A model has been developed for the optimization of the share structure of an investment portfolio in high-tech projects supported by the leaders of the leading industry companies in Russia. Several indicators (financial leverage, integrated rating of companies, industry rating) were applied in the decision support system for the shared distribution of investments. High-tech production is based on innovative technologies for saving resources, the resiliency of systems for transporting and transferring raw materials and finished products within Russia, so the main income will remain within the country. It is possible to export high-tech products, rather than raw materials, which will increase export revenues. Investors will invest in high-tech projects of Russian companies, taking into account the targeting of investment development. The guarantee is the stable financial position of the companies and the competitiveness rating. Methods: The authors propose a new approach that does not contradict modern rating scales, based on a hierarchical rating procedure and fuzzy logical rules that allow you to build an integral rating in the form of portfolio shares from the whole. A higher share shows an indicator of the higher investment attractiveness of companies. The industry rating is obtained based on the principle of the company’s first affiliation to the highest rating indicator. The final minimax portfolio is based on the initial ratings in a circular convolution and is then adjusted by industry. A software package has been compiled that allows the testing of the method of capital allocation between investment projects for the largest companies’ leaders of high-tech industries in Russia. This software uses the author’s method of multi-stage analysis, the evaluation of financial coefficients, the integral ranking and the correction of the solution taking into account the industry attributes. Results: The results are presented with computer-aided design (CAD) in the form of an algorithmized decision support system (DSS). The CAD system is based on a hierarchical algorithm, based on the use of a multi-level redistribution of investment shares of high-tech companies, taking into account the adaptation to the requirements of the return on investment portfolio. When compiling the portfolio, the minimax optimality criterion is applied, which allows the stabilization of the risk by purposefully redistributing funds between the companies involved in the analysis. The authors of the article have compiled an algorithm for the software implementation of the model. Features of the rating approach: the use of the author’s mathematical apparatus, which includes a hierarchical analysis of the ranked indicators of the financial and economic activity of companies, taking into account their priority, and the use of a minimax approach to obtain a rating assessment of companies, taking into account the industry attributes. Development: The proposed approach should be used for targeted financing of large industry companies engaged in the implementation of high-tech projects.
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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.