The article discusses the issues of financial stability of enterprises in unstable economic conditions. The authors propose a formal model of the gradual quantitative assessment of the financial stability of enterprises based on the use of regression equations with determination coefficients. The financial stability of enterprises is described by the indicators of their financial status according to the regional-average and industry-average levels. A qualitative assessment of the financial stability potential of enterprises is given based on the interpretation of deviations of the financial stability coefficients. The article defines the limiting values of financial stability of enterprises, the output of which allows the unambiguous interpretation of this concept and its level. An example that determines the financial stability of various Russian enterprises is also presented.

In the oil and gas industry, which is the basis of the Russian energy market, a significant and urgent question arises: How to distribute companies according to their investment attractiveness? Accordingly, quantitative indicators are needed. Lacking extensive experience in the practical implementation of fundamental rating tools, work is needed to develop methodologies of weighting coefficients and lists, built on the experience of the “big three” rating agencies. The article proposes an algorithm for forming an integral rating of companies based on financial reporting indicators and the author’s rules of fuzzy logic based on the principle of “circular convolution”, from the best to the slave, deepening the analysis to the center, when all companies are exhausted and places in the rating are distributed. The problem of assessing and integrally indexing the indicators of large companies in leading sectors of the economy (e.g., oil and gas, banks, electricity) is becoming manifest, while it is obvious that there is competition between large companies of the country’s leading industries for state investment resources. The nature of the leading industries is such that it is necessary to assess the quality of the company’s functioning based on the formation of rating groups. Based on the rating, investments are distributed among the companies under consideration. The author has developed a portfolio model that is analogous to the Harry Max Markowitz model, which does not contradict this model but allows consideration of a broader range of risk assessments used in the model (for example, the rating of companies). The optimal portfolio is built, taking into account the resulting index and the initial grouping in the hierarchical data correction mode. The logically sequential method of circular convolution of four important indicators to an integral index and a mathematically substantiated method for optimizing the minimax portfolio presented in the work will allow the investor to develop optimal (from the point of view of the transparency of the apparatus used, mathematical feasibility and time spent on the implementation of the software package) tools for investing and enlarging his capital.

In this article, the problem of modeling a time series using the Minimax method is considered. The expediency of using Minimax to identify points of change in trends and the range of changes in the graphical figures of technical analysis is justified. Spline approximation of the dynamic process with range constraints was performed to improve the quality of the model. Investors are advised to refrain from making hasty decisions in favor of holding reliable shares (such as PJSC Novatek shares), rather than selling them. The purchase of new shares should be carefully analyzed. Through an approximation of the dynamic number of the applicable optimization problem of minimizing the maximum Hausdorff distances between the ranges of the dynamic series and the values of the approximating function, the applied approach can provide reliable justification for signals to buy shares. Energy policy occupies the highest place in the list of progress ratings according to news analytics of businesses related to the energy sector of the economy. At the same time, statistical indicators and technologies of expert developments in this field, including intellectual analysis, can become an important basis for the development of a robotic knowledge program in the field under study, an organic addition to which is the authors’ methodology of development in energy economics as in energy policy. This paper examines the model of approximation of the multivalued time series of PJSC Novatek, represented as a series of ranges of numerical values of the indicators of financial markets, with constraints on the approximating function. The authors consider it advisable for promising companies to apply this approach for successful long-term investment.

At the present stage, the whole world is facing serious energy challenges, including the rapid growth of energy consumption, the inevitable exhaustion of energy resources with an extremely uneven distribution, a large environmental burden on nature, and the globalization of energy. The electric power industry harms the environment with its excessive emissions of pollutants, which is reflected globally. The article first of all offers a literary review of studies on this topic. A comparative description of the achievements of countries in the field of emission schedules is proposed, as well as the prospects for drawing up a schedule of emission intensity for the period up to 2030 in comparison with countries. In addition, this paper presents unresolved problems that impede sustainable development, which guarantees the stability of the future existence of mankind. These challenges hamper the sustainable development of the energy industry in the long term and the global sustainable development and prospects for green economic growth of the country. Thus, the relevance of the subject of the study is due to the lack of resources, reflecting the relationship of trends in reducing pollution from the activities of industry with the conditions of economic growth.

The article describes key tendencies of the Russian tourist market development as an integral part of the global market. Special attention is paid to the Stavropol Krai tourism market, listed in the top 10 most tourism attractive regions of Russia and to the Caucasian Mineral Waters region, as the main region tourism destinations. The analysis of competitive advantages of resorts in Caucasian Mineral Waters relatively to the world's leading thermal spas reveals the regional resorts competitiveness by price. The comparative analysis indicated the high price competitiveness of services by Caucasian Mineral Waters resorts compared to foreign ones. However, even competitive regions may have very low flows of tourists because of the infrastructure inconsistency (full or partial) to the tourists' goals. The main obstacle, proved to inhibit turning the region with competitive natural and cultural characteristics into a full-fledged tourist destination, is the poor quality of accommodation, as well as the low level of development of the systematic infrastructure. Key infrastructure constraints hampering the further development of a tourist cluster in Caucasian Mineral Waters are disclosed, and recommendations for their mitigation are given.