Issue |
SHS Web Conf.
Volume 91, 2021
Innovative Economic Symposium 2020 – Stable Development in Unstable World (IES2020)
|
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Article Number | 01006 | |
Number of page(s) | 6 | |
Section | Stable Development in Unstable World | |
DOI | https://doi.org/10.1051/shsconf/20219101006 | |
Published online | 14 January 2021 |
Prediction of Financial Health of Business Entities of Selected Sector Using Balance Analysis II. by Rudolf Doucha and Verification of Its Predictive Ability through ROC
University of Zilina, The Faculty of Operation and Economics of Transport and Communications, Department of Economics, Zilina, Slovakia
* Corresponding author: dusan.karpac@fpedas.uniza.sk
Forecasting business failure is a worldwide known term, in a global notion, and there is a lot of prediction models constructed to compute financial health of a company and, by that, state whether a company inclines to financial boom or bankruptcy. A healthy financial management of a business entity is very important for the proper operation of the business, and it is therefore very important to know how to assess financial health and to anticipate possible problems that will be easier to eliminate in advance. Globalized prediction models compute financial health of companies, but the vast majority of models predicting business failure are constructed solely for the conditions of a particular country or even just for a specific sector of a national economy. Predictive models can indicate whether an entity tends to prosper or bankruptcy, and so we can assess the financial health of the business. This paper provides a description of the balance analysis II. by Rudolf Doucha, discusses its application to a sample of 266 Slovak subjects and points to its prediction in the given field. The verification of the ability to forecast bankruptcy or financial stability has been evaluated through ROC analysis.
Key words: Specificity / Financial prediction / ROC curve / AUC
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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