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All issues Volume 74 (2020) SHS Web Conf., 74 (2020) 05024 References
Open Access
Issue
SHS Web Conf.
Volume 74, 2020
The 19th International Scientific Conference Globalization and its Socio-Economic Consequences 2019 – Sustainability in the Global-Knowledge Economy
Article Number 05024
Number of page(s) 8
Section Regions and Economic Resilience
DOI https://doi.org/10.1051/shsconf/20207405024
Published online 10 January 2020
  1. M. Durica, I. Podhorska, P. Durana, Business failure prediction using cart-based model: A case of Slovak companies. Ekonomicko-manazerske spektrum 13, 1, 51-61 (2019) [CrossRef] [Google Scholar]
  2. J. Salaga, V. Bartosova, E. Kicova, Economic value added as a measurement tool of financial performance. Procedia Economics and Finance 26, 484-489 (2015) [CrossRef] [Google Scholar]
  3. K. Valaskova, K. Kramarova, B. Kollar, Theoretical aspects of a model of credit risk determinationCredit risk. Advances in Education Research 81, 401-406 (2015) [Google Scholar]
  4. Svabova, Durica, 2016 [Google Scholar]
  5. N. Shpak, O. Sorochak, M. Hvozd, W. Sroka, Risk evaluation of the reengineering projects: A Case Study Analysis. Scientific Annals of Economics and Business 65, 2, 215-226 (2018) [CrossRef] [Google Scholar]
  6. P. Adamko, E. Spuchlakova, K. Valaskova, The history and ideas behind VaR. Procedia Economics and Finance 24, 18-24 (2015) [CrossRef] [Google Scholar]
  7. J. Oláh, G. Karmazin, D. Máté, J.K. Grabara, J. Popp, The effect of acquisition moves on income, pre-tax profits and future strategy of logistics firms. Journal of International Studies 10, 4, 233-245 (2017) [CrossRef] [Google Scholar]
  8. M. Dobrodolac, L. Svadlenka, M. Cubranic-Dobrodolac, S. Cicevic, B. Stanivukovic, A model for the comparison of business units. Personnel Review 47, 1, 150-165 (2018) [CrossRef] [Google Scholar]
  9. M. Kovacova, T. Kliestik, Logit and Probit application for the prediction of bankruptcy in Slovak companies. Equilibrium 12, 4, 2017. [Google Scholar]
  10. B. Gavurova, F. Janke, M. Packova, M. Pridavok, Analysis of impact of using the trend variables on bankruptcy prediction models performance. Ekonomicky casopis 65, 4, 2017. [Google Scholar]
  11. M. Mihalovic, Performance comparison of multiple discriminant analysis and logit models in bankruptcy prediction. Economics & Sociology 9, 4, 2016. [Google Scholar]
  12. P. Adamko, L. Svabova, Prediction of the risk of bankruptcy of Slovak companies. In M. Culik (Ed.). Proceedings of the 8th International scientific conference managing and modelling of financial risks. Ostrava, Czech Republic, 2016. [Google Scholar]
  13. K. Valaskova, L. Svabova, M. Durica, Verifikácia predikčných modelov v podmienkach Slovenského poľnohospodárskeho sektora. Economics, Management, Innovation 9, 3, 30-38, 2017. [Google Scholar]
  14. C.F. Tsai, K.C. Cheng, Simple instance selection for bankruptcy prediction. Knowledge-based Systems 27, 2012. [Google Scholar]
  15. S. Linares-Mustaros, G. Coenders, M. Vives-Mestres, Financial performance and distress profiles. From classification according to financial ratios to compositional classification. Advances in Accounting 40, 2018. [CrossRef] [Google Scholar]
  16. M.J. Alrawashdeh, T.R. Radwan, K.A. Abunawas, Performance of linear discriminant analysis using different robust methods. European Journal of Pure and Applied Mathematics 11, 1, 2018. [Google Scholar]
  17. S. Figini, F. Bonelli, E. Giovannini, Solvency prediction for small and medium enterprises in banking. Decision Support Systems 102, 2017. [Google Scholar]
  18. B. Pawelek, K. Galuszka, J. Kostrzewska, M. Kostrzewski, Classification methods in the research on the financial standing of construction enterprises after bankruptcy in Poland. In F. Palumbo, A. Montanari, M. Vichi (Eds.). Data science: Innovative developments in data analysis and clustering. Springer International Pulishing, 2015. [Google Scholar]
  19. J. Kostrzewska, M. Kostrzewski, B. Pawelek, K. Galuszka, The classical and Bayesian logistic regression in the research on the financial standing of enterprises after bankruptcy in Poland. In M. Papiez & S. Smiech (Eds.). Proceedings of 10th professor Aleksander Zelias international conference on modelling and forecasting of socio-economic phenomena. Cracow: Foundation of the Cracow University of Economics, 2016. [Google Scholar]
  20. B. Pawelek, J. Kostrzewska, A. Lipieta, The problem of outliers in the research on the financial standing of construction enterprises in Poland. In M. Papiez & S. Smiech (Eds.). Proceedings of 9th professor Aleksander Zelias international conference on modelling and forecasting of socio-economic phenomena. Cracow: Foundation of the Cracow University of Economics, 2015. [Google Scholar]
  21. B.G. Tabachnick, L.S. Fidell, Using multivariate statistics. Boston, USA: Pearson Education, 2013. [Google Scholar]
  22. L. Svabova, M. Durica, I. Podhorska, Prediction of Default of Small Companies in the Slovak Republic. Economics and Culture 15, 1, 88-95, 2018. [Google Scholar]

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