The methodical approach of bankruptcy probability estimation in an anti-crisis management system of enterprise

Authors

  • Dr. Inna Neskorodieva V. N. Karazin Kharkiv National University
  • Dr. Nikolay Megits Webster University
  • Dr. Vladimir Rodchenko Karazin Business School. V. N. Karazin Kharkiv National University
  • Dr. Svitlana Pustovhar International Economic Relations and Finance Department, Kyiv National University of Trade and Economics, Kharkiv Institute of Trade and Economics
  • Dr. Oleksand Stamatin

DOI:

https://doi.org/10.15549/jeecar.v6i2.332

Keywords:

anti-crisis management, insolvency, bankruptcy risk, financial standing, financial stability.

Abstract

The article presents the methodical approach to anti-crisis management system development for metallurgical enterprises of Ukraine, which is aimed at bankruptcy probability estimation based on financial indicators. The methodical approach is implemented by means of defining the indicators of the enterprise bankruptcy; integrated solvability index calculation; integrated solvability index limits definition by the class of enterprise depending on the risk of the enterprise bankruptcy. The elaborated methodical approach is the instrument for preventive anti-crisis management at the enterprises of Ukraine due to its direction at determining early marks of insolvency. Approbation results for the elaborated methodical approach at metallurgical enterprises testified high bankruptcy risk caused by the enterprise loss-making activity, which has a negative impact on the current financial standing and poses the potential threat of bankruptcy resulting from the lack of self-finance sources, thus, reducing the enterprise financial stability and creditworthiness.

Author Biographies

Dr. Inna Neskorodieva, V. N. Karazin Kharkiv National University

Professor

Dr. Vladimir Rodchenko, Karazin Business School. V. N. Karazin Kharkiv National University

Professor

Dr. Svitlana Pustovhar, International Economic Relations and Finance Department, Kyiv National University of Trade and Economics, Kharkiv Institute of Trade and Economics

Senior Lecturer

Dr. Oleksand Stamatin

Starsen LLC.

References

Altman, E., & Hotchkiss, E. (2006). Corporate Financial Distress and Bankruptcy: Predict and Avoid Bankruptcy, Analyze and Invest in Distressed Debt. Hoboken: John Wiley and Sons, Ltd.

Antunes, F., Ribeiro, B., & Pereira, F. (2017). Probabilistic modeling and visualization for bankruptcy prediction. Applied Soft Computing, 60, 831-843. DOI: https://doi.org/10.1016/j.asoc.2017.06.043

Azayite, F., & Achchab, S. (2016). Hybrid Discriminant Neural Networks for Bankruptcy Prediction and Risk Scoring. Procedia Computer Science, 83, 670-674 DOI: https://doi.org/10.1016/j.procs.2016.04.149

Chan-Lau, J. (2006). Fundamentals-based estimation of default probabilities: a survey Retrieved January 20, 2019 from http://ideas.repec.org/p/imf/imfwpa/06-149.html.

Dai, X., & Li, S. (2018). Cross-modal deep discriminant analysis. Neurocomputing, 314, 437-444. DOI: https://doi.org/10.1016/j.neucom.2017.09.059

Fulmer, J.G.Jr. et al. (1984). Bankruptcy Classification Model for Small Firms. Journal of commercial Bank Lending, 25-37.

Hamilton, D.T., Sun, Zh., & Ding, M. (2011). Through-the-Cycle EDF Credit Measures. Moody's Analytics Methodology. Retrieved January 20, 2019 from http://www.moodysanalytics.com/~/media/Microsites/ERS/2011/through-cycle-EDF/MoodysAnalytics_Through-the-Cycle%20EDF%20Measure% 20Methodology%20Overview.pdf

Hosaka, T. (2019). Bankruptcy prediction using imaged financial ratios and convolutional neural networks. Expert Systems with Applications, 117, 287-299. DOI: https://doi.org/10.1016/j.eswa.2018.09.039

Jabeur, S. (2017). Bankruptcy prediction using Partial Least Squares Logistic Regression. Journal of Retailing and Consumer Services, 36, 197-202. DOI: https://doi.org/10.1016/j.jretconser.2017.02.005

Ko?išová, K., & Mišanková, M. (2014). Discriminant Analysis as a Tool for Forecasting Company's Financial Health. Procedia - Social and Behavioral Sciences, 110, 1148-1157 DOI: https://doi.org/10.1016/j.sbspro.2013.12.961

Menke, W. (2018). Factor Analysis. Geophysical Data Analysis (Fourth Edition), 207–222. DOI: https://doi.org/10.1016/B978-0-12-813555-6.00010-1

Neskorodeva, I., & Pustovgar, S. (2015). An Approach to Predicting the Insolvency of Ukrainian Steel Enterprises Based on Financial Potential. Journal of Eastern European and Central Asian Research, 2 (2), 33-43. DOI: https://doi.org/10.15549/jeecar.v2i2.104

Pereira, J., Basto, M., & da Silva, A. (2016). The Logistic Lasso and Ridge Regression in Predicting Corporate Failure. Procedia Economics and Finance, 39, 634-641 DOI: https://doi.org/10.1016/S2212-5671(16)30310-0

Rousseau, R., Egghe, L., & Guns, R. (2018). Statistics. Becoming Metric-Wise, 67-97. DOI: https://doi.org/10.1016/B978-0-08-102474-4.00004-2

Springate, G.L.V. (1978). Predicting the Possibility of Failure in a Canadian Firm. Canada: Simon Fraser University.

Toffler, R., & Tishaw, H. (1977). Going, going, gone – four factors which predict. Accountancy, March, 50-54.

Wilson, T. (1997). Portfolio Credit Risk: part I. RiskMagazine, September, 111-117.

State Statistical Service of Ukraine. (2019). Statistical information January 25, 2019 from http://www.ukrstat.gov.ua/

Koval, L. (2008). Diagnostics and Prevention of Agricultural Enterprises Bankruptcy. Lviv.

On Approval of the Concept of National Security Provision in the Financial Sphere. (2012). Ordinance of the Cabinet of Ministers of Ukraine of 15.08.2012 ? 569-?. Retrieved January 25, 2019 from https://zakon.rada.gov.ua/laws/show/569-2012-%D1%80.

Tereshchenko, O., & Pavlovskyi, S. (2016). To the Issue of Improving Enterprise Anti-Crisis Management Financial Mechanism. Finances of Ukraine, 6, 108-122.

Tereshchenko, O., & Stetsko, M. (2017). Diagnostics of Enterprise Insolvency as the Technique for Financial Decision Making Support. Effective Economy, 3. Retrieved January 25, 2019 from http://www.economy. nayka.com.ua/?op=1&z=5521.

Published

2019-11-30

How to Cite

Neskorodieva, I., Megits, N., Rodchenko, V., Pustovhar, S., & Stamatin, O. . (2019). The methodical approach of bankruptcy probability estimation in an anti-crisis management system of enterprise. Journal of Eastern European and Central Asian Research (JEECAR), 6(2), 259–269. https://doi.org/10.15549/jeecar.v6i2.332

Most read articles by the same author(s)

1 2 3 > >>