Scientific Journal of KubSAU

The analysis of economic effect of new method of estimation of financial performance is reviewed in the article. The example of the program’s work, which determines financial performance of a company with advertising investments, is described and the mostly important results are discussed

The article provides a comparative analysis of assessments of the socio-economic development of the Krasnodar region from such well-known rating agencies as Standard & Poors, Moody’s, Fitch Ratings, which belong to the United States of America. The studied ratings are compared with the ratings of the national agency of the Russian Federation called “Expert RA”. The values of the established ratings are examined, as well as number of possible reasons why the ratings of the United States of America differ from the ratings of the Russian Federation, for example, economic and political reasons, and, subsequently, how these ratings affect the investment attractiveness of the Krasnodar region. The article explains positive and negative aspects of the integrated methodology used by international rating agencies, consisting of software and expert opinion, the level of access to it for study and analysis. We study another (local) source of information on the investment attractiveness of the Krasnodar region, which is a state institution, namely the Department of Investments and Development of Small and Medium Enterprises of the Krasnodar region. Options are proposed for improving the system of analysis of statistical data through methods that are based on a clear mathematical approach to provide an adequate assessment of the region and municipalities without the influence of subjective expert opinion

This article is devoted to a problem of effective management of a financial and economic condition of companies on the example of the enterprises of oil products supply. We consider questions of support of adoption of management decisions which concern stabilization of a financial condition of the company and as a result of decrease in financial risks. The article also provides a description of the program complex called FESP_ON developed by the authors allowing to carry out the profound complex assessment of a financial and economic condition of Societies of oil products supply

The article discusses the use of machine learning methods and fuzzy production systems for studying the social and economic development of urban districts, areas and settlements of the Krasnodar region. The fundamental patterns and their connection with quantitative and qualitative indicators are considered

This article is devoted to rating assessment of the socio-economic situation of the Krasnodar region, presented by such agencies as "RAEKS-Analytics", "Expert RA" and "National Rating Agency". The methodologies used by these agencies were studied and analyzed. A comparison of these methodologies was also conducted. As a result, a number of their shortcomings were identified, including the lack of a complete methodological model in the public domain. Some agencies do not provide links to statistics that are used in the analysis. In the article using the STATISTICA environment, a statistical analysis of data reflecting the level of socio-economic situation of the Krasnodar region is carried out. Based on the work [12], the article created a discriminant model for assessing the socio-economic development of urban districts of the Krasnodar region with a confidence of 85%. The study conducted a cluster, discriminant, classification (decision trees), coefficient (proposed by the authors) based on the data of the Federal State Statistics website for the period from 2009 to 2018 in the city districts: Krasnodar, Anapa, Armavir, Gelendzhik, Goryachiy Klyuch, Novorossiysk Sochi. During the study, analyzes such as cluster and classification trees showed poor results, since they are not able to detect latent nonlinear relationships between the study indicators. Using the constructed discriminant model, we have carried out an analysis of the socio-economic development of urban districts of the Krasnodar region for the period 2009-2018, which allows us to identify the leaders and the outsiders