Relevance. The coronavirus pandemic has both negative and less obvious positive effects on the world economy. In order to better understand these processes, it is necessary to examine the sectors that have shown growth against the general decline in production. Such sectors include the Internet and telecommunication services. Research objective. The purpose of this study is to model the impact of the pandemic and foreign companies on the value of shares of Russian tech companies. Data and methods. The study involves daily share price data of such American corporations as Google, PayPal, Netflix, Adobe, and the Russian company Yandex. Moreover, we used the dummy variable Covid-19. The econometric analysis was conducted by using vector autoregression (VAR). The direction of cause-and-effect relationships was investigated with the help of the Granger test, and the effect of single shocks, through impulse response functions (IRF). Results. A stable VAR model was built. The IRF graphs were used to describe the impact of the pandemic and the value of US. companies on Russian companies. Conclusions. The study shows that the 2020 pandemic has proven to be a positive shock for companies in the ICT sector, contributing to increased demand for their services and market capitalization. The pandemic has affected both Russian and foreign companies. The study has also found the influence of the American stock market on share prices in Russia. Russian companies reacted to changes in the American stock market with a lag of up to 10 days.

Given the importance of stock market synchronization for international portfolio diversification, we estimate the degrees of co-movements among US, Chinese and Russian markets. By applying the TVP-VAR approach, we measure total and bivariate synchronization indices utilizing daily data from 1998 to 2021. Our analysis demonstrates that the total connectedness index (TCI) is 26.15% among the three markets. We find that the US market is the highest volatility contributor, whereas the Russian market is the highest receiver. Since stock market synchronization is exposed to geopolitical risk, at the second stage, we apply the Quantile-on-Quantile framework to measure the response of total and bilateral connectedness indices to geopolitical risk (GPR). The findings affirm our proposition that GPR impedes TCI when it has a bullish state and a higher quantile of GPR. The response of bilateral connectedness is negative towards GPR concerning US–China and US–Russian pairs. However, the degree of connectedness between Russian and Chinese stock markets is less responsive to GPR.

Oil and gas dependence and the volatility of their prices is currently a serious challenge for the Russian economy. Coincidently, export revenues from oil and gas products are the main source of the federal budget. Export diversification can contribute to risk reduction for the Russian economy by increasing the share of products from other industries in the export structure. In this regard, the present study examines the determinants of export diversification in Russian industrial regions using econometric modelling methods. To this end, the Herfindahl and Theil indices for 97 export groups were calculated. It is hypothesised that the development of small and medium-sized enterprises, as well as the sanctions imposed by Western states against Russia are the main factors of export diversification in industrial regions. Simultaneously, natural resource extraction is assumed to significantly increase the concentration of exports in the regions. To test this hypothesis, panel data of 50 Russian industrial regions for the period 2001-2019 were analysed. The quantile regression approach was applied to solve the heteroscedasticity problem. Three groups of regions were distinguished according to their level of diversification: regions with a high level of export diversification (Q10-Q30), with an average level of diversification (Q40-Q60), with a low level of export diversification (Q70-Q90). The research findings show that the development of small and medium-sized enterprises contributes to export diversification in Russian industrial regions. While the sanctions did not have a significant impact on export diversification, regional potential and natural resource extraction increase the concentration of exports. The obtained study results complement the existing literature on export diversification in Russia, and contribute to the development of policy implications.

The dependence of Russian exports on hydrocarbon products negatively affects the country's economy due to the high volatility of oil and gas prices. The purpose of the study is to assess the degree of export diversification of Russia's regions and to determine the main determinants of export diversification. The hypothesis of the study is that in order to increase the number of exporters and the volume of international trade, the regions of Russia need to balance the structure of exports and actively develop small and medium-sized businesses. To identify regional determinants of export diversification in Russia, we use panel data for 83 entities of the Russian Federation for the period from 2001 to 2019. Within the analysis, we calculate the indicator of export diversification at the regional level using the Herfindahl and Theil indices and implement the quantile regression approach, which allows us to solve the heteroscedasticity problem and identify regions with high, medium, and low levels of export diversification. The study considers such regional characteristics as small and medium-sized businesses, the index of business potential and risk, the region's openness to international trade, the natural resources endowment, and also take into account the impact of sanctions imposed against Russia. The results of the study show that regions with the lowest level of export diversification have more opportunities to reduce the export concentration. The most significant factor contributing to export diversification is the number of small and medium enterprises in the region. At the same time, the analysis revealed that the vast majority of regional characteristics increase export concentration, for example, the extraction of natural resources, the import of technologies, the indicator of openness, risk and potential of companies. The results obtained complement the existing literature on export diversification in Russia and can be used to develop recommendations for improving government policy in terms of the reduction of oil and gas share in the overall exports structure.

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