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    Tytuł:
    Management of financial risks in Slovak enterprises using regression analysis
    Autorzy:
    Valaskova, Katarina
    Kliestik, Tomas
    Kovacova, Maria
    Powiązania:
    https://bibliotekanauki.pl/articles/18799016.pdf
    Data publikacji:
    2018
    Wydawca:
    Instytut Badań Gospodarczych
    Tematy:
    financial risk
    default
    bankruptcy
    regression model
    Opis:
    Research background: Financial risk management is the task of monitoring financial risks and managing their impact. Financial risk is often perceived as the risk that a company may default on its debt payments. The issue of the debt, default or prosperity of the company are presented in the article as one of the ways of the risk management. A prediction of corporate default is an inseparable element of the risk management. Mainly the consequences of risk are the engine of research and development of methods and models, which enable to predict economic and financial situation in specific conditions of global economies. Purpose of the article: The main aim of the presented article is to assess financial risks of Slovak entities, realized by the identification of significant factors and determinants affecting the prosperity of Slovak companies. Methods: To conduct the research we have used the data of Slovak enterprises, obtained from annual financial reports covering the year 2015 and the calculated financial ratios of profitability, activity, liquidity and indebtedness that may affect the financial health of the company were applied in the regression analysis. Realizing the multiple regression analysis, the statistically significant determinants that affect the future financial development of the company are identified, as well as the regression model of the bankruptcy prediction. Findings & Value added: In the research aimed at the management of financial risks in Slovak enterprises, we focused on the revelation of significant economic risk factors using multiple regression. The results suggest that the most significant predictors are net return on capital, cash ratio, quick ratio, current ratio, net working capital, RE/TA ratio, current debt ratio, financial debt ratio and current assets turnover based on which the decision about the future company default can be made. These factors are significant enough to manage financial risks and to affect the profitability and prosperity of the company.
    Źródło:
    Oeconomia Copernicana; 2018, 9, 1; 105-121
    2083-1277
    Pojawia się w:
    Oeconomia Copernicana
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Bankruptcy prediction in the post-pandemic period: A case study of Visegrad Group countries
    Autorzy:
    Valaskova, Katarina
    Gajdosikova, Dominika
    Belas, Jaroslav
    Powiązania:
    https://bibliotekanauki.pl/articles/19322751.pdf
    Data publikacji:
    2023
    Wydawca:
    Instytut Badań Gospodarczych
    Tematy:
    bankruptcy
    prediction model
    multiple discriminant analysis
    Visegrad group countries
    Opis:
    Research background: Effective monitoring of financial health is essential in the financial management of enterprises. Early studies to predict corporate bankruptcy were published at the beginning of the last century. The prediction models were developed with a significant delay even among the Visegrad group countries. Purpose of the article: The primary aim of this study is to create a model for predicting bankruptcy based on the financial information of 20,693 enterprises of all sectors that operated in the Visegrad group countries during the post-pandemic period (2020-2021) and identify significant predictors of bankruptcy. To reduce potential losses to shareholders, investors, and business partners brought on by the financial distress of enterprises, it is possible to use multiple discriminant analysis to build individual prediction models for each Visegrad group country and a complex model for the entire Visegrad group. Methods: A bankruptcy prediction model is developed using multiple discriminant analysis. Based on this model, prosperity is assessed using selected corporate financial indicators, which are assigned weights such that the difference between the average value calculated in the group of prosperous and non-prosperous enterprises is as large as possible. Findings & value added: The created models based on 6-14 financial indicators were developed using different predictor combinations and coefficients. For all Visegrad group countries, the best variable with the best discriminating power was the total indebtedness ratio, which was included in each developed model. These findings can be used also in other Central European countries where the economic development is similar to the analyzed countries. However, sufficient discriminant ability is required for the model to be used in practice, especially in the post-pandemic period, when the financial health and stability of enterprises is threatened by macroeconomic development and the performance and prediction ability of current bankruptcy prediction models may have decreased. Based on the results, the developed models have an overall discriminant ability greater than 88%, which may be relevant for academicians to conduct further empirical studies in this field.
    Źródło:
    Oeconomia Copernicana; 2023, 14, 1; 253-293
    2083-1277
    Pojawia się w:
    Oeconomia Copernicana
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Systematic review of variables applied in bankruptcy prediction models of Visegrad group countries
    Autorzy:
    Kovacova, Maria
    Kliestik, Tomas
    Valaskova, Katarina
    Durana, Pavol
    Juhaszova, Zuzana
    Powiązania:
    https://bibliotekanauki.pl/articles/19106225.pdf
    Data publikacji:
    2019
    Wydawca:
    Instytut Badań Gospodarczych
    Tematy:
    bankruptcy
    bankruptcy prediction
    variables
    countries of Visegrad four
    Opis:
    Research background: Since the first bankruptcy prediction models were developed in the 60's of the 20th century, numerous different models have been constructed all over the world. These individual models of bankruptcy prediction have been developed in different time and space using different methods and variables. Therefore, there is a need to analyse them in the context of various countries, while the question about their suitability arises. Purpose of the article: The analysis of more than 100 bankruptcy prediction models developed in V4 countries confirms that enterprises in each country prefer different explanatory variables. Thus, we aim to review systematically the bankruptcy prediction models developed in the countries of Visegrad four and analyse them, with the emphasis on explanatory variables used in these models, and evaluate them using appropriate statistical methods. Methods: Cluster analysis and correspondence analysis were used to explore the mutual relationships among the selected categories, e.g. clusters of explanatory variables and countries of the Visegrad group. The use of the cluster analysis focuses on the identification of homogenous subgroups of the explanatory variables to sort the variables into clusters, so that the variables within a common cluster are as much similar as possible. The correspondence analysis is used to examine if there is any statistically significant dependence between the monitored factors ? bankruptcy prediction models of Visegrad countries and explanatory variables. Findings & Value added: Based on the statistical analysis applied, we confirmed that each country prefers different explanatory variables for developing the bankruptcy prediction model. The choice of an appropriate and specific variable in a specific country may be very helpful for enterprises, researchers and investors in the process of construction and development of bankruptcy prediction models in conditions of an individual country.
    Źródło:
    Oeconomia Copernicana; 2019, 10, 4; 743-772
    2083-1277
    Pojawia się w:
    Oeconomia Copernicana
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-3 z 3

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