Network analysis of exchange data: interdependence drives crisis contagion | ||
| dc.conicet.organizacion | Universidad de Oviedo | |
| dc.conicet.organizacion | Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología | |
| dc.conicet.organizacion | Consejo Nacional de Investigaciones Científicas y Técnicas | |
| dc.conicet.paisOrganizacion | España | |
| dc.conicet.paisOrganizacion | Argentina | |
| dc.conicet.paisOrganizacion | Argentina | |
| dc.conicet.produccionid | 5201366 | |
| dc.contributor.author | Matesanz Gómez, David | |
| dc.contributor.author | Ortega, Guillermo José | |
| dc.date.accessioned | 2017-09-12T19:56:32Z | |
| dc.date.available | 2017-09-12T19:56:32Z | |
| dc.date.issued | 2013-05 | |
| dc.date.updated | 2017-09-12T16:29:23Z | |
| dc.description.abstract | In this paper, we examine linear and nonlinear co-movements that appear in the real exchange rates of a group of 28 developed and developing countries. The matrix of Pearson correlation and Phase Synchronous coefficients have been used in order to construct a topology and hierarchy of countries by using the Minimum Spanning Tree (MST). In addition, the MST cost and global correlation coefficients have been calculated to observe the co-movements’ dynamics throughout the time sample. By comparing Pearson and Phase Synchronous information, a new methodology is emphasized; one that can uncover meaningful information pertaining to the contagion economic issue and, more generally, the debate surrounding interdependence and/or contagion in financial time series. Our results suggest some evidence of contagion in the Asian currency crises; however, this contagion is driven by previous and stable interdependence. | es |
| dc.description.fil | Fil: Matesanz Gómez, David. Universidad de Oviedo; España | |
| dc.description.fil | Fil: Ortega, Guillermo José. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina | |
| dc.format | application/pdf | es |
| dc.identifier.citation | Matesanz Gómez, David; Ortega, Guillermo José; Network analysis of exchange data: interdependence drives crisis contagion; Springer; Quality & Quantity; 48; 4; 5-2013; 1835–1851 | es |
| dc.identifier.eissn | 1573-7845 | es |
| dc.identifier.institucional | CONICET | |
| dc.identifier.issn | 0033-5177 | es |
| dc.identifier.repo | CONICET Digital | |
| dc.identifier.uri | http://hdl.handle.net/11336/24088 | |
| dc.journal.ciudad | Dordrecht | es |
| dc.journal.number | 4 | es |
| dc.journal.pagination | 1835–1851 | es |
| dc.journal.pais | Países Bajos | es |
| dc.journal.title | Quality & Quantity | es |
| dc.journal.volume | 48 | es |
| dc.language.iso | eng | es |
| dc.publisher | Springer | es |
| dc.relation.alternativeid | info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1007/s11135-013-9855-z | |
| dc.relation.alternativeid | info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007/s11135-013-9855-z | |
| dc.rights | info:eu-repo/semantics/restrictedAccess | * |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ | * |
| dc.subject | Crises | es |
| dc.subject | Exchange Rate | es |
| dc.subject | Hierarchical Tree | es |
| dc.subject.classification | Otras Economía y Negocios | es |
| dc.subject.classification | Economía y Negocios | es |
| dc.subject.classification | CIENCIAS SOCIALES | es |
| dc.title | Network analysis of exchange data: interdependence drives crisis contagion | es |
| dc.type | info:eu-repo/semantics/article | |
| dc.type | info:ar-repo/semantics/artículo | |
| dc.type | info:eu-repo/semantics/publishedVersion | |
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