Analysis of Factors Influencing Share Price of Russian Oil and Gas Companies within the Framework of Volatility Models.

This study presents theoretical aspects of volatility modeling in financial data. A review of the theoretical material in relation to the use of common GARCH-models for forecasting financial indicators is conducted. Recent studies show that specialists hold quite various views about the quality of volatility models. While the debate over this topic seems to gain popularity, several empirical tasks are left unaccomplished and this problem is currently an active area of research. The present research belongs to newly evolving investigations and it aims to elaborate a coherent model for precise forecasting volatility in finance. Using the data of Gazprom share prices from 2013:Q1 to 2017:Q2, advanced GARCH and Heston models were implemented and then compared. Based on GARCH and Heston models of stochastic volatility, the new approach involves factors, considered to be external for oil and gas sector: crude oil futures’ return, Dow Jones index, MICEX index etc. In addition, the main political and economic events and their relationship with the volatility level fluctuations are considered. The evidence could be better summed up in the idea of a positive effect of adding external factors like crude oil future prices as external parameters into the existing specification of models. Furthermore, the results obtained in the research might have some practical implications advancing volatility models and presenting more precise ones. In some instances, the approach employed seems to be very promising, as it could raise our awareness of the nature of real financial markets and investing strategies applied to them. In future it seems worthwhile to employ the technique more widely implementing the merits of the study for other sectors of national and world economies.