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    Wyświetlanie 1-4 z 4
    Tytuł:
    Being an outlier: a company non-prosperity sign?
    Autorzy:
    Svabova, Lucia
    Durica, Marek
    Powiązania:
    https://bibliotekanauki.pl/articles/22446412.pdf
    Data publikacji:
    2019
    Wydawca:
    Instytut Badań Gospodarczych
    Tematy:
    bankruptcy prediction models
    financial ratios
    failure prediction
    financial distress
    Opis:
    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.
    Źródło:
    Equilibrium. Quarterly Journal of Economics and Economic Policy; 2019, 14, 2; 359-375
    1689-765X
    2353-3293
    Pojawia się w:
    Equilibrium. Quarterly Journal of Economics and Economic Policy
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Logit business failure prediction in V4 countries
    Autorzy:
    Durica, Marek
    Valaskova, Katarina
    Janoskova, Katarina
    Powiązania:
    https://bibliotekanauki.pl/articles/125652.pdf
    Data publikacji:
    2019
    Wydawca:
    Politechnika Białostocka. Oficyna Wydawnicza Politechniki Białostockiej
    Tematy:
    logit
    business failure
    financial ratio
    prediction model
    V4 countries
    funkcja logitowa
    niepowodzenie biznesowe
    wskaźnik finansowy
    model prognostyczny
    kraje V4
    Opis:
    The paper presents the creation of the model that predicts the business failure of companies operating in V4 countries. Based on logistic regression analysis, significant predictors are identified to forecast potential business failure one year in advance. The research is based on the data set of financial indicators of more than 173 000 companies operating in V4 countries for the years 2016 and 2017. A stepwise binary logistic regression approach was used to create a prediction model. Using a classification table and ROC curve, the prediction ability of the final model was analysed. The main result is a model for business failure prediction of companies operating under the economic conditions of V4 countries. Statistically significant financial parameters were identified that reflect the impending failure situation. The developed model achieves a high prediction ability of more than 88%. The research confirms the applicability of the logistic regression approach in business failure prediction. The high predictive ability of the created model is comparable to models created by especially sophisticated artificial intelligence approaches. The created model can be applied in the economies of V4 countries for business failure prediction one year in advance, which is important for companies as well as all stakeholders.
    Źródło:
    Engineering Management in Production and Services; 2019, 11, 4; 54-64
    2543-6597
    2543-912X
    Pojawia się w:
    Engineering Management in Production and Services
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Decision tree based model of business failure prediction for Polish companies
    Autorzy:
    Durica, Marek
    Frnda, Jaroslav
    Svabova, Lucia
    Powiązania:
    https://bibliotekanauki.pl/articles/19090954.pdf
    Data publikacji:
    2019
    Wydawca:
    Instytut Badań Gospodarczych
    Tematy:
    decision trees
    prediction model
    financial ratios
    business failure
    Polish companies
    Opis:
    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.
    Źródło:
    Oeconomia Copernicana; 2019, 10, 3; 453-469
    2083-1277
    Pojawia się w:
    Oeconomia Copernicana
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Evaluation of the impacts of the COVID-19 pandemic on the development of the unemployment rate in Slovakia: counterfactual before-after comparison
    Autorzy:
    Svabova, Lucia
    Tesarova, Eva Nahalkova
    Durica, Marek
    Strakova, Lenka
    Powiązania:
    https://bibliotekanauki.pl/articles/22444343.pdf
    Data publikacji:
    2021
    Wydawca:
    Instytut Badań Gospodarczych
    Tematy:
    unemployment
    labour market
    COVID-19
    counterfactual evaluation
    Opis:
    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.
    Źródło:
    Equilibrium. Quarterly Journal of Economics and Economic Policy; 2021, 16, 2; 261-284
    1689-765X
    2353-3293
    Pojawia się w:
    Equilibrium. Quarterly Journal of Economics and Economic Policy
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-4 z 4

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