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dc.contributor.authorBystray, G. P.en
dc.contributor.authorLykov, I. A.en
dc.contributor.authorNikulina, N. L.en
dc.date.accessioned2017-09-04T14:46:04Z-
dc.date.available2017-09-04T14:46:04Z-
dc.date.issued2012-
dc.identifier.citationBystray G. P. Risks assessment and forecasting long time rows of economic indicators / G. P. Bystray, I. A. Lykov, N. L. Nikulina // Economy of Region. — 2012. — № 3. — P. 240-249.en
dc.identifier.issn2411-1406online
dc.identifier.issn2072-6414print
dc.identifier.other2good_DOI
dc.identifier.otherhttp://www.scopus.com/inward/record.url?partnerID=8YFLogxK&scp=84979920599m
dc.identifier.other50b5a30d-092d-41b8-9b71-e180f905e3c8pure_uuid
dc.identifier.urihttp://elar.urfu.ru/handle/10995/51525-
dc.description.abstractThis paper reviews main approaches to risk assessment. The authors accented attention on the nonlinear approach to the theory of risks. It is proposed to define economic risk as the probability of threats that could have material adverse effect on the economic system under study and to change its current state. The method and the program product designed by the authors integrate a wide range of indicators of economic and financial activities at the regional level in the program-technical complex. This paper describes a new method for assessing synergistic and prediction of risk over long time rows of economic indicators at the regional level, including methods of nonlinear and chaotic dynamics, enabling a pseudo-phase and phase portraits, to determine the volatility, to calculate fractal characteristics and predict the behavior of socio-economic indicators with modernized method of Hurst, to model based on recovery probability distribution function of non-equilibrium potential function, to determine the local and global stability of the regional economy and to identify risks as the probability of the threats of an economic nature.en
dc.format.mimetypeapplication/pdfen
dc.language.isoenen
dc.publisherInstitute of Economics, Ural Branch of the Russian Academy of Sciencesen
dc.publisherИнститут экономики Уральского отделения Российской академии наукru
dc.relation.ispartofЭкономика региона. 2012. Выпуск 3ru
dc.rightsinfo:eu-repo/semantics/openAccessen
dc.sourceEcon. Reg.2
dc.sourceEconomy of Regionen
dc.subjectECONOMIC RISKen
dc.subjectFORECASTING OF ECONOMIC INDICATORSen
dc.subjectMODERNIZED METHOD OF HURSTen
dc.subjectSYNERGETIC METHODen
dc.titleRisks assessment and forecasting long time rows of economic indicatorsen
dc.typeArticleen
dc.typeinfo:eu-repo/semantics/publishedVersionen
dc.typeinfo:eu-repo/semantics/articleen
dc.identifier.doi10.17059/2012-3-24-
dc.identifier.scopus84979920599-
local.affiliationDepartment for General and Molecular Physics, Federal State Autonomous Educational Institution of Higher Professional Education, Ural Federal University named after the first President of Russia B.N. Yeltsin, pr. Lenina, 51, Yekaterinburg, 620083, Russian Federationen
local.affiliationCenter for Economic Security, Institute of Economics, Ural Branch of Russian Academy of Sciences, Moskovskaya St., 29, Ekaterinburg, 620014, Russian Federationen
local.contributor.employeeБыстрай Геннадий Павловичru
local.contributor.employeeЛыков Иван Александровичru
local.description.firstpage240-
local.description.lastpage249-
local.issue3-
dc.identifier.wos000422166800024-
local.contributor.departmentИнститут естественных наук и математикиru
local.identifier.pure1126963-
local.identifier.eid2-s2.0-84979920599-
local.identifier.wosWOS:000422166800024-
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