Social Network Analysis and Big Data tools applied to the Systemic Risk supervision

After 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 no...

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Main Author: Mari-Carmen Mochón
Format: Article
Language:English
Published: Universidad Internacional de La Rioja (UNIR) 2016-03-01
Series:International Journal of Interactive Multimedia and Artificial Intelligence
Subjects:
Online Access:http://www.ijimai.org/journal/node/935
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author Mari-Carmen Mochón
author_facet Mari-Carmen Mochón
author_sort Mari-Carmen Mochón
collection DOAJ
description After 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.
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spelling doaj.art-8ff0866d0c7a479eaac1f98f8dd48c8f2022-12-22T03:07:59ZengUniversidad Internacional de La Rioja (UNIR)International Journal of Interactive Multimedia and Artificial Intelligence1989-16601989-16602016-03-0136343710.9781/ijimai.2016.365ijimai.2016.365Social Network Analysis and Big Data tools applied to the Systemic Risk supervisionMari-Carmen MochónAfter 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.http://www.ijimai.org/journal/node/935AnalysisBig DataNetworkOTC DerivativesRiskSocial
spellingShingle Mari-Carmen Mochón
Social Network Analysis and Big Data tools applied to the Systemic Risk supervision
International Journal of Interactive Multimedia and Artificial Intelligence
Analysis
Big Data
Network
OTC Derivatives
Risk
Social
title Social Network Analysis and Big Data tools applied to the Systemic Risk supervision
title_full Social Network Analysis and Big Data tools applied to the Systemic Risk supervision
title_fullStr Social Network Analysis and Big Data tools applied to the Systemic Risk supervision
title_full_unstemmed Social Network Analysis and Big Data tools applied to the Systemic Risk supervision
title_short Social Network Analysis and Big Data tools applied to the Systemic Risk supervision
title_sort social network analysis and big data tools applied to the systemic risk supervision
topic Analysis
Big Data
Network
OTC Derivatives
Risk
Social
url http://www.ijimai.org/journal/node/935
work_keys_str_mv AT maricarmenmochon socialnetworkanalysisandbigdatatoolsappliedtothesystemicrisksupervision