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dc.creatorRajković, Milan
dc.date.accessioned2018-03-03T13:51:32Z
dc.date.available2018-03-03T13:51:32Z
dc.date.issued2000
dc.identifier.issn0378-4371 (print)
dc.identifier.urihttp://vinar.vin.bg.ac.rs/handle/123456789/6297
dc.description.abstractA method for extracting information carrying eigenvalues of the correlation matrix is presented based on the topological transformation of the manifold defined by the data matrix itself. The transformation, performed with the use of the minimum spanning tree and the barycentric transformation, linearizes the topological manifold and the singular value decomposition is performed on the fnal data matrix corresponding to the linearized hypersurface. It is shown that the results of this procedure are superior to the results of the random matrix theory as applied to the financial data. The method may be used independently or in conjunction with the random matrix theory. Other possible uses of the method are mentioned. (C) 2000 Elsevier Science B.V. All rights reserved.en
dc.rightsrestrictedAccessen
dc.sourcePhysica A: Statistical Mechanics and Its Applicationsen
dc.subjectfinancial markets dataen
dc.subjectrandom matricesen
dc.subjectminimum spanning treeen
dc.subjectbarycentric transformationen
dc.titleExtracting meaningful information from financial dataen
dc.typearticleen
dcterms.abstractРајковић Милан;
dc.citation.volume287
dc.citation.issue3-4
dc.citation.spage383
dc.citation.epage395
dc.identifier.wos000165587600005
dc.identifier.doi10.1016/S0378-4371(00)00377-0
dc.citation.rankM22
dc.description.other229th WE Heraeus Seminar on Economics Dynamics from the Physics Point of View, Apr 27-30, 2000, Bad Honnef, Germanyen
dc.identifier.scopus2-s2.0-0034501778


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