Assessment of companies prospect by their position in two-dimensional space

Abstract

This paper proposes methodology for companies’ assessment. There is suggesting assessing the company’s prospect, not only according to share price, forecasts of the analysts, but also on the basis of position of each company in two-dimensional space in respect of the other companies. Seeking to describe the share prices of a company during the year, the parameters of skew t distribution are calculated. Then they are used in the inputs of random forest algorithm. Proximity matrices are stored during classification, and they are displayed in two-dimensional space. Thus, two clusters are obtained: one of the companies with upgrade trend, another one – with downgrade trend. This method may be useful those investors who are important to choose the most promising companies of all industry without wasting a lot of time.DOI: 10.15181/csat.v3i2.1112