Vovk V. Modeling the activities of stock market participants in conditions of uncertainty.

The dissertation is devoted to the substantiation of theoretical positions and the development of practical recommendations and a set of economic and mathematical models for making effective decisions by the participants of a stock market, which requires the most accurate forecasting of the yield of securities, the assessment of their risks and taking into account the qualitative factors that affect the processes on the stock market most of all.Financial time series of quotations of shares of Ukrainian companies were found to have conditional heteroskedasticity. This allows to effectively predict stock volatility using the GARCH-models.The research was conducted on the data of stock price quotes from 1/4/2009 to 31/08/2017 of five Ukrainian companies that enjoyed the greatest demand in the Ukrainian stock market in 2016 as to the volume of exchange contracts executed: PJSC "State Power Generating Company "Tsentrenergo", PJSC "Raiffeisen Bank Aval", PJSC "Motor Sich", PJSC "Ukrnafta" and PJSC "Ukrtelecom".A set of models for forecasting the volatility of the yield of each company's shares was constructed and investigated, namely GARCH(1,1), GARCH(2,1), GJR-GARCH(1,1), GJR-GARCH(2,1), EGARCH(1,1), EGARCH(2,1). Based on the best for each company, predicted values of yield volatility on stock were calculated for a 10-day period.