Subject The article addresses oil price forecasting, being very important for all financial market actors as oil is an essential asset and any changes in oil prices have a direct influence on the entire financial markets industry. Objectives The purposes of the study are to describe the logic of developing the analytical and forecasting methods, which are used on financial markets; to devise a committee machine methodology to analyze data from financial markets; to build a real committee machine model for oil price forecasting. Methods To forecast oil prices, we apply the committee machine method with majority logic. Main sources of information on market prices and oil reserves include websites of FINAM company, Investing.com, and Bloomberg analytical platform. Results Constructed committee machines with majority logic of 3 and 5 members are the results of the research. To build the models, we analyzed intraday quotes on the day of the EIA report publishing and changes in oil supplies from 11 February 2009 to 9 August 2017. Based on the analysis and comparison of the models' quality, we built a model to forecast heightened volatility of oil prices after the EIA report release. Conclusions The findings show that the committee machine method can be used as a tool to forecast oil price changes.
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