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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/74835
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dc.contributor.authorDa Fonseca, Eder Lucio-
dc.contributor.authorFerreira, Fernando F.-
dc.contributor.authorMuruganandam, Paulsamy-
dc.contributor.authorCerdeira, Hilda A.-
dc.date.accessioned2014-05-27T11:28:40Z-
dc.date.accessioned2016-10-25T18:45:35Z-
dc.date.available2014-05-27T11:28:40Z-
dc.date.available2016-10-25T18:45:35Z-
dc.date.issued2013-03-15-
dc.identifierhttp://dx.doi.org/10.1016/j.physa.2012.11.006-
dc.identifier.citationPhysica A: Statistical Mechanics and its Applications, v. 392, n. 6, p. 1386-1392, 2013.-
dc.identifier.issn0378-4371-
dc.identifier.urihttp://hdl.handle.net/11449/74835-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/74835-
dc.description.abstractFollowing the thermodynamic formulation of a multifractal measure that was shown to enable the detection of large fluctuations at an early stage, here we propose a new index which permits us to distinguish events like financial crises in real time. We calculate the partition function from which we can obtain thermodynamic quantities analogous to the free energy and specific heat. The index is defined as the normalized energy variation and it can be used to study the behavior of stochastic time series, such as financial market daily data. Famous financial market crashes-Black Thursday (1929), Black Monday (1987) and the subprime crisis (2008)-are identified with clear and robust results. The method is also applied to the market fluctuations of 2011. From these results it appears as if the apparent crisis of 2011 is of a different nature to the other three. We also show that the analysis has forecasting capabilities. © 2012 Elsevier B.V. All rights reserved.en
dc.format.extent1386-1392-
dc.language.isoeng-
dc.sourceScopus-
dc.subjectEconophysics-
dc.subjectFinancial markets-
dc.subjectFluctuation phenomena-
dc.subjectFractals-
dc.subjectInterdisciplinary physics-
dc.subjectTime series analysis-
dc.subjectEconophysicss-
dc.subjectEnergy variations-
dc.subjectFinancial crisis-
dc.subjectFinancial market-
dc.subjectForecasting capability-
dc.subjectMarket fluctuations-
dc.subjectMulti fractals-
dc.subjectNew indices-
dc.subjectPartition functions-
dc.subjectReal time-
dc.subjectStochastic time series-
dc.subjectThermodynamic formulation-
dc.subjectThermodynamic quantities-
dc.subjectFinance-
dc.subjectCommerce-
dc.titleIdentifying financial crises in real timeen
dc.typeoutro-
dc.contributor.institutionUniversidade de São Paulo (USP)-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.contributor.institutionPalkalaiperur Campus-
dc.description.affiliationGRIFE-Escola de Arte, Ciências e Humanidades Universidade de São Paulo, Av. Arlindo Bettio 1000, 03828-000 São Paulo-
dc.description.affiliationInstituto de Física Teórica UNESP-Universidade Estadual Paulista, Rua Dr. Bento Teobaldo Ferraz 271, Bloco II, 01140-070 São Paulo-
dc.description.affiliationSchool of Physics Bharathidasan University Palkalaiperur Campus, Tiruchirappalli 620024, Tamilnadu-
dc.description.affiliationInstituto de Matemática Estatística Universidade de São Paulo, Rua do Matão, 1010, 05508-090 São Paulo, SP-
dc.description.affiliationUnespInstituto de Física Teórica UNESP-Universidade Estadual Paulista, Rua Dr. Bento Teobaldo Ferraz 271, Bloco II, 01140-070 São Paulo-
dc.identifier.doi10.1016/j.physa.2012.11.006-
dc.identifier.wosWOS:000315618100012-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofPhysica A: Statistical Mechanics and Its Applications-
dc.identifier.scopus2-s2.0-84872297411-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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