dc.contributorUniversidade de São Paulo (USP)
dc.contributorUniversidade Estadual Paulista (Unesp)
dc.contributorPalkalaiperur Campus
dc.date.accessioned2014-05-27T11:28:40Z
dc.date.accessioned2022-10-05T18:45:56Z
dc.date.available2014-05-27T11:28:40Z
dc.date.available2022-10-05T18:45:56Z
dc.date.created2014-05-27T11:28:40Z
dc.date.issued2013-03-15
dc.identifierPhysica A: Statistical Mechanics and its Applications, v. 392, n. 6, p. 1386-1392, 2013.
dc.identifier0378-4371
dc.identifierhttp://hdl.handle.net/11449/74835
dc.identifier10.1016/j.physa.2012.11.006
dc.identifierWOS:000315618100012
dc.identifier2-s2.0-84872297411
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/3923785
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.
dc.languageeng
dc.relationPhysica A: Statistical Mechanics and Its Applications
dc.relation2.132
dc.relation0,773
dc.rightsAcesso restrito
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 time
dc.typeArtigo


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