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Being an outlier: a company non-prosperity sign?

100%
Svabova L., Durica M.
Equilibrium. Quarterly Journal of Economics and Economic Policy
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2019
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vol. 14
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issue 2
359-375
EN
Research background: The state of financial distress or imminent bankruptcy are very difficult situations that the management of every company wants to avoid. For these reasons, prediction of company bankruptcy or financial distress has been recently in a focus of economists and scientists in many countries over the world. Purpose of the article: Various financial indicators, mostly financial ratios, are usually used to predict the financial distress. In order to create a strong prediction model and a statistically significant prediction of bankruptcy, it is advisable to use a deep statistical analysis of the data. In this paper, we analysed the real financial ratios of Slovak companies from the year 2017. In the phase of data preparation for further analysis, we checked the existence of outliers and found that there are some companies that are multivariate outliers because are significantly different from other companies in the database. Thus, we deeply focused on these outlying companies and analysed whether to be an outlier is a sign of financial distress. Methods: We analysed whether there are much more non-prosperous companies in the set of outlier companies and if their financial indicators are significantly different from those of the prosperous companies. For these analyses, we used testing of the statistical hypotheses, such as the test for equality of means and chi-square test. Findings & Value added: The ratio of non-prosperous companies between the outliers is significantly higher than 50 % and the attributes of non-prosperity and being an outlier are dependent. The means of almost all financial ratios of prosperous and non-prosperous companies among outliers are significantly different.
2
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Evaluation of the impacts of the COVID-19 pandemic on the development of the unemployment rate in Slovakia: counterfactual before-after comparison

81%
Svabova L., Tesarova E. N., Durica M., Strakova L.
Equilibrium. Quarterly Journal of Economics and Economic Policy
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2021
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vol. 16
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issue 2
261-284
EN
Research background: The COVID-19 pandemic, which hit the world in the first quarter of 2020, has impacted almost every area of people's lives. Many states have introduced varying degrees of measures to prevent its spread. Most of these measures were, or still are, aimed at reducing or completely stopping the operation of shops and services, or in some cases, also the large manufacturing companies. However, as many companies have failed to cope with these restrictions, unemployment has risen in almost all EU countries. A similar situation was also observed in Slovakia, where the mentioned measures also had a significant impact on unemployment. Purpose of the article: In this study, we deal with the quantification of the impact of a pandemic, or more precisely, anti-pandemic measures, on the development of the registered unemployment rate in Slovakia. Methods: This quantification is based on the counterfactual method of before-after comparison, which is one of the most widely used methods in the field of impact assessments and brings very accurate results, based on real data. In the analysis, we use officially published data on the unemployment rate in Slovakia during the years 2013?2020 on a monthly basis. Such a long time series, using statistical methods of its decomposition and modelling of its trend, will allow predicting the development of the unemployment rate in Slovakia, assuming a counterfactual situation of no pandemic, and compare this development with the actual situation that occurred during 2020. Findings & Value added: The study results indicate an increase in the unemployment rate in Slovakia during 2020 by 2?3% compared to the trend of its development, which would have occurred without a pandemic. Given the counterfactual method used, this difference can be described as the impact of the COVID-19 pandemic. The results of the study can be used in practice in the design and implementation of measures introduced to mitigate the impacts of the pandemic on unemployment and, in the long-term perspective, also to eliminate these effects as much as possible. It can also be used as a theoretical tool in conducting impact assessments, which have so far been carried out very rarely in Slovakia.
3
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Decision tree based model of business failure prediction for Polish companies

81%
Durica M., Frnda J., Svabova L.
Oeconomia Copernicana
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2019
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vol. 10
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issue 3
453-469
EN
Research background: The issue of predicting the financial situation of companies is a relatively young field of economic research. Its origin dates back to the 30's of the 20th century, but constant research in this area proves the currentness of this topic even today. The issue of predicting the financial situation of a company is up to date not only for the company itself, but also for all stakeholders. Purpose of the article: The main purpose of this study is to create new prediction models by using the method of decision trees, in achieving sufficient prediction power of the generated model with a large database of real data on Polish companies obtained from the Amadeus database. Methods: As a result of the development of artificial intelligence, new methods for predicting financial failure of the company have been introduced into financial prediction analysis. One of the most widely used data mining techniques in this field is the method of decision trees. In the paper, we applied the CART and CHAID approach to create a model of predicting the financial difficulties of Polish companies. Findings & Value added: For the creation of the prediction model, a total of 37 financial and economic indicators of Polish companies were used. The resulting decision trees based prediction models for Polish companies reach a prediction power of more than 98%. The success of the classification for non-prosperous companies is more than 83%. The created decision tree-based prediction models are useful mainly for predicting the financial difficulties of Polish companies, but can also be used for companies in another country.
4
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Detecting earnings manipulation and fraudulent financial reporting in Slovakia

81%
Svabova L., Kramarova K., Chutka J., Strakova L.
Oeconomia Copernicana
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2020
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vol. 11
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issue 3
485-508
EN
Research background: Misleading financial reporting has a negative impact on all stakeholders since financial records are the primary source of information on financial stability, economic activity, and financial health of any company. The handling of them is primarily the responsibility of managers or owners and reasons for doing so may differ. Their common denominator is the artificial creation of information asymmetry to get different types of benefits. It is, therefore, logical that the issue of detecting opportunistic earnings management comes to the fore. Purpose of the article: The purpose of the study is to create a discriminant model of the detection of earnings manipulators in the conditions of the Slovak economy.  Methods: We used the discriminant analysis to create a model to identify fraudulent companies, based on the real data on companies that were convicted from misleading financial reporting in connection with tax fraud in the years 2009-2018. The model is inspired by the Beneish model, which is one of the most applied fraud detection methods at all. Findings & Value added: In order to achieve more accurate detection results, we extended the original model by taking into account the values of indicators from three consecutive years, i.e. by taking into account the development of the potential tendency of companies to be involved in opportunistic earnings management. Our model correctly identified 86.4% of fraudulent companies and overall reaches 84.1% classification ability. Both models were applied on empirical data on 1,900 Slovak companies from the years 2016-2018, while their overlap was 32.7% for fraudulent companies and 38.4% for non-fraud companies. This is a very useful result, as the application of both models rein-forces the results obtained and the identical classification of the company into fraudulent indicates that the manipulation of earnings occurs with a high probability.
5
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New paradigms of quantification of economic efficiency in the transport sector

71%
Poliak M., Svabova L., Konecny V., Zhuravleva N. A., Culik K.
Oeconomia Copernicana
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2021
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vol. 12
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issue 1
193-212
EN
Research background: In determining the prices in road transport, carriers usually use the calculations based on a so-called routes utilisation coefficient, which allows the carrier to also take the possibility of the return rides without load into account. Currently, it is usually used as a constant from the interval from zero to one. Purpose of the article: Considering a different offer of return transport from individual European Union (EU) countries, it can be assumed that the routes utilisation coefficient should have different values because there is a varying level of non-zero probability that the vehicle will return without a load. This study therefore proposes a new approach to determining the value of this coefficient based on transport direction. The study also aims to identify clusters of EU countries, for which the common value of the coefficient should be set. Methods: The Analysis of Variance (ANOVA) test was used to verify the assumption of the differences among the means of transport offers. Cluster analysis was used to identify the aforementioned groups of countries. This analysis is based on real data on transport offers to Slovakia from 18 different EU countries. Findings & value added: The results of the analysis can also be used in other EU countries because if significant differences in transport offers to Slovakia exist in individual countries, there is a reasonable assumption that this conclusion will also be valid in other countries. The analysis demonstrated that it is more appropriate to use the routes utilisation coefficient with various values, dependent on the transport direction. For the transport companies, implementation of the obtained results into practice is beneficial to increase their competitiveness through the more precise setting of transport prices, but also to the optimisation of the transport price itself with regard to the expected costs.
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