A. A., Wang, X., Chen, Y., Wang, M., & Chen, H. (2021). Towards augmented kernel extreme learning models for bankruptcy prediction: algorithmic behavior and comprehensive analysis. Neurocomputing, 430, 185-212. https://doi.org/10.1016/j.neucom.2020.10.038 Search in Google Scholar

Zmijewski, M .E. (1984) Methodological issues related to the estimation of financial distress prediction models. Journal of Accounting Research, 22, 59-82. https://doi.org/10.2307/2490859 Search in Google Scholar