Trade and Economic Relations between the EAEU Countries during the COVID-2019 Pandemic

The relevance of the selected topic of the article is due to the fact that the coronavirus pandemic and the imposed restrictive measures associated with it, which have swept the entire planet, affects all national economies and, accordingly, the integration groups that include these states. The EAEU is no exception. The Eurasian Economic Union was created with the aim of strengthening the national economies and the potential of the member states in the global economy, in which four freedoms operate: the movement of goods, services, finance and labor. Its appearance occurred during the period of global economic instability and geopolitical changes in Eurasia, which affected the situation within the EAEU.The purpose of this article is to study trade and economic relations between the EAEU countries during the COVID-2019 pandemic. Achievement of the goal set in the work was performed based on the application of general scientific methods within the framework of comparative, logical and statistical analysis.The results of the research performed in the article are based on the analysis of statistical information on foreign trade within the integration group, as well as on data on the prevailing trends in foreign economic relations between countries in non-trade spheres.It was concluded that in the context of the COVID-2019 pandemic, the growth rates slowed down, and the intensity of the countries’ foreign economic relations decreased significantly, which aggravates the negative trends in the decrease in the integration ties strength and the increase in contradictions between countries even before the start of the pandemic. The prospects for the recovery and further development of the EAEU member states’ economies are largely associated with the influence of external factors. The macroeconomic forecast for the states of the region critically depends on the nature of the COVID-19 pandemic course. An important factor is that each of the states in the region is in a unique epidemiological situation, which also makes it difficult to assess both the quarantine measures duration and the economic consequences depth of the imposed restrictions.Nevertheless, it is obvious that the EAEU countries intend to continue working towards a joint response to the threat of coronavirus infection. It should be borne in mind that the nature of such interaction will have certain limits associated with the current level of integration.

SPATIAL ANALYSIS OF FINANCIAL INDICATORS DETERMINING THE LEVEL OF ENSURING THE ECONOMIC SECURITY OF RUSSIA

The key mechanism for assessing the risks and threats of the national economy at a qualitative level is the system of economic security indicators. The most important of its sections is the system of financial indicators, which includes groups of indicators that reflect the activities of the state and economic entities in various spheres of the economy. The object of the research is the economic security of Russia. The subject of the research is the system of financial indicators of economic security of Russia. The practical significance of the work is as follows: – the approaches proposed by the authors make it possible to assess the reality of the parameters of a macroeconomic forecast; – the system of financial indicators of economic security makes it possible to monitor the tax, budget, currency and other systems in aggregate, and to highlight those that are at risk; – the system of financial indicators of economic security contributes to the formation of individual of measures of a proactive nature to prevent and minimize crisis processes aimed at eliminating imbalances in the development and effective functioning of the national economic system. The results of the research can be used in the process of monitoring the economic activity of business entities, in the educational process of financial and economic disciplines, by government bodies in the formation of economic policy.

An Improved Long Short-Term Memory Neural Network for Macroeconomic Forecast

The statistics and cyclical swings of macroeconomics are necessary for exploring the internal laws and features of the market economy. To realize intelligent and efficient macroeconomic forecast, this paper puts forward a macroeconomic forecast model based on improved long short-term memory (LSTM) neural network. Firstly, a scientific evaluation index system (EIS) was constructed for macroeconomy. The correlation between indices was measured by Spearman correlation coefficient, and the index data were preprocessed by interpolating the missing items and converting low-frequency series into high-frequency series. Next, the corresponding mixed frequency dataset was constructed, followed by the derivation of the state space equation. Then, the LSTM neutral network was optimized by the Kalman filter or macroeconomic forecast. The effectiveness of the proposed forecast method was verified through experiments. The research results lay a theoretical basis for the application of LSTM in financial forecasts.