dc.contributorNascimento, Thiago Cavalcante
dc.contributorNascimento, Thiago Cavalcante
dc.contributorTorres, Ricardo Lobato
dc.contributorLemes Júnior, Antonio Barbosa
dc.creatorKung, Jenniger
dc.date.accessioned2020-11-23T20:09:31Z
dc.date.accessioned2022-12-06T15:18:58Z
dc.date.available2020-11-23T20:09:31Z
dc.date.available2022-12-06T15:18:58Z
dc.date.created2020-11-23T20:09:31Z
dc.date.issued2017-06-21
dc.identifierKung, Jennifer. Previsão e estresse de cenários da taxa de inadimplência de crédito no Brasil via modelagem estatística. 2017. 52 f. Trabalho de Conclusão de Curso (Especialização em Gestão Financeira) – Universidade Tecnológica Federal do Paraná, Curitiba, 2017.
dc.identifierhttp://repositorio.utfpr.edu.br/jspui/handle/1/19605
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/5264012
dc.description.abstractIt was studied the credit default rate of Brazil and adjusted statistics models utilizing time series methodology. Two types of time series models were adjusted in this work, ARIMA and ARIMAX, both models showed well adjusted to credit default rate. But, when compared the long term forecast results of both models, the forecast of ARIMAX model is more sensible to the oscillation, decrease and increase of the default rate. The stress test study’s scenarios were developed base on financial crises that Brazil have been through this latest years and, stressed default rate base on this scenario was simulated utilizing two techniques, first was a empirical simulation base on historical rate and the second was simulated using the simulate.Arima function of statistical software R. The stress test results serve as a complementary tool to assist in the creation and maintenance of credit policy so that banks can be prepared to absorb losses related to credit operations and preserve the financial system, thus ensuring the stability of the economy.
dc.publisherUniversidade Tecnológica Federal do Paraná
dc.publisherCuritiba
dc.publisherBrasil
dc.publisherEspecialização em Gestão Financeira
dc.publisherUTFPR
dc.rightsopenAccess
dc.subjectPrevisão
dc.subjectEstatística - Modelos
dc.subjectInadimplência (Finanças)
dc.subjectCrise econômica
dc.subjectCréditos - Avaliação
dc.subjectForecasting
dc.subjectStatistics - Models
dc.subjectDefault (Finance)
dc.subjectDepressions
dc.subjectCredit ratings
dc.titlePrevisão e estresse de cenários da taxa de inadimplência de crédito no Brasil via modelagem estatística
dc.typespecializationThesis


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