dc.contributorUniversidade Estadual Paulista (Unesp)
dc.contributorUniversidade de São Paulo (USP)
dc.date.accessioned2014-05-20T15:12:10Z
dc.date.available2014-05-20T15:12:10Z
dc.date.created2014-05-20T15:12:10Z
dc.date.issued2012-08-01
dc.identifierPesquisa Operacional. Sociedade Brasileira de Pesquisa Operacional, v. 32, n. 2, p. 293-313, 2012.
dc.identifier0101-7438
dc.identifierhttp://hdl.handle.net/11449/28299
dc.identifier10.1590/S0101-74382012005000019
dc.identifierS0101-74382012000200003
dc.identifierS0101-74382012000200003.pdf
dc.identifier1268945434870814
dc.identifier0000-0002-0968-0108
dc.description.abstractIn this work we compared the estimates of the parameters of ARCH models using a complete Bayesian method and an empirical Bayesian method in which we adopted a non-informative prior distribution and informative prior distribution, respectively. We also considered a reparameterization of those models in order to map the space of the parameters into real space. This procedure permits choosing prior normal distributions for the transformed parameters. The posterior summaries were obtained using Monte Carlo Markov chain methods (MCMC). The methodology was evaluated by considering the Telebras series from the Brazilian financial market. The results show that the two methods are able to adjust ARCH models with different numbers of parameters. The empirical Bayesian method provided a more parsimonious model to the data and better adjustment than the complete Bayesian method.
dc.languageeng
dc.publisherSociedade Brasileira de Pesquisa Operacional
dc.relationPesquisa Operacional
dc.relation0,365
dc.rightsAcesso aberto
dc.sourceSciELO
dc.subjectARCH models
dc.subjectBayesian approach
dc.subjectMCMC methods
dc.titleComparison between the complete Bayesian method and empirical Bayesian method for ARCH models using Brazilian financial time series
dc.typeArtículos de revistas


Este ítem pertenece a la siguiente institución