Purpose of research. The actuality of the problem of the integrated (complex) assessment of investment attractiveness of large Russian companies is due to the need of increasing production volumes and improves processing technologies of the largest sectors of the Russian economy, as well as the requirements of the accelerated growth of high-tech exports. The purpose of this study is to develop rating of investment attractiveness of companies using minimax approach and hierarchical data analysis. Decision about share structure of investment distribution contributes to the implementation of important knowledge-intensive projects for the development of major industry companies. Integral rating of companies plays a leading role in making investment decisions. Research hypothesis of the minimax approach application and hierarchical data analysis will allow developing an intelligent computerized system that will perform real-time calculations and make recommendations on share distribution of investments of the largest Russian companies using a hierarchical rating procedure and minimax approach.Materials and methods. Currently, methodological tools for rating of investment attractiveness of the largest Russian companies are at initial stage of development, although the relevance of such studies in world practice has reached the highest level, thanks to leading rating agencies that have their own methodology and justified methodology for rating companies. Until middle of 2017 when developing investment strategies for the development of Russian industry giants, the opinions of the international rating agencies of “big three”: Standard & Poor's, Fitch Ratings, Moody's and experts of Forbes magazine were taken into account. However, due to reduction in the activity of foreign expertise in Russia, it became necessary to develop and implement its own rating methodology for assessing the investment attractiveness of companies. Current rating approach (accredited Agency Expert RA), as well as young and promising rating agencies need new and mathematically sound approach to compile rating, which optimizes investment process for the most important high-tech projects by priority indicators and industry sign companies. Author's methodology is based at analysis of statistical indicators of companies in the most important sectors of economy. The important feature of the developed method is using author's mathematical apparatus, including a hierarchical analysis of the ranked indicators of financial-economic activity of companies according to their priority and application of minimax approach to obtain rating of companies based at industry characteristics.Results. Method developed in the paper is based at logical rules of grouping companies, allows obtaining rating of companies and rating of leading Russian industries, which companies were considered in data analysis. By using obtained ratings and minimax approach, the rating of investment attractiveness of the companies is made (taking into account industry affiliation). Proposed method has scientific novelty, due to hierarchical procedure of ranking indicators and minimax problem. More that author’s method allows obtaining rating assessment of investment attractiveness of companies, taking into account industry characteristic. In this paper, computational experiments were performed, which used indicators on volume of output and profit of the largest (by volume of output) companies in Russia. Computational experiments have shown the leading role of oil and gas and banking companies in Russian economy.Conclusion. The practical use of the developed method of integral ranking of companies allows optimizing process of allocation the investment resources and contributes to expansion of production of high-tech products produced by leading companies of the most important sectors of Russian economy. Proposed method is advisable for using in investment strategies for the development of high-tech projects. Efficiency of the developed rating of Russian companies has been demonstrated at practice of assessing the largest Russian companies; results are complemented, expanded and enriched by existing research of specialists and leading rating agencies. The author recommends using presented tools for optimization the investment resources for development of the most important industry companies in Russia.
Two-Stage Topic Extraction Model for Bibliometric Data Analysis Based on Word Embeddings and Clustering
