Abstract

In this paper we proposed two new strategies for initialization and training of Radial Basis Function (RBF) Neural Network. The first approach takes into consideration the "error" between the input vector p of the network and the x-axis, which are the centers of radial functions. The second approach takes into account the "error" between the input vector p and the network output. In order to check the performances of these strategies, we used Brazilian financial market data for the RBF networks training, specifically the adjusted prices of the 10 greater weighted shares in the Bovespa index at the time of data collection - from April 8th , 2009 to October 31th , 2014. The first approach presented a 52% of improvement in the mean squared error (MSE) compared to the standard RBF network, while the improvement for the second approach was 38%. The strategies proved to be consistent for the time series tested, in addition to having a low computational cost. It is proposed that these strategies be improved by testing them with the Levenberg-Marquardt algorithm.

Abstract

The topic of the study is relevant due to the fact that abrupt changes in the economy and in the financial system, particularly those caused by the coronavirus pandemic, have changed all existing development forecasts. At the same time, a whole range of new risks for the financial system appeared. In this regard, the development of a forecast for the development of the financial sector in various scenarios, taking into account risks and opportunities, seems to be the most important task for the Russian economy. The purpose of the study is to develop a medium-term forecast for the development of the financial sector in the Russian Federation. The subject of this research is the dynamics of the development of the financial system of the Russian Federation in the medium term. The research method or methodology is based on the study of key current and retrospective data on the state of the financial sector of the Russian Federation, highlighting the most important risks for the financial sector and building a medium-term forecast. As a result of the work carried out, the key components of the budgetary sphere, financial and credit markets have been analyzed, and the impact of the deterioration in the external environment has been assessed. Thus, the work presents the assessments of the prerequisites for the forecast and developed three possible scenarios for the development of the financial sector in Russia. The scientific novelty of the research lies in producing unique forecasts for the development of the financial sector in Russia. The recommendations obtained as a result of the study indicate the need to develop mechanisms for responding to certain risks for the financial system, taking into account the possible consequences of such an impact presented in the forecast. The project was carried out as part of research work by the Laboratory for Structural Research of the IAER at the Russian Presidential Academy of National Economy and Public Administration in 2021.

Abstract

The relevance of the topic is due to the fact that the sharp changes in the sectors of the economy generated by the coronavirus pandemic have changed all existing development forecasts. At the same time, a number of new risks have emerged. In this regard, the development of a forecast for the development of economic sectors, taking into account risks and opportunities, seems to be the most important task for the Russian economy. The purpose of the study is to develop a forecast for key parameters of the socio-economic development of Russia, assess the risks of the forecast and develop tools for responding to risk situations, develop a forecast for the development of the financial sector in the Russian Federation in the medium term The subject of the study is the dynamics of the economic development of the Russian Federation in the medium term. The method or methodology of the study is based on the study of key current and retrospective data on the state of the sectors of the economy of the Russian Federation, highlighting the most important risks and building a medium-term forecast. Main research methods: economic observation, economic modeling, construction of economic hypotheses, historical analysis of economic phenomena, formalization and mathematization method, logical interpretation method, axiomatization method, analogy method As a result of the work carried out, the key components of the public sector, financial and credit markets were analyzed, and an assessment was made of the impact of the worsening external environment. Thus, the paper presents estimates of the prerequisites for the forecast and develops three possible scenarios for the development of sectors of the Russian economy. The scientific novelty of the study lies in the development of unique forecasts for the development of sectors of the Russian economy. The recommendations received as a result of the study indicate the need to develop mechanisms for responding to certain risks, taking into account the possible consequences of such an impact, presented in the forecast.

Abstract

The relevance of the topic is due to the fact that the sharp changes in the sectors of the economy caused by the coronavirus pandemic have affected all existing forecasts of socioeconomic development. At the same time, a number of new support measures have appeared, both at the federal level and at the regional level. In this regard, it is necessary to analyze the current support measures aimed at the development of economic sectors, taking into account risks and opportunities, which seems to be the most important task for the Russian economy. The purpose of the study was to study the effectiveness of industry support measures in a crisis caused by non-economic reasons. The subject of the study is the effectiveness of support measures in the context of the coronavirus pandemic and their contribution to the restoration of the economic activity of the Russian Federation. The research method or methodology is to conduct a comprehensive economic analysis, a review of research literature (Russian and foreign), an analysis of foreign practices in providing business support, an assessment of financial stability and the effectiveness of support measures in a pandemic As a result of the work carried out, the effectiveness of support measures in the context of the coronavirus pandemic and their contribution to the restoration of economic activity, both in foreign countries and in federal and regional support measures for Russia, were analyzed. The scientific novelty of the study lies in the analysis and application of the experience of foreign countries in Russian realities and the study of the contribution to the Russian economy of the impact of existing support measures. The recommendations obtained as a result of the study indicate the need to calculate the effectiveness of support measures before its introduction. The project was carried out as part of research work by the Laboratory for Structural Research of the IPEI RANEPA under the President of Russian Federation in 2022.