From the time of Altman and the first bankruptcy prediction models, the prediction of default of companies is in the centre of interest of many economists and scientists all over the world. For companies, early detection of the possible threat of imminent financial difficulties or even bankruptcy is a very important part of financial analysis. Over the last few years, many predictive models have been created in the world. However, it has been shown that these models are not very well transferable to the conditions of the economy of another country and their prediction or rating power in another country is lower. Therefore, it is best to create a specific predictive model in the country that takes into account the situation of companies on the basis of real data on their financial situation. This paper is focused on creating a model of failure prediction of small companies in Slovakia using a well-known and widely used method of multivariate discriminant analysis. Discriminant analysis is one of the oldest multivariate statistical methods and sometimes it is difficult to fulfil certain assumptions for data. However, its results are easily interpretable and can be used to classify a company to the group of companies with risk of financial difficulties or, on the contrary, between well-prosperous companies. Prediction model is created based on real data on Slovak enterprises and has a strong classification ability in the specific conditions of the Slovak Republic.
Ivana Podhorska, Maria Kovacova and Katarina Valaskova
The issue of enterprise in bankrupt or financial health as a whole is still very actual topic not only in Slovakia but also in abroad. Works dealing with the enterprise in bankruptcy have already appeared in the 1930s of the 20th century. Bankrupt of enterprise affect all subject in relationship with this enterprise. Financial experts were looking for the ways for enterprise bankrupt prediction. This article is based on the searching for key factors that could indicate the enterprise in bankrupt in Slovak conditions. This article tries to work with financial variables from the area of financial health assessment of enterprise and works with the sample of Slovak enterprises. This sample includes 8,522 financial statements of enterprises in 2016. According to several relevant decisions rules, for example, the value of equity or equity debt ratio, enterprises are divided into two categories – bankrupt enterprises and creditworthy enterprises. Subsequently, this article tries to find statistically significant financial variables that could indicate involving enterprises in these two categories and works with several statistical methods for searching significant relationship between variables and the tightness of relations between them. As a main statistical method, Pearson´s correlation coefficient is used, which is supported by correlation matrices. In addition, it is necessary to test an existence of outliers in the sample of enterprises. Existence of outliers is tested by the Grubbs test of outliers.
Ivana Podhorska, Katarina Valaskova, Vojtech Stehel and Tomas Kliestik
The paper deals with the possibilities of company goodwill valuation and verification. The value of company goodwill is still an actual issue for the scientific community. Goodwill as an economic phenomenon has attracted the attention of economic experts since the nineteenth century. Nowadays, there are many approaches to goodwill valuation. However, its identification and quantification are still a challenge. The paper aim is to identify significant sources of company goodwill creation and their verification on the sample of 2 European countries with the similar business environment, political stability and regulatory platform - Slovak and Czech companies. The sample for the identification of significant sources of company goodwill creation consists of the financial statements of Slovak companies in 2015. The sample for data verification consists of the financial statements of Slovak and Czech companies in 2016. The paper identifies the determinants of goodwill creation by multiple regression analysis. The paper also verifies the total explanatory power of these determinants by matrixes of changes. Volatility and deviation of the results are captured by descriptive statistical methods. The paper’s results point to a necessity to identify the key determinants of goodwill creation. They bring the construction of an econometric model for company goodwill valuation. It could be used to compute the value of company goodwill of the individual companies in the Slovak economic conditions.