Estratégia de alocação para portfólios de crédito corporativo no Brasil utilizando Data Envelopment Analysis (DEA)
Autor(a) principal: | |
---|---|
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. |
id |
FGV_1c519cb315fb58b3e20f59bbb1e27dec |
---|---|
oai_identifier_str |
oai:repositorio.fgv.br:10438/30649 |
network_acronym_str |
FGV |
network_name_str |
Repositório Institucional do FGV (FGV Repositório Digital) |
repository_id_str |
3974 |
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; charset=utf-84707https://repositorio.fgv.br/bitstreams/cc40ea3b-d1da-43ca-8aee-56a2ad32a470/downloaddfb340242cced38a6cca06c627998fa1MD52ORIGINALTese Decio Cunha Jr_DEA.pdfTese Decio Cunha Jr_DEA.pdfPDFapplication/pdf1676392https://repositorio.fgv.br/bitstreams/e5dca81a-899b-4f3e-a770-ea286fb9312d/download5dd8e0b4f4c279e74dcc7dd5dfa276e3MD51TEXTTese Decio Cunha Jr_DEA.pdf.txtTese Decio Cunha Jr_DEA.pdf.txtExtracted texttext/plain103227https://repositorio.fgv.br/bitstreams/fd260afd-93db-4d85-91cc-45b0cb36cce1/downloadc3c1dbe33d01f7f776819a773cd78a09MD55THUMBNAILTese Decio Cunha Jr_DEA.pdf.jpgTese Decio Cunha Jr_DEA.pdf.jpgGenerated Thumbnailimage/jpeg2630https://repositorio.fgv.br/bitstreams/9ba293fd-485e-4317-bb08-60fc54e99769/downloadc624f1def2aa0b75071b451e94e77170MD5610438/306492024-10-08 13:55:02.071open.accessoai:repositorio.fgv.br:10438/30649https://repositorio.fgv.brRepositório InstitucionalPRIhttp://bibliotecadigital.fgv.br/dspace-oai/requestopendoar:39742024-10-08T13:55:02Repositório Institucional do FGV (FGV Repositório Digital) - Fundação Getulio Vargas (FGV)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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) |
bitstream.url.fl_str_mv |
https://repositorio.fgv.br/bitstreams/cc40ea3b-d1da-43ca-8aee-56a2ad32a470/download https://repositorio.fgv.br/bitstreams/e5dca81a-899b-4f3e-a770-ea286fb9312d/download 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 5dd8e0b4f4c279e74dcc7dd5dfa276e3 c3c1dbe33d01f7f776819a773cd78a09 c624f1def2aa0b75071b451e94e77170 |
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 |
|
_version_ |
1813797672189952000 |