Avaliação do risco de crédito: aplicação do modelo KMV para obter a probabilidade de default no setor siderúrgico

Detalhes bibliográficos
Autor(a) principal: Moura, João Sichieri
Data de Publicação: 2007
Tipo de documento: Dissertação
Idioma: por
Título da fonte: Repositório Institucional do FGV (FGV Repositório Digital)
Texto Completo: https://hdl.handle.net/10438/2686
Resumo: Credit risk management has assumed increasing importance for the managers and directors of enterprises. Thus, different approaches aimed to measure the probability of default are under discussion nowadays. This paper evaluates models that have become more popular over the last 30 years in order forecast defaults or to provide information regarding to financial difficulties of enterprises. This paper will focus on the KMV model in order to estimate the probability of default, its methodology based on market value of the asset and its volatility and finally estimate the probability of default. Finally, to test the KMV model will be used a sample of global steel companies that have credit in Companhia Vale do Rio Doce (CVRD), which will allow us to make comparisons with the models presented in this work.
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spelling Moura, João SichieriEscolas::EPGEFGVLa Rocque, Eduarda Cunha deAragão, César Santiago Lima de2009-07-07T14:51:00Z2009-07-07T14:51:00Z2007-05-30MOURA, João Sichieri. Avaliação do risco de crédito: aplicação do modelo KMV para obter a probabilidade de default no setor siderúrgico. Dissertação (Mestrado em Finanças e Economia Empresarial) - Escola de Pós-Graduação em Economia, Fundação Getúlio Vargas - FGV, Rio de Janeiro, 2007.https://hdl.handle.net/10438/2686Credit risk management has assumed increasing importance for the managers and directors of enterprises. Thus, different approaches aimed to measure the probability of default are under discussion nowadays. This paper evaluates models that have become more popular over the last 30 years in order forecast defaults or to provide information regarding to financial difficulties of enterprises. This paper will focus on the KMV model in order to estimate the probability of default, its methodology based on market value of the asset and its volatility and finally estimate the probability of default. Finally, to test the KMV model will be used a sample of global steel companies that have credit in Companhia Vale do Rio Doce (CVRD), which will allow us to make comparisons with the models presented in this work.A gestão de riscos de crédito tem assumido importância cada vez maior para os gestores e administradores de empresas. Desta forma, diferentes abordagens voltadas para medir a capacidade de pagamento de empresas hoje estão em discussão. Este trabalho avalia modelos que se tornaram mais populares nos últimos 30 anos com o intuito de prever falências ou dificuldades financeiras de empresas. Será dado um enfoque para o modelo KMV de estimação de probabilidade de default e sua metodologia baseada no valor de mercado do ativo e sua volatilidade para estimar a probabilidade de default. Por fim, para testar o modelo KMV, será utilizada uma amostra de empresas siderúrgicas mundiais que possuem crédito na Companhia Vale do Rio Doce (CVRD), que nos permitirá efetuar comparações com os modelos apresentados neste trabalho.porJoão MouraModelo KMVCredit riskSteel industryEconomiaAdministração de riscoAdministração de créditoRisco (Economia)CréditosAvaliação do risco de crédito: aplicação do modelo KMV para obter a probabilidade de default no setor siderúrgicoinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional do FGV (FGV Repositório Digital)instname:Fundação Getulio Vargas (FGV)instacron:FGVORIGINALTese_MFEE_JOAO SICHIERI_2007.pdfTese_MFEE_JOAO SICHIERI_2007.pdfPDFapplication/pdf336631https://repositorio.fgv.br/bitstreams/5ce53151-e459-481d-b3ed-e5bebd7cdf55/downloaddc4d29066af0bd6c7564db0c209c3eb2MD51LICENSElicense.txtlicense.txttext/plain; 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dc.title.por.fl_str_mv Avaliação do risco de crédito: aplicação do modelo KMV para obter a probabilidade de default no setor siderúrgico
title Avaliação do risco de crédito: aplicação do modelo KMV para obter a probabilidade de default no setor siderúrgico
spellingShingle Avaliação do risco de crédito: aplicação do modelo KMV para obter a probabilidade de default no setor siderúrgico
Moura, João Sichieri
Modelo KMV
Credit risk
Steel industry
Economia
Administração de risco
Administração de crédito
Risco (Economia)
Créditos
title_short Avaliação do risco de crédito: aplicação do modelo KMV para obter a probabilidade de default no setor siderúrgico
title_full Avaliação do risco de crédito: aplicação do modelo KMV para obter a probabilidade de default no setor siderúrgico
title_fullStr Avaliação do risco de crédito: aplicação do modelo KMV para obter a probabilidade de default no setor siderúrgico
title_full_unstemmed Avaliação do risco de crédito: aplicação do modelo KMV para obter a probabilidade de default no setor siderúrgico
title_sort Avaliação do risco de crédito: aplicação do modelo KMV para obter a probabilidade de default no setor siderúrgico
author Moura, João Sichieri
author_facet Moura, João Sichieri
author_role author
dc.contributor.unidadefgv.por.fl_str_mv Escolas::EPGE
dc.contributor.affiliation.none.fl_str_mv FGV
dc.contributor.member.none.fl_str_mv La Rocque, Eduarda Cunha de
dc.contributor.author.fl_str_mv Moura, João Sichieri
dc.contributor.advisor1.fl_str_mv Aragão, César Santiago Lima de
contributor_str_mv Aragão, César Santiago Lima de
dc.subject.por.fl_str_mv Modelo KMV
topic Modelo KMV
Credit risk
Steel industry
Economia
Administração de risco
Administração de crédito
Risco (Economia)
Créditos
dc.subject.eng.fl_str_mv Credit risk
Steel industry
dc.subject.area.por.fl_str_mv Economia
dc.subject.bibliodata.por.fl_str_mv Administração de risco
Administração de crédito
Risco (Economia)
Créditos
description Credit risk management has assumed increasing importance for the managers and directors of enterprises. Thus, different approaches aimed to measure the probability of default are under discussion nowadays. This paper evaluates models that have become more popular over the last 30 years in order forecast defaults or to provide information regarding to financial difficulties of enterprises. This paper will focus on the KMV model in order to estimate the probability of default, its methodology based on market value of the asset and its volatility and finally estimate the probability of default. Finally, to test the KMV model will be used a sample of global steel companies that have credit in Companhia Vale do Rio Doce (CVRD), which will allow us to make comparisons with the models presented in this work.
publishDate 2007
dc.date.issued.fl_str_mv 2007-05-30
dc.date.accessioned.fl_str_mv 2009-07-07T14:51:00Z
dc.date.available.fl_str_mv 2009-07-07T14:51:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.citation.fl_str_mv MOURA, João Sichieri. Avaliação do risco de crédito: aplicação do modelo KMV para obter a probabilidade de default no setor siderúrgico. Dissertação (Mestrado em Finanças e Economia Empresarial) - Escola de Pós-Graduação em Economia, Fundação Getúlio Vargas - FGV, Rio de Janeiro, 2007.
dc.identifier.uri.fl_str_mv https://hdl.handle.net/10438/2686
identifier_str_mv MOURA, João Sichieri. Avaliação do risco de crédito: aplicação do modelo KMV para obter a probabilidade de default no setor siderúrgico. Dissertação (Mestrado em Finanças e Economia Empresarial) - Escola de Pós-Graduação em Economia, Fundação Getúlio Vargas - FGV, Rio de Janeiro, 2007.
url https://hdl.handle.net/10438/2686
dc.language.iso.fl_str_mv por
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dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv João Moura
publisher.none.fl_str_mv João Moura
dc.source.none.fl_str_mv reponame:Repositório Institucional do FGV (FGV Repositório Digital)
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repository.name.fl_str_mv Repositório Institucional do FGV (FGV Repositório Digital) - Fundação Getulio Vargas (FGV)
repository.mail.fl_str_mv
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