Публікації викладачів та співробітників
Постійне посилання на розділhttps://dspace.krok.edu.ua/handle/krok/118
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Документ Analysis of financial statements as a business management tool(MAGNANIMITAS Assn, 2024) Panchenko, Olha; Balazyuk, Oksana; Portovaras, Tetіana; Andrieieva, Vita; Kotkovsky, Volodymyr; Андрєєва, Віта АнатоліївнаIn today's dynamic business environment and intensified competition among companies, the study of financial stability and management efficiency is crucial for any successful organization. Therefore, the analysis of financial statements is a necessary tool for enterprises to make rational management decisions and achieve strategic goals. Additionally, financial analysis is essential in the context of increasing competition and market volatility. The capacity to promptly respond to changes in the economic environment and adapt strategies is increasingly crucial for ensuring enterprise efficiency. Financial statement analysis, in particular, enables companies to assess their financial strength, determine optimal development strategies and make informed decisions in a changing market environment. Financial statement analysis is a crucial aspect of successful management. It involves a systematic analysis of an enterprise's financial and economic activities, including its structure, dynamics, and effectiveness. The scientific literature reviewed in this paper emphasizes the significance of financial statement analysis as a tool for identifying risks, formulating management strategies, and enhancing financial stability. In particular, the article discusses various aspects of the analytical approach, methods and tools of analysis that can help companies make informed management decisions. This article aims to explore the role and importance of financial statement analysis in business management. It covers various aspects of the analytical approach, methods, and implements of analysis to determine how this tool can become crucial for making informed strategic and operational decisions.Документ Structural modeling of the impact of bank nonperforming loans on the banking sector: the Ukrainian experience(LLC CPC Business Perspectives, 2020) Bondarenko, Eugenia; Zhuravka, Olena; Aiyedogbon, John O.; Sunday, Ologunla Emmanuel; Andrieieva, Vita; Андрєєва, Віта АнатоліївнаThe paper aims to develop scientific and methodological approach to assessing the interaction of nonperforming loans of Ukrainian banking institutions, the profitability of the banking sector and its financial stability, which will allow a more detailed assessment of the directions and degree of mutual influence of these elements. To substantiate this interaction economically and mathematically, structural equation modeling was chosen. Particularly, Statistica was chosen as a software tool to assess the adequacy of the resulting model and determine the level of statistical significance of its parameters. Six key indicators were selected as a research information base, two for each subject of research: indicators of nonperforming loans in the banking sector (the volume of nonperforming loans and the ratio of problem loans excluding capital reserves), profitability indicators of the Ukrainian banking sector (assets profit and rate of return on capital), and indicators of financial stability of the Ukrainian banking sector (regulatory capital-to-risk-weighted assets ratio and liquid assets-to-total assets ratio). For calculations, statistic data of selected indicators for 2005-2019 were used. As a result of calculations, mathematical data were obtained that accurately described the interaction of nonperforming loans of Ukrainian banking institutions, the profitability of the banking sector and its financial stability. The adequacy of the model was verified based on the following criteria: main summary statistics (ICSF criterion, ICS criterion, discrepancy function, maximum residual cosine), noncentrality fit indices (noncentrality parameter, population noncentrality parameter, Steiger-Lind RMSEA index, McDonald noncentrality index, adjusted population Gamma index), other single sample indices (Akaike information criterion, Schwarz criterion), and a normal probability plot. © Eugenia Bondarenko, Olena Zhuravka, John O. Aiyedogbon, Ologunla Emmanuel Sunday, Vita Andrieieva, 2020