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dc.contributor.authorMochón, Mari-Carmen
dc.date2016
dc.date.accessioned2020-06-24T11:35:11Z
dc.date.available2020-06-24T11:35:11Z
dc.identifier.issn1989-1660
dc.identifier.urihttps://reunir.unir.net/handle/123456789/10211
dc.description.abstractAfter the financial crisis initiated in 2008, international market supervisors of the G20 agreed to reinforce their systemic risk supervisory duties. For this purpose, several regulatory reporting obligations were imposed to the market participants. As a consequence, millions of trade details are now available to National Competent Authorities on a daily basis. Traditional monitoring tools may not be capable of analyzing such volumes of data and extracting the relevant information, in order to identify the potential risks hidden behind the market. Big Data solutions currently applied to the Social Network Analysis (SNA), can be successfully applied the systemic risk supervision. This case of study proposes how relations established between the financial market participants could be analyzed, in order to identify risk of propagation and market behavior, without the necessity of expensive and demanding technical architectures.es_ES
dc.language.isoenges_ES
dc.publisherInternational Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI)es_ES
dc.relation.ispartofseries;vol. 3, nº 6
dc.relation.urihttps://www.ijimai.org/journal/bibcite/reference/2535es_ES
dc.rightsopenAccesses_ES
dc.subjectnetworkes_ES
dc.subjectsociales_ES
dc.subjectanalysises_ES
dc.subjectbig dataes_ES
dc.subjectriskes_ES
dc.subjectOTC Derivativeses_ES
dc.subjectIJIMAIes_ES
dc.titleSocial Network Analysis and Big Data tools applied to the Systemic Risk supervisiones_ES
dc.typearticlees_ES
reunir.tag~IJIMAIes_ES
dc.identifier.doihttp://doi.org/10.9781/ijimai.2015.332


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