Social Network Analysis and Big Data tools applied to the Systemic Risk supervision
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...
| Título de la revista: | International Journal of Interactive Multimedia and Artificial Intelligence |
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| Autor: | Mari-Carmen Mochón |
| Palabras clave: | |
| Idioma: | No especificado |
| Enlace del documento: | http://www.ijimai.org/journal/sites/default/files/files/2016/02/ijimai20163_6_5_pdf_14449.pdf https://www.ijimai.org/journal/node/935 |
| Tipo de recurso: | Documento de revista |
| Fuente: | International Journal of Interactive Multimedia and Artificial Intelligence; Vol 3, No 6 Especial (Año 2016). |
| Entidad editora: | Universidad Internacional de La Rioja |
| Derechos de uso: | Reconocimiento (by) |
| Materias: | Ciencias Físicas e Ingeniería --> Informática, Inteligencia Artificial |
| Resumen: | 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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