Previsão da estrutura a termo de cupom cambial
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Repositório Institucional do FGV (FGV Repositório Digital) |
Texto Completo: | http://hdl.handle.net/10438/19300 |
Resumo: | This paper proposes to apply a similar framework adopted by Diebold and Li (2006) to forecast the Brazilian term structure of the US dollar-denominated interest rates, which have been done through the well-known three factors model developed by Nelson-Siegel. The methodology used to find the lambda factor, which drives the decay velocity of interest rates, was the rolling window optimization where for each forecast was calculated the lambda that minimizes the root mean square error (RMSE) of Nelson and Siegel fit. Furthermore, an autoregressive model was used to estimate the latent factors and, consequently, the interest rate. The results obtained were analogous to those found by Diebold and Li, where the authors verified a good predictive capacity for the model when compared to the random walk and other models used as benchmark. |
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Barbosa, Diego MakaseviciusEscolas::EPGEFGVVicente, JoséGonçalves, Edson Daniel LopesGlasman, Daniela Kubudi2017-12-08T16:46:06Z2017-12-08T16:46:06Z2017-09-25http://hdl.handle.net/10438/19300This paper proposes to apply a similar framework adopted by Diebold and Li (2006) to forecast the Brazilian term structure of the US dollar-denominated interest rates, which have been done through the well-known three factors model developed by Nelson-Siegel. The methodology used to find the lambda factor, which drives the decay velocity of interest rates, was the rolling window optimization where for each forecast was calculated the lambda that minimizes the root mean square error (RMSE) of Nelson and Siegel fit. Furthermore, an autoregressive model was used to estimate the latent factors and, consequently, the interest rate. The results obtained were analogous to those found by Diebold and Li, where the authors verified a good predictive capacity for the model when compared to the random walk and other models used as benchmark.O presente trabalho concentra-se em fazer um exercício de previsão da curva de cupom cambial futura similar ao proposto por Diebold e Li (2006) para as treasuries americanas, onde os autores utilizam um modelo econométrico de três fatores, no caso o conhecido Nelson e Siegel. A metodologia adotada para encontrar o fator λ (lambda), parâmetro este que rege a velocidade de decaimento da taxa do cupom cambial, foi uma otimização utilizando uma janela móvel, onde para cada instante t é observado qual o lambda que minimizaria a raiz do erro quadrático médio (REQM) do fit do modelo de Nelson-Siegel. Em seguida é conduzido um modelo autoregressivo para estimar os fatores latentes e consequentemente a taxa de cupom cambial para o exercício. O resultado obtido foi em linha com o encontrado por Diebold e Li onde os autores constataram uma boa capacidade preditiva para o modelo quando comparado ao passeio aleatório, nosso benchmark.porDollar-denominated interest ratesForcastingTerm structureCupom cambialPrevisãoEstrutura a termoFinançasTaxa de jurosInvestimentos - AnáliseMercado financeiroPrevisão da estrutura a termo de cupom cambialinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisreponame:Repositório Institucional do FGV (FGV Repositório Digital)instname:Fundação Getulio Vargas (FGV)instacron:FGVinfo:eu-repo/semantics/openAccessTEXTTrabalho Final (Assinada).pdf.txtTrabalho Final (Assinada).pdf.txtExtracted texttext/plain55226https://repositorio.fgv.br/bitstreams/95c6d039-adc1-46bd-9507-ac9d5cca0fa5/downloadd32d8c59d0e56455215cc6fa77bca68eMD57ORIGINALTrabalho Final (Assinada).pdfTrabalho Final 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dc.title.por.fl_str_mv |
Previsão da estrutura a termo de cupom cambial |
title |
Previsão da estrutura a termo de cupom cambial |
spellingShingle |
Previsão da estrutura a termo de cupom cambial Barbosa, Diego Makasevicius Dollar-denominated interest rates Forcasting Term structure Cupom cambial Previsão Estrutura a termo Finanças Taxa de juros Investimentos - Análise Mercado financeiro |
title_short |
Previsão da estrutura a termo de cupom cambial |
title_full |
Previsão da estrutura a termo de cupom cambial |
title_fullStr |
Previsão da estrutura a termo de cupom cambial |
title_full_unstemmed |
Previsão da estrutura a termo de cupom cambial |
title_sort |
Previsão da estrutura a termo de cupom cambial |
author |
Barbosa, Diego Makasevicius |
author_facet |
Barbosa, Diego Makasevicius |
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 |
Vicente, José Gonçalves, Edson Daniel Lopes |
dc.contributor.author.fl_str_mv |
Barbosa, Diego Makasevicius |
dc.contributor.advisor1.fl_str_mv |
Glasman, Daniela Kubudi |
contributor_str_mv |
Glasman, Daniela Kubudi |
dc.subject.eng.fl_str_mv |
Dollar-denominated interest rates Forcasting Term structure |
topic |
Dollar-denominated interest rates Forcasting Term structure Cupom cambial Previsão Estrutura a termo Finanças Taxa de juros Investimentos - Análise Mercado financeiro |
dc.subject.por.fl_str_mv |
Cupom cambial Previsão Estrutura a termo |
dc.subject.area.por.fl_str_mv |
Finanças |
dc.subject.bibliodata.por.fl_str_mv |
Taxa de juros Investimentos - Análise Mercado financeiro |
description |
This paper proposes to apply a similar framework adopted by Diebold and Li (2006) to forecast the Brazilian term structure of the US dollar-denominated interest rates, which have been done through the well-known three factors model developed by Nelson-Siegel. The methodology used to find the lambda factor, which drives the decay velocity of interest rates, was the rolling window optimization where for each forecast was calculated the lambda that minimizes the root mean square error (RMSE) of Nelson and Siegel fit. Furthermore, an autoregressive model was used to estimate the latent factors and, consequently, the interest rate. The results obtained were analogous to those found by Diebold and Li, where the authors verified a good predictive capacity for the model when compared to the random walk and other models used as benchmark. |
publishDate |
2017 |
dc.date.accessioned.fl_str_mv |
2017-12-08T16:46:06Z |
dc.date.available.fl_str_mv |
2017-12-08T16:46:06Z |
dc.date.issued.fl_str_mv |
2017-09-25 |
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.uri.fl_str_mv |
http://hdl.handle.net/10438/19300 |
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http://hdl.handle.net/10438/19300 |
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 |
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FGV |
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