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dc.contributor.authorDremova, U. V.en
dc.contributor.authorДремова, У. В.ru
dc.date.accessioned2020-10-19T10:45:15Z-
dc.date.available2020-10-19T10:45:15Z-
dc.date.issued2015-
dc.identifier.citationДремова У. В. Совершенствование методики оценки банковских рисков долгосрочного кредитования инвестиций (на примере банков г. Севастополь) / У. В. Дремова. – DOI 10.17059/2015-1-20. – Текст : электронный // Экономика региона. — 2015. — Том 1. — С. 234-244.ru
dc.identifier.issn2072-6414print
dc.identifier.otherhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84979807257&doi=10.17059%2f2015-1-20&partnerID=40&md5=2d0e8ddc27b571d266ef7fc45beb2934m
dc.identifier.otherWOS:000422213100020wos
dc.identifier.urihttp://elar.urfu.ru/handle/10995/92052-
dc.description.abstractThe external destabilizing factor - financial crisis - has significantly influenced on the level increase of riskiness of the banking credit operations. Taking into account that the increased level of risk follows long-term credits, these operations has been influenced the most, that can be as one of the constraining conditions for the provision of bank long-term credit resources. It, in turn, causes the need to develop the risk assessment technique of long-term credits in regulation of banks' long-term credit operations. As the risk assessment of credit operations in banking practice is generally limited to the calculation of credit risk, it is efficient to consider the scientifically reasonable approach to a risks assessment of long-term crediting including influence of private risks for the purpose of carrying out the generalized assessment of riskiness both separate types of long-term credits, and a long-term credit portfolio in general. The offered method is based on the calculation of aggregate risk coefficient of the long-term credits, calculated by means of mathematical method of principal component. In the work, it is offered to perform an assessment of private risks by means of statistics: the expectation value, mean square deviation, and the coefficient of a variation. The use of the principal components' method at the risk assessment of longterm crediting meets such requirements as a lack of value judgment, accounting of specific features of private risks of long-term credits, mathematical validity. It gives the chance to apply the offered risk assessment method of long-term credits in banking. The conclusion is made that the application of an aggregative risk indicator of a long-term crediting will allow banks to trace more accurately the level of riskiness of a long-term credit portfolio and separate types of long-term credits that will strengthen the bank information and analytical base on risk regulation in the field and will expand tools of bank management. © 2015 The Journal of Economic Theory.en
dc.description.abstractРассмотрены основные риски, сопровождающие долгосрочное кредитование. При оценке риска долгосрочного кредитования предложено применение агрегированного коэффициента риска, рассчитанного с помощью математического метода главных компонент.ru
dc.format.mimetypeapplication/pdfen
dc.language.isoruen
dc.publisherInstitute of Economics, Ural Branch of the Russian Academy of Sciencesen
dc.publisherИнститут экономики Уральского отделения РАНru
dc.relation.ispartofЭкономика региона. 2015. Выпуск 1ru
dc.rightsinfo:eu-repo/semantics/openAccessen
dc.subjectLONG-TERM CREDITSen
dc.subjectMETHOD OF PRINCIPAL COMPONENTen
dc.subjectRISK ASSESSMENT OF A LONG-TERM CREDITINGen
dc.titleСовершенствование методики оценки банковских рисков долгосрочного кредитования инвестиций (на примере банков г. Севастополь)ru
dc.title.alternativeDevelopment of the technique of assessment of banking risks of long-term crediting of investments (on the example of Banks of Sevastopol)en
dc.typeArticleen
dc.typeinfo:eu-repo/semantics/articleen
dc.typeinfo:eu-repo/semantics/publishedVersionen
dc.identifier.doi10.17059/2015-1-20-
dc.identifier.scopus84979807257-
local.description.firstpage234-
local.description.lastpage244-
local.volume1-
dc.identifier.wos000422213100020-
local.identifier.eid2-s2.0-84979807257-
Располагается в коллекциях:Economy of Regions

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