Abstract
This paper provides a new methodology for company assessment besides other traditional assessment measures such as share price or forecasts of the analysts. It is suggested to assess the market reaction on change in share price via using graphical approaches. Investors buy shares with the expectation that its price will rise in the future. But sometimes expectations don’t coincide with reality and then shares are sold. This work has been taken into account in the asymmetry between expectations of investors and results. In order to identify the position of a company in 2D space, the paper uses classification algorithm of random forests with data on change in share price during the period of the year in the inputs, and the forecasts of analysts, i.e., whether a price will increase or decrease, for the same year in the outputs. Thus, two clusters of companies are seeking to represent: one of the companies whose changes in share price coincide with investors’ expectations, and another one – on the contrary. This method can be useful to investors, for whom it is important to identify the market reaction about companies from the whole industry or its branches and analyze its trend.
Highlights
A number of research have shown that the trend of share markets is not entirely random and can be forecasted, various random factors, for ex-I
The results show that density integration parameter of skew t distribution has the greatest influence in the model, developed, and seeking to assess priority areas and describe the expectations of investors in more details
As area parameter h is the key indicator of market reaction research, Figure 1 shows the results of examination of this parameter
Summary
A number of research (see Angelovska 2016; Coussement, Van den Poel 2009; Liang et al 2015; Lin et al 2014; Price et al 2011) have shown that the trend of share markets is not entirely random and can be forecasted, various random factors, for ex-I. Recommendations of analysts, engaged in assessment of financial market elements, are treated controversially. On one hand, they are commonly based on technical analysis (share price is forecasted by attempting to determine the trends and statistical analogies, following the historical price volatility). Barber et al (2006) researched criteria under which analysts’ recommendations should be classified to buy, hold shares expecting future rise or to sell shares at a profit now. Barber et al (2006) researched criteria under which analysts’ recommendations should be classified to buy, hold shares expecting future rise or to sell shares at a profit They found out that there is a need to discipline the brokers, who commonly tend to recommend buying shares. The forecasts of analysts can be used only as additional information, and not as final proposal to buy or sell the shares of specific business
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