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Research purpose. Financial distress being a global phenomenon makes it impact firms in all sectors of the economy and predicting corporate bankruptcy has become a crucial issue in economics. At the beginning of the last century, the first studies aimed to predict corporate bankruptcy were published. In Slovakia, however, several prediction models were developed with a significant delay. The main aim of this paper is to develop a model for predicting bankruptcy based on the financial information of 3,783 Slovak enterprises operating in the manufacturing and construction sectors in 2020 and 2021.

The business environment is an integral part of all business activity. Every business operates in a certain atmosphere that is dynamic and has a constant impact on the business. Therefore, it is important to analyse and predict the development of the business environment.

Research background: Debt is considered a normal part of enterprises these days. If enterprises do not have enough equity, they will start to use a large amount of debt which is mainly associated with indebtedness. Rising indebtedness can be a difficult financial situation for business entities in the form of default and inability to meet their liabilities.

The financial markets, shaped by dynamic forces, including macroeconomic trends and technological advancements, are influenced by a multitude of factors impacting the S&P 500 stock index, a pivotal indicator in the US equity markets. This paper highlights the significance of understanding the exogenous variables affecting the index's profitability for academics, portfolio managers, and investment professionals. Amid the global ramifications of the S&P 500, particularly in combating the eroding purchasing power caused by inflation, investing in stock indexes emerges as a means to safeguard wealth. The study employs various statistical techniques, emphasizing a methodical approach to uncover influential variables, and using static regression and autoregressive models for immediate and time-lagged effects. In conclusion, the findings have broad practical implications beyond investment strategy, extending to portfolio construction and risk management. Acknowledging inherent uncertainties in financial market forecasts, future research endeavors should target long-term trends, specific influences, and the impact of exchange rate fluctuations on index evolution. Collaboration across regulatory bodies, academia, and the financial industry is underscored, holding the potential for effective risk monitoring and bolstering overall economic and financial market stability. This research serves as a foundational step towards enhancing market understanding and facilitating more efficient investment decision-making approaches. [ABSTRACT FROM AUTHOR]

Background and Purpose: Models of identifying and predicting earnings management in companies by using accruals are in general based on the dependence between total assets of companies and various profit measures. In this paper, we focused on an initial dependency analysis between these business indicators in the Visegrad group’s business entities. We explore the mentioned relationships, verify, and quantify the strength of the dependencies between earnings levels of companies (in terms of economic evaluation of the return on business capital in absolute terms) and the value of their total assets (i.e. business capital tied in the assets without its further classification and analysis).

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.

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.

Background and Purpose: Behavioural finance is a relatively new, but rapidly evolving field that provides explanations of an economic decision-making by cognitive psychology, conventional economic and financial theory. Behavioural finance searches the influence of psychology on the behaviour of financial practitioners and the subsequent effects on the financial markets. The purpose of the paper is the research on behavioural aspects of financial decision-making as they help explain why and how markets might be inefficient.

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.

Research background: The corporate debt situation can be considered a crucial factor influencing the future development of the financial performance of the firm. It is essential for every business entity to know its financial health, its strengths and weaknesses, and how its business has been affected by the COVID-19 pandemic and all the changes it has brought. Purpose of the article: The main aim of this paper is to explain and quantify the consequences of the COVID-19 pandemic, analyze changes in the growth of crucial determinants, and identify new trends in Slovak enterprises throughout the monitored period of 2018-2021. Methods: Hence, a statistically significant difference between the individual indicators due to the period in which the firms achieved these values was determined using the Friedman test. It determined whether the average values of the financial indicators remained constant over the period under review (the years 2018 and 2019 are considered pre-COVID-19 years, while 2020 and 2021 are years when the globe was already being impacted by the outbreak of the COVID-19 pandemic) or whether the individual values of the indicators differed significantly. Findings & value added: Considering that there are statistically significant differences in the indicators of self-financing ratio, current indebtedness ratio, and equity leverage ratio in all monitored periods except for the years 2020 and 2021, where the average values of these debt indicators are the same, the results indicate that the COVID-19 pandemic also negatively impacted the indebtedness of Slovak enterprises. Although this research paper, focusing on the financial performance of the firms in the post-pandemic period, is pioneering in Slovakia, the biggest contribution of the study is the application of the latest information, which could help in more precise monitoring of corporate financial stability and debt policy during the current challenging period. The obtained results provide important universal guidelines for building financial strategies improving long-term financial resilience of enterprises. [ABSTRACT FROM AUTHOR]

Research background: Earnings is a source of information for capital owners, potential investors, competitors, customer and supplier of the company. Managers have the direct motivation and knowledge and use adequate techniques to adjust legally the reported earnings to meet the specific requirements of the company and achieve stable financial results. Thus, earnings management is currently the most provocative and highly topical issue in the field of finance and accounting at the global perspective. Purpose of the article: The main purpose of the paper is to detect the manipulation with earnings in a specific sector of economy, following the global principles of financial reporting, and to reveal the degree of manipulation of enterprises in the selected countries of the Visegrad grouping. Methods: The model of Beneish M-score is applied using the sectoral data and compares the level of manipulation in the period 2015-2019. The Beneish model is a mathematical-statistical model that uses financial ratios calculated with accounting data of a specific enterprise aimed to detect if an enterprise is likely that the reported earnings of the company were manipulated. Findings & Value added: The paper monitors the development of the manipulation with earnings in the given sector (enterprises tend to manage earnings upwards), and analyses the influences of macroeconomic factors on the phenomenon of earnings management. The detection of earnings management by M-score helps protect business partners of an enterprise against fraudulent behaviour, especially in the global environment.

Research background: Legal earnings manipulation is current hot topic, which is evidenced by a significant number of academic articles from the countries of developed markets. But this issue has been still the research gap for the emerging countries. Slovakia and Bulgaria are emerging counties with the similar economic and political history. The existence of the purposeful earnings management is confirmed in both countries. Therefore, the enterprises from these countries are selected to the common comparison. Purpose of the article: The main purpose and the set target of delivered examination is to disclose significant conformity or discrepancy in the dimension of the legal managers’ earnings modification in the Slovakian and Bulgarian enterprises. Methods: The provided financial modelling used 1,089 Slovak enterprises and 1,421 Bulgarian enterprises. Two parametric tests were computed for this study. Fisher’s F-test to detect the ratio between the variances of the populations, and t-test for two independent samples to test provided hypothesis of the article. Findings & Value added: The paper aimed at the earnings before interest, taxes (EBIT) in two emerging countries under a global magnifier. It was detected that the dimension of financial managers’ earnings manipulations in the Slovakian and Bulgarian enterprises is not significantly different. The similar nature of the approach of the management to the earnings manipulation was identified.

Research background: One of the significant problems of corporate financial management in the international context is the appropriate determination of the total amount of capital as well as the correct composition of financial sources to finance the activities of enterprises. The determination of the optimal capital structure, and thus the minimization of the costs of capital have been of interest to authors worldwide for several decades, as they can significantly influence the level of corporate earnings. Purpose of the article: The main aim of the paper is to find a mathematical formula to determine whether the indebtedness of an enterprise is related to any financial problems or does not affect the financial performance of an enterprise and thus contributes to the profitability, i.e. if the debt management is performed efficiently. Methods: To find the mathematical formula, we used the financial data of enterprises operating in the selected Visegrad group and calculated the financial ratios of indebtedness, which were further used in the multiple discriminant analysis. The final discriminant function and calculated centroids allow dividing the enterprises into two different groups, with and without financial problems. Findings & Value added: The results of this analysis can be used in the international context to determine the appropriate level of indebtedness also in other countries, not only in the Visegrad group, which may be helpful for corporate financial managers or creditors, because optimal indebtedness helps generate revenues.