Evaluation of Investment Attractiveness Factors of Enterprises

This paper considers the main approaches to the definition of the term "investment attractiveness of an enterprise", the existing classifications of types of investors, the dependence of their behavior on investment goals, risk preferences and the theory of the company's life cycle. Then, the main approaches and methods for assessing investment attractiveness, as well as empirical work of specialists were investigated, including expert methods, qualimetric, multilevel models using point, rating, integral methods, correlation and regression analysis tools, along with methods for assessing the activities of enterprises, implemented by analytical agencies. The information learned was used to build a regression model. The scientific novelty of the research is determined by the fact that when building a model, there is a distancing from industry methods, the use of which is not always feasible and requires high time costs for investors. In addition, in the developed model, the weights are determined not by an expert method, which has a high risk of subjectivity, but with the help of econometric tools. Non-traditional indicators were taken as the explanatory variables characterizing the investment attractiveness of the company - total material capital and tangible assets, since investments are usually directed to business development and the growth of fixed assets, which means that these indicators reflect whether the company is attractive among investors or not. The model has shown the signs corresponding to the expectations for all regressors. The explanatory variables were market capitalization of enterprises, net profit, Tobin's q-ratio, and the aggregate environmental, social and corporate governance rating (ESG). The model reflects most of the key indicators a value investor focuses on, with the exception of dividend yield. However, the possibility that there are other factors in the Russian investment market should not be excluded. The determination coefficient was more than 75%, and the model showed the best results for energy and telecommunications companies. Based on this, a number of recommendations were developed for investors to make investment decisions and for financial managers to identify the main directions of business development.