Previsão de rating empresarial com o uso de índices contábeis
| Ano de defesa: | 2021 |
|---|---|
| Autor(a) principal: | |
| Orientador(a): | |
| Banca de defesa: | |
| Tipo de documento: | Dissertação |
| Tipo de acesso: | Acesso aberto |
| Idioma: | por |
| Instituição de defesa: |
Não Informado pela instituição
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| Programa de Pós-Graduação: |
Não Informado pela instituição
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| Departamento: |
Não Informado pela instituição
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| País: |
Não Informado pela instituição
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| Palavras-chave em Português: | |
| Link de acesso: | http://www.repositorio.ufc.br/handle/riufc/59886 |
Resumo: | Credit rating is a tool that provides interested professionals with an efficient way to analyze a company’s credit risk. In this work, forecast models for the credit rating of Brazilian companies were estimated, using the S&P credit rating and accounting ratios for the period 2017 to 2019. The rating of the companies in the sample is between B and AAA ratings. The first estimated model was the ordered post-lasso probit with five statistically significant variables. The results of this model corroborate those obtained by Damasceno et al. (2008), but they have a higher hit rate, correctly predicting 72.39% of the sample. The model had a low hit rate for rating categories B, A and AAA, while category AA had a high hit rate of 97.65%. The third estimated model was the ordered probit model with the variables selected by Damasceno et al. (2008), using data from this survey. The two variables present in the model were statistically significant. The hit rate of the model was 64.92%, being lower than the first model. The third model was not able to predict any ratings B or AAA, but correctly predicted all ratings AA. |
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Ferreira, Danilo Alves VerasSouza, Sérgio Aquino de2021-08-09T17:23:18Z2021-08-09T17:23:18Z2021FERREIRA, Danilo Alves Veras. Previsão de rating empresarial com o uso de índices contábeis. 2021. 29f. Dissertação (Mestrado em Economia de Empresas) - Faculdade de Economia, Administração, Atuária e Contabilidade - FEAAC, Programa de Economia Profissional - PEP, Universidade Federal do Ceará - UFC, Fortaleza (CE), 2021.http://www.repositorio.ufc.br/handle/riufc/59886Credit rating is a tool that provides interested professionals with an efficient way to analyze a company’s credit risk. In this work, forecast models for the credit rating of Brazilian companies were estimated, using the S&P credit rating and accounting ratios for the period 2017 to 2019. The rating of the companies in the sample is between B and AAA ratings. The first estimated model was the ordered post-lasso probit with five statistically significant variables. The results of this model corroborate those obtained by Damasceno et al. (2008), but they have a higher hit rate, correctly predicting 72.39% of the sample. The model had a low hit rate for rating categories B, A and AAA, while category AA had a high hit rate of 97.65%. The third estimated model was the ordered probit model with the variables selected by Damasceno et al. (2008), using data from this survey. The two variables present in the model were statistically significant. The hit rate of the model was 64.92%, being lower than the first model. The third model was not able to predict any ratings B or AAA, but correctly predicted all ratings AA.O rating de crédito é uma ferramenta que proporciona aos profissionais interessados uma maneira eficiente de analisar o risco de crédito de uma empresa. Nesse trabalho foram estimados modelos previsão de rating de crédito de empresas brasileiras, utilizando o rating de crédito da S&P e índices contábeis para o período de 2017 a 2019. O rating das empresas da amostra está entre as avaliações B e AAA. O primeiro modelo estimado foi o pós-lasso probit ordenado com cinco variáveis estatisticamente significantes. Os resultados desse modelo corroboram com os obtidos por Damasceno et al. (2008), nas contam com uma taxa de acerto maior, prevendo corretamente 72,39% da amostra. O modelo apresentou baixa taxa de acerto para as categorias de rating B, A e AAA, já a categoria AA teve uma alta taxa de acerto de 97,65%. O terceiro modelo estimado foi o modelo probit ordenado com as variáveis selecionadas por Damasceno et al. (2008), utilizando os dados dessa pesquisa. As duas variáveis presentes no modelo foram estatisticamente significantes. A taxa de acerto do modelo foi de 64,92%, sendo inferior ao primeiro modelo. O terceiro modelo não foi capaz de prever nenhum rating B ou AAA, mas previu corretamente todos os ratings AA.Rating de créditoProbit ordenadoLassoContabilidadePrevisão de rating empresarial com o uso de índices contábeisinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisporreponame:Repositório Institucional da Universidade Federal do Ceará (UFC)instname:Universidade Federal do Ceará (UFC)instacron:UFCinfo:eu-repo/semantics/openAccessLICENSElicense.txtlicense.txttext/plain; charset=utf-81748http://repositorio.ufc.br/bitstream/riufc/59886/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52ORIGINAL2021_dis_davferreira.pdf2021_dis_davferreira.pdfapplication/pdf415024http://repositorio.ufc.br/bitstream/riufc/59886/1/2021_dis_davferreira.pdf82856e1230a7de04aa9390e55ee4b4cbMD51riufc/598862023-07-12 15:57:50.228oai:repositorio.ufc.br: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Repositório InstitucionalPUBhttp://www.repositorio.ufc.br/ri-oai/requestbu@ufc.br || repositorio@ufc.bropendoar:2023-07-12T18:57:50Repositório Institucional da Universidade Federal do Ceará (UFC) - Universidade Federal do Ceará (UFC)false |
| dc.title.pt_BR.fl_str_mv |
Previsão de rating empresarial com o uso de índices contábeis |
| title |
Previsão de rating empresarial com o uso de índices contábeis |
| spellingShingle |
Previsão de rating empresarial com o uso de índices contábeis Ferreira, Danilo Alves Veras Rating de crédito Probit ordenado Lasso Contabilidade |
| title_short |
Previsão de rating empresarial com o uso de índices contábeis |
| title_full |
Previsão de rating empresarial com o uso de índices contábeis |
| title_fullStr |
Previsão de rating empresarial com o uso de índices contábeis |
| title_full_unstemmed |
Previsão de rating empresarial com o uso de índices contábeis |
| title_sort |
Previsão de rating empresarial com o uso de índices contábeis |
| author |
Ferreira, Danilo Alves Veras |
| author_facet |
Ferreira, Danilo Alves Veras |
| author_role |
author |
| dc.contributor.author.fl_str_mv |
Ferreira, Danilo Alves Veras |
| dc.contributor.advisor1.fl_str_mv |
Souza, Sérgio Aquino de |
| contributor_str_mv |
Souza, Sérgio Aquino de |
| dc.subject.por.fl_str_mv |
Rating de crédito Probit ordenado Lasso Contabilidade |
| topic |
Rating de crédito Probit ordenado Lasso Contabilidade |
| description |
Credit rating is a tool that provides interested professionals with an efficient way to analyze a company’s credit risk. In this work, forecast models for the credit rating of Brazilian companies were estimated, using the S&P credit rating and accounting ratios for the period 2017 to 2019. The rating of the companies in the sample is between B and AAA ratings. The first estimated model was the ordered post-lasso probit with five statistically significant variables. The results of this model corroborate those obtained by Damasceno et al. (2008), but they have a higher hit rate, correctly predicting 72.39% of the sample. The model had a low hit rate for rating categories B, A and AAA, while category AA had a high hit rate of 97.65%. The third estimated model was the ordered probit model with the variables selected by Damasceno et al. (2008), using data from this survey. The two variables present in the model were statistically significant. The hit rate of the model was 64.92%, being lower than the first model. The third model was not able to predict any ratings B or AAA, but correctly predicted all ratings AA. |
| publishDate |
2021 |
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2021-08-09T17:23:18Z |
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2021-08-09T17:23:18Z |
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2021 |
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info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/masterThesis |
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masterThesis |
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publishedVersion |
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FERREIRA, Danilo Alves Veras. Previsão de rating empresarial com o uso de índices contábeis. 2021. 29f. Dissertação (Mestrado em Economia de Empresas) - Faculdade de Economia, Administração, Atuária e Contabilidade - FEAAC, Programa de Economia Profissional - PEP, Universidade Federal do Ceará - UFC, Fortaleza (CE), 2021. |
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http://www.repositorio.ufc.br/handle/riufc/59886 |
| identifier_str_mv |
FERREIRA, Danilo Alves Veras. Previsão de rating empresarial com o uso de índices contábeis. 2021. 29f. Dissertação (Mestrado em Economia de Empresas) - Faculdade de Economia, Administração, Atuária e Contabilidade - FEAAC, Programa de Economia Profissional - PEP, Universidade Federal do Ceará - UFC, Fortaleza (CE), 2021. |
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