Classificação de ratings, sustentabilidade e previsão de default uma abordagem utilizando a regressão quantílica

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dc.contributor.advisorPerera, Luiz Carlos Jacobpt_BR
dc.contributor.advisor1Latteshttp://lattes.cnpq.br/3386375141622007por
dc.contributor.authorAlves Filho, Cy Dy Augustopt_BR
dc.creator.Latteshttp://lattes.cnpq.br/4800239507072382por
dc.date.accessioned2016-03-15T19:32:50Z
dc.date.accessioned2020-05-28T18:17:35Z
dc.date.available2014-12-11pt_BR
dc.date.available2020-05-28T18:17:35Z
dc.date.issued2014-08-29pt_BR
dc.description.abstractThe literature on analytical methods of accounting and corporate financial analysis models and cr edit indicators is large , and among the methods of credit risk classification is the classification model ratings, through which institutions classifie s customers according to their risk. However, the classical models of modeling credit risk using statisti cal techniques widely disseminated, as is the case of simple linear regression, the least squares method, among others. The quantile regression, evaluated in disseminated by Koenker and Basset (1978) has it as a main characteristic , analyzing the sample by the median and allow the analysis of subpopulations through the quantiles of the sample, which allows more specific inferences in according to the needs of the study. In recent years the concern with social and environmental issues have become increasing present in both the practical means and academia and in society in general, which brings up the idea of including the analysis of social indicators in environmental analysis credit, as already proposed in previous studies. However, the combined use of ec onomic, financial, social and environmental indicators, together with quantile regression, is an innovative proposal, and the subject of this academic study. This work is an exploratory and descriptive study , objective verify the possible contribution of t he inclusion of social and environmental variables, combined with the use of quantile regression for ratings classification and hence prediction of default. To fulfill this goal, we devel oped a database on panel, with the total of 561 observations, consist ing of data from publicly traded, its ratings, economic indicators, financial, social and environmental, the years 2007 to 2012 companies. With use of quantile regression was possible to infer that the social environmental variables are relevant for classi fication ratings and, consequently, to predict default.eng
dc.formatapplication/pdfpor
dc.identifier.urihttp://dspace.mackenzie.br/handle/10899/26297
dc.languageporpor
dc.publisherUniversidade Presbiteriana Mackenziepor
dc.rightsAcesso Abertopor
dc.subjectratingpor
dc.subjectregressão quantílicapor
dc.subjectdefaultpor
dc.subjectsustentabilidade, análise de créditopor
dc.subjectindicadores sócio ambientaispor
dc.subjectindicadores econômico financeirospor
dc.subjectratingeng
dc.subjectquantile regressioneng
dc.subjectdefaulteng
dc.subjectsustainabilityeng
dc.subjectcredit analysiseng
dc.subjectsocio environmental indicatorseng
dc.subjecteconomic indicators financialeng
dc.subject.cnpqCNPQ::CIENCIAS SOCIAIS APLICADAS::ADMINISTRACAO::CIENCIAS CONTABEISpor
dc.thumbnail.urlhttp://tede.mackenzie.br/jspui/retrieve/3259/Cy-dy%20Augusto%20Alves%20Filho.pdf.jpg*
dc.titleClassificação de ratings, sustentabilidade e previsão de default uma abordagem utilizando a regressão quantílicapor
dc.typeDissertaçãopor
local.contributor.board1Mendonça Neto, Octavio Ribeiro dept_BR
local.contributor.board2Kimura, Herbertpt_BR
local.contributor.board2Latteshttp://lattes.cnpq.br/2048706172366367por
local.publisher.countryBRpor
local.publisher.departmentCiências Contábeispor
local.publisher.initialsUPMpor
local.publisher.programControladoria Empresarialpor
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