Estratégia de alocação para portfólios de crédito corporativo no Brasil utilizando Data Envelopment Analysis (DEA)

Detalhes bibliográficos
Autor(a) principal: Cunha Júnior, Décio
Data de Publicação: 2021
Tipo de documento: Tese
Idioma: por
Título da fonte: Repositório Institucional do FGV (FGV Repositório Digital)
Texto Completo: https://hdl.handle.net/10438/30649
Resumo: The purpose of this thesis is to use the Data Envelopment Analysis (DEA) methodology for corporate credit portfolios in Brazil, specifically made up of corporate bonds (debêntures); however it can be extrapolated to products with similar characteristics. Optimization of credit portfolio of corporate bonds is treated in very few academic papers and the use of DEA for this purpose is unprecedented in the country. This research consists in optimizing portfolios by checking the efficiency of the methodologies of Markowitz and Data Envelopment Analysis. Three analyses will be carried out, the first using the Markowitz model for a period resulting in an efficient frontier portfolio that presents maximum diversification; the second, using two classic DEA models; and the last, through the application of the efficient frontier model to a portfolio with maximum diversification in the two DEA models, resulting in a hybrid methodology. The reference prices for the debentures are provided by a self-regulator in the financial market. Criteria to inputs and outputs are defined regarding the DEA model. This modeling considers as inputs and outputs variables, respectively, the volatility of the spread and the duration of the asset, the return on the credit spread and the current rating of the bond. Twenty-four monthly allocations are performed and, at the end of each period, the results were compared in each allocation of the respective models. As a result, the portfolios generated by DEA methodology were performed better than the set of assets generated by Markowitz’s model for a portfolio with maximum diversification.
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spelling Cunha Júnior, DécioEscolasCicogna, Maria Paula VieiraYoshinaga, Cláudia EmikoLemgruber, Eduardo FacóEid Júnior, William2021-05-26T18:25:59Z2021-05-26T18:25:59Z2021-04-28https://hdl.handle.net/10438/30649The purpose of this thesis is to use the Data Envelopment Analysis (DEA) methodology for corporate credit portfolios in Brazil, specifically made up of corporate bonds (debêntures); however it can be extrapolated to products with similar characteristics. Optimization of credit portfolio of corporate bonds is treated in very few academic papers and the use of DEA for this purpose is unprecedented in the country. This research consists in optimizing portfolios by checking the efficiency of the methodologies of Markowitz and Data Envelopment Analysis. Three analyses will be carried out, the first using the Markowitz model for a period resulting in an efficient frontier portfolio that presents maximum diversification; the second, using two classic DEA models; and the last, through the application of the efficient frontier model to a portfolio with maximum diversification in the two DEA models, resulting in a hybrid methodology. The reference prices for the debentures are provided by a self-regulator in the financial market. Criteria to inputs and outputs are defined regarding the DEA model. This modeling considers as inputs and outputs variables, respectively, the volatility of the spread and the duration of the asset, the return on the credit spread and the current rating of the bond. Twenty-four monthly allocations are performed and, at the end of each period, the results were compared in each allocation of the respective models. As a result, the portfolios generated by DEA methodology were performed better than the set of assets generated by Markowitz’s model for a portfolio with maximum diversification.A finalidade desta tese consiste na utilização da metodologia Data Envelopment Analysis (DEA) para portfólios de crédito corporativo no Brasil, especificamente constituídos de debêntures, contudo, pode ser extrapolado para produtos com características similares. A otimização de carteiras de crédito de títulos corporativos é tratada em raríssimos trabalhos acadêmicos e a utilização de DEA para este fim é inédita no país. Esta pesquisa consiste na otimização de portfólios, mediante a verificação da eficiência das metodologias de Markowitz e da Análise Envoltória de Dados (DEA). São realizadas três análises: a primeira, utilizando o modelo de Markowitz para um período resultando em uma carteira da fronteira eficiente que apresente máxima diversificação; a segunda, com a utilização de dois modelos DEA clássicos; e a última, mediante a aplicação do modelo de fronteira eficiente para uma carteira com máxima diversificação nas duas modelagens DEA, tendo como resultado uma metodologia híbrida. Os preços de referência das debêntures são fornecidos por um autorregulador do mercado financeiro. Com relação ao modelo DEA, são definidos critérios de inputs e outputs do modelo. Para os indicadores de entrada e saída desta modelagem são considerados, respectivamente, a volatilidade do spread e o prazo médio do ativo; o retorno do spread de crédito e o rating atual da emissão. São performadas vinte e quatro alocações mensais e ao final de cada período se procedeu a comparação dos resultados em cada alocação dos respectivos modelos, e como resultado, os portfólios gerados pela modelagem DEA performaram melhor do que a carteira com máxima diversificação resultante do modelo de Markowitz.porData Envelopment Analysis (DEA)Corporate bondsPortfolio pptimizationMarkowitz’s modelPortfolio with maximum diversificationDebênturesOtimização de portfólioModelo de MarkowitzCarteira com máxima diversificaçãoAdministração de empresasDebênturesInvestimentos - AdministraçãoAnálise envoltória de dadosEstratégia de alocação para portfólios de crédito corporativo no Brasil utilizando Data Envelopment Analysis (DEA)info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional do FGV (FGV Repositório Digital)instname:Fundação Getulio Vargas (FGV)instacron:FGVLICENSElicense.txtlicense.txttext/plain; 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dc.title.por.fl_str_mv Estratégia de alocação para portfólios de crédito corporativo no Brasil utilizando Data Envelopment Analysis (DEA)
title Estratégia de alocação para portfólios de crédito corporativo no Brasil utilizando Data Envelopment Analysis (DEA)
spellingShingle Estratégia de alocação para portfólios de crédito corporativo no Brasil utilizando Data Envelopment Analysis (DEA)
Cunha Júnior, Décio
Data Envelopment Analysis (DEA)
Corporate bonds
Portfolio pptimization
Markowitz’s model
Portfolio with maximum diversification
Debêntures
Otimização de portfólio
Modelo de Markowitz
Carteira com máxima diversificação
Administração de empresas
Debêntures
Investimentos - Administração
Análise envoltória de dados
title_short Estratégia de alocação para portfólios de crédito corporativo no Brasil utilizando Data Envelopment Analysis (DEA)
title_full Estratégia de alocação para portfólios de crédito corporativo no Brasil utilizando Data Envelopment Analysis (DEA)
title_fullStr Estratégia de alocação para portfólios de crédito corporativo no Brasil utilizando Data Envelopment Analysis (DEA)
title_full_unstemmed Estratégia de alocação para portfólios de crédito corporativo no Brasil utilizando Data Envelopment Analysis (DEA)
title_sort Estratégia de alocação para portfólios de crédito corporativo no Brasil utilizando Data Envelopment Analysis (DEA)
author Cunha Júnior, Décio
author_facet Cunha Júnior, Décio
author_role author
dc.contributor.unidadefgv.por.fl_str_mv Escolas
dc.contributor.member.none.fl_str_mv Cicogna, Maria Paula Vieira
Yoshinaga, Cláudia Emiko
Lemgruber, Eduardo Facó
dc.contributor.author.fl_str_mv Cunha Júnior, Décio
dc.contributor.advisor1.fl_str_mv Eid Júnior, William
contributor_str_mv Eid Júnior, William
dc.subject.eng.fl_str_mv Data Envelopment Analysis (DEA)
Corporate bonds
Portfolio pptimization
Markowitz’s model
Portfolio with maximum diversification
topic Data Envelopment Analysis (DEA)
Corporate bonds
Portfolio pptimization
Markowitz’s model
Portfolio with maximum diversification
Debêntures
Otimização de portfólio
Modelo de Markowitz
Carteira com máxima diversificação
Administração de empresas
Debêntures
Investimentos - Administração
Análise envoltória de dados
dc.subject.por.fl_str_mv Debêntures
Otimização de portfólio
Modelo de Markowitz
Carteira com máxima diversificação
dc.subject.area.por.fl_str_mv Administração de empresas
dc.subject.bibliodata.por.fl_str_mv Debêntures
Investimentos - Administração
Análise envoltória de dados
description The purpose of this thesis is to use the Data Envelopment Analysis (DEA) methodology for corporate credit portfolios in Brazil, specifically made up of corporate bonds (debêntures); however it can be extrapolated to products with similar characteristics. Optimization of credit portfolio of corporate bonds is treated in very few academic papers and the use of DEA for this purpose is unprecedented in the country. This research consists in optimizing portfolios by checking the efficiency of the methodologies of Markowitz and Data Envelopment Analysis. Three analyses will be carried out, the first using the Markowitz model for a period resulting in an efficient frontier portfolio that presents maximum diversification; the second, using two classic DEA models; and the last, through the application of the efficient frontier model to a portfolio with maximum diversification in the two DEA models, resulting in a hybrid methodology. The reference prices for the debentures are provided by a self-regulator in the financial market. Criteria to inputs and outputs are defined regarding the DEA model. This modeling considers as inputs and outputs variables, respectively, the volatility of the spread and the duration of the asset, the return on the credit spread and the current rating of the bond. Twenty-four monthly allocations are performed and, at the end of each period, the results were compared in each allocation of the respective models. As a result, the portfolios generated by DEA methodology were performed better than the set of assets generated by Markowitz’s model for a portfolio with maximum diversification.
publishDate 2021
dc.date.accessioned.fl_str_mv 2021-05-26T18:25:59Z
dc.date.available.fl_str_mv 2021-05-26T18:25:59Z
dc.date.issued.fl_str_mv 2021-04-28
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/doctoralThesis
format doctoralThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://hdl.handle.net/10438/30649
url https://hdl.handle.net/10438/30649
dc.language.iso.fl_str_mv por
language por
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositório Institucional do FGV (FGV Repositório Digital)
instname:Fundação Getulio Vargas (FGV)
instacron:FGV
instname_str Fundação Getulio Vargas (FGV)
instacron_str FGV
institution FGV
reponame_str Repositório Institucional do FGV (FGV Repositório Digital)
collection Repositório Institucional do FGV (FGV Repositório Digital)
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https://repositorio.fgv.br/bitstreams/fd260afd-93db-4d85-91cc-45b0cb36cce1/download
https://repositorio.fgv.br/bitstreams/9ba293fd-485e-4317-bb08-60fc54e99769/download
bitstream.checksum.fl_str_mv dfb340242cced38a6cca06c627998fa1
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bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
MD5
MD5
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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