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dc.contributorPerelló Palou, Josep
dc.contributor.authorDoria Arrieta, Omar Alonso
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Física Aplicada
dc.date.accessioned2011-07-15T11:46:54Z
dc.date.available2011-07-15T11:46:54Z
dc.date.issued2011-06-17
dc.identifier.urihttp://hdl.handle.net/2099.1/12665
dc.description.abstractIn the present we have analyzed the data from 480 companies of the S&P500 using the Random Matrix Theory and the Inverse Participation Ratio, we analyzed the eigenvalues and its respective eigenvectors in order to find structural behaviour in market. We take off the non-random part from the correlation matrix and use the new correlation matrix to calculate the risk for a given portfolio, showing good results as were expected. Also, we give a complex network perspective of the companies, building a network with the Spanning Tree Algorithm, in order to obtain some useful different measure of group behaviour.
dc.language.isoeng
dc.publisherUniversitat Politècnica de Catalunya
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Matemàtica financera
dc.subject.lcshMatrices
dc.subject.otherEconophysics
dc.subject.otherFinance
dc.subject.otherNetwork
dc.subject.otherRandom Matrix
dc.titleEmergent Group Properties in Financial Markets
dc.typeMaster thesis
dc.subject.lemacMatrius (Matemàtica)
dc.rights.accessOpen Access
dc.audience.educationlevelMàster
dc.audience.mediatorFacultat d'Informàtica de Barcelona
dc.audience.degreeMÀSTER UNIVERSITARI EN FÍSICA COMPUTACIONAL I APLICADA (Pla 2009)


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