Finance and Credit
 

Applying the committee machine method to forecast responses of oil prices to changes in oil reserves

Vol. 24, Iss. 5, MAY 2018

Received: 27 February 2018

Received in revised form: 13 March 2018

Accepted: 28 March 2018

Available online: 29 May 2018

Subject Heading: THEORY OF FINANCE

JEL Classification: C38, C53, C65, G17

Pages: 1079-1097

https://doi.org/10.24891/fc.24.5.1079

Akberdina V.V. Institute of Economics of Ural Branch of Russian Academy of Sciences, Yekaterinburg, Russian Federation
akb_vic@mail.ru

https://orcid.org/0000-0002-6463-4008

Chernavin N.P. Institute of Economics of Ural Branch of Russian Academy of Sciences, Yekaterinburg, Russian Federation
ch_k@mail.ru

https://orcid.org/0000-0002-2093-9715

Chernavin F.P. PAO Sberbank, Yekaterinburg, Russian Federation
chernavin_fedor@mail.ru

https://orcid.org/0000-0003-4105-231X

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.

Keywords: committee machine method, data mining, financial market, oil, EIA report

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