Forecasting Economic Indicators by Applied Technologies of Data Processing

Today economic forecasts are necessary to identify possible goals of business and society development in general. Available models of information processes of economic system functioning differ by methods of mathematic tools usage. The degree of algorithm complexity with regard to their advantages a...

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Autores principales: R. R. Veynberg, A. S. Skotchenko, A. A. Grigorev, A. B. Yaroshyk
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Lenguaje:RU
Publicado: Plekhanov Russian University of Economics 2021
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Acceso en línea:https://doaj.org/article/0b14da85b1ae4b00813b9c613a7a1627
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spelling oai:doaj.org-article:0b14da85b1ae4b00813b9c613a7a16272021-11-15T05:20:50ZForecasting Economic Indicators by Applied Technologies of Data Processing2413-28292587-925110.21686/2413-2829-2021-1-124-132https://doaj.org/article/0b14da85b1ae4b00813b9c613a7a16272021-02-01T00:00:00Zhttps://vest.rea.ru/jour/article/view/1012https://doaj.org/toc/2413-2829https://doaj.org/toc/2587-9251Today economic forecasts are necessary to identify possible goals of business and society development in general. Available models of information processes of economic system functioning differ by methods of mathematic tools usage. The degree of algorithm complexity with regard to their advantages and drawbacks cannot give an opportunity to choose one method without certain changes. For example, when the trend line is plotted usually only one economic indicator is used, however practice shows that in forecasting it is necessary to take into account several interdependent factors. Standard applied software products are rather expensive and to resolve the set tasks some additional instrumental means, tuning and users’ training are needed. The article proposes a method of plotting the trend line for several economic indicators simultaneously by using tools of widely spread software. The results of using the method for finding the common trend line for the rate of Euro to Russian ruble and the cost of oil barrel (3D) were shown. Apart from that the mathematic instrument for n-dimension case, which later could allow us to assess the possibility of changing several economic indicators at once and analyze their mutual impact.R. R. VeynbergA. S. SkotchenkoA. A. GrigorevA. B. YaroshykPlekhanov Russian University of Economicsarticletrend lineeconomic forecastingeconomic and mathematic modelsEconomics as a scienceHB71-74RUВестник Российского экономического университета имени Г. В. Плеханова, Vol 18, Iss 1, Pp 124-132 (2021)
institution DOAJ
collection DOAJ
language RU
topic trend line
economic forecasting
economic and mathematic models
Economics as a science
HB71-74
spellingShingle trend line
economic forecasting
economic and mathematic models
Economics as a science
HB71-74
R. R. Veynberg
A. S. Skotchenko
A. A. Grigorev
A. B. Yaroshyk
Forecasting Economic Indicators by Applied Technologies of Data Processing
description Today economic forecasts are necessary to identify possible goals of business and society development in general. Available models of information processes of economic system functioning differ by methods of mathematic tools usage. The degree of algorithm complexity with regard to their advantages and drawbacks cannot give an opportunity to choose one method without certain changes. For example, when the trend line is plotted usually only one economic indicator is used, however practice shows that in forecasting it is necessary to take into account several interdependent factors. Standard applied software products are rather expensive and to resolve the set tasks some additional instrumental means, tuning and users’ training are needed. The article proposes a method of plotting the trend line for several economic indicators simultaneously by using tools of widely spread software. The results of using the method for finding the common trend line for the rate of Euro to Russian ruble and the cost of oil barrel (3D) were shown. Apart from that the mathematic instrument for n-dimension case, which later could allow us to assess the possibility of changing several economic indicators at once and analyze their mutual impact.
format article
author R. R. Veynberg
A. S. Skotchenko
A. A. Grigorev
A. B. Yaroshyk
author_facet R. R. Veynberg
A. S. Skotchenko
A. A. Grigorev
A. B. Yaroshyk
author_sort R. R. Veynberg
title Forecasting Economic Indicators by Applied Technologies of Data Processing
title_short Forecasting Economic Indicators by Applied Technologies of Data Processing
title_full Forecasting Economic Indicators by Applied Technologies of Data Processing
title_fullStr Forecasting Economic Indicators by Applied Technologies of Data Processing
title_full_unstemmed Forecasting Economic Indicators by Applied Technologies of Data Processing
title_sort forecasting economic indicators by applied technologies of data processing
publisher Plekhanov Russian University of Economics
publishDate 2021
url https://doaj.org/article/0b14da85b1ae4b00813b9c613a7a1627
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AT asskotchenko forecastingeconomicindicatorsbyappliedtechnologiesofdataprocessing
AT aagrigorev forecastingeconomicindicatorsbyappliedtechnologiesofdataprocessing
AT abyaroshyk forecastingeconomicindicatorsbyappliedtechnologiesofdataprocessing
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