SHS Web of Conf.
Volume 92, 2021The 20th International Scientific Conference Globalization and its Socio-Economic Consequences 2020
|Number of page(s)||12|
|Section||Regions and Economic Resilience|
|Published online||13 January 2021|
Impact of Global Oil Shocks on the Russian Stock Market
1 Financial University under the Government of Russian Federation, Department of Corporate Finance and Corporate Management, Moscow, Russia
2 Financial University under the Government of Russian Federation, Department of the English Language and Professional Communication, Moscow, Russia
* Corresponding author: firstname.lastname@example.org
Research background: The study focuses on modeling assessment of oil shocks impact on the Russian stock market.
Purpose of the article: The purpose of the study is to determine the impact of oil prices abrupt changes on the Russian stock market, its quantitative and temporal specifications. The study consists of two interrelated sections. The first section includes the results of statistical processing of initial data, calculation of their key characteristics and preliminary analysis. The second section of the study is devoted to modeling the assessment of the impact of oil shocks on the behavior of the Russian market RTS stock index.
Methods: Based on an extensive sample of daily price values for Brent North sea oil and the Russian stock index RTS for the period from 1997 to May 2020, the study was conducted using models vector auto regression (VAR-model). Findings &Value added: The VAR model was developed and tested to assess the impact of oil shocks on the Russian stock market. Unlike the results of other studies, it is shown that the Brent oil price variance explains only about 10% of the RTS index yield variance in long-term time intervals. The low correlation of time series data and time limit of the impact of oil shocks on the Russian market have been revealed. According to the results of the study, the market recovery takes about 2 months, then the stock index returns to the ‘historical’ range of average ± standard deviation.
Key words: oil shocks / stock market / econometric methods / modeling / vector auto regression models (VAR)
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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