Determinantes de intervenção do Banco Central do Brasil no mercado de câmbio: uma abordagem empírica por regressão logística e redes neurais
| Ano de defesa: | 2015 |
|---|---|
| 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
|
| Departamento: |
Não Informado pela instituição
|
| País: |
Não Informado pela instituição
|
| Palavras-chave em Português: | |
| Palavras-chave em Inglês: | |
| Link de acesso: | http://hdl.handle.net/10438/14112 |
Resumo: | A common scenario in countries with inflation targeting regimes is Central Bank intervention in exchange market to keep volatility under control. Those interventions are commom in developing countries. In Brazil interventions are mostly done through spot market, derivatives market (exchange rate swaps) and also through forward market operations, liquidity and borrowing lines. Due to low volumes related to the last three, we kept our efforts concentrated in interventions through spot and derivatives markets. There are several articles discussing how successful those interventions are but only a few evaluating which factors may lead Central Bank of Brazil to an intervention. We try to fill this gap using two different techniques: the ever present logistic regression and a new approach (as fas as we know) using artificial neural networks. In parallel we will try to define if there are specific factors affecting different scenarios of intervention. The dataset goes from 2005 to 2012, period where Central Bank of Brazil has been intervening based on market demand and not in a standardized way for longer periods of time. Our results show that there may be factors more relevant to one of the intervention decisions (buying or selling dollars) and we can highlight the relevance of exchange rate volatility, particularly in interventions where Central Bank of Brazil is buying dollars. This result is fully aligned with other papers on the subject. |
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Figueiredo, Cassius Marcellus do CarmoEscolas::EMApAraújo, Gustavo SilvaBranco, Antônio Carlos SaraivaEvsukoff, Alexandre GonçalvesLeão, SérgioCansino, Hugo Alexander de la Cruz2015-10-13T13:12:33Z2015-10-13T13:12:33Z2015-08-31FIGUEIREDO, Cassius Marcellus do Carmo. Determinantes de intervenção do Banco Central do Brasil no mercado de câmbio: uma abordagem empírica por regressão logística e redes neurais. Dissertação (Mestrado em Matemática Aplicada) - Escola de Matemática Aplicada, Fundação Getúlio Vargas - FGV, Rio de Janeiro, 2015.http://hdl.handle.net/10438/14112A common scenario in countries with inflation targeting regimes is Central Bank intervention in exchange market to keep volatility under control. Those interventions are commom in developing countries. In Brazil interventions are mostly done through spot market, derivatives market (exchange rate swaps) and also through forward market operations, liquidity and borrowing lines. Due to low volumes related to the last three, we kept our efforts concentrated in interventions through spot and derivatives markets. There are several articles discussing how successful those interventions are but only a few evaluating which factors may lead Central Bank of Brazil to an intervention. We try to fill this gap using two different techniques: the ever present logistic regression and a new approach (as fas as we know) using artificial neural networks. In parallel we will try to define if there are specific factors affecting different scenarios of intervention. The dataset goes from 2005 to 2012, period where Central Bank of Brazil has been intervening based on market demand and not in a standardized way for longer periods of time. Our results show that there may be factors more relevant to one of the intervention decisions (buying or selling dollars) and we can highlight the relevance of exchange rate volatility, particularly in interventions where Central Bank of Brazil is buying dollars. This result is fully aligned with other papers on the subject.Em economias com regimes de metas de inflação é comum que Bancos Centrais intervenham para reduzir os níveis de volatilidade do dólar, sendo estas intervenções mais comuns em países não desenvolvidos. No caso do Brasil, estas intervenções acontecem diretamente no mercado à vista, via mercado de derivativos (através de swaps cambiais) ou ainda com operações a termo, linhas de liquidez e via empréstimos. Neste trabalho mantemos o foco nas intervenções no mercado à vista e de derivativos pois estas representam o maior volume financeiro relacionado à este tipo de atuação oficial. Existem diversos trabalhos que avaliam o impacto das intervenções e seus graus de sucesso ou fracasso mas relativamente poucos que abordam o que levaria o Banco Central do Brasil (BCB) a intervir no mercado. Tentamos preencher esta lacuna avaliando as variáveis que podem se relacionar às intervenções do BCB no mercado de câmbio e adicionalmente verificando se essas variáveis se relacionam diferentemente com as intervenções de venda e compra de dólares. Para tal, além de utilizarmos regressões logísticas, como na maioria dos trabalhos sobre o tema, empregamos também a técnica de redes neurais, até onde sabemos inédita para o assunto. O período de estudo vai de 2005 a 2012, onde o BCB interveio no mercado de câmbio sob demanda e não de forma continuada por longos períodos de tempo, como nos anos mais recentes. Os resultados indicam que algumas variáveis são mais relevantes para o processo de intervenção vendendo ou comprando dólares, com destaque para a volatilidade implícita do câmbio nas intervenções que envolvem venda de dólares, resultado este alinhado com outros trabalhos sobre o tema.porCentral Bank of BrazilExchange rate interventionLogitBanco Central do BrasilCâmbioRedes neurais (Computação)Neural networksMatemáticaBanco Central do BrasilCâmbioRedes neurais (Computação)Determinantes de intervenção do Banco Central do Brasil no mercado de câmbio: uma abordagem empírica por regressão logística e redes neuraisinfo: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/openAccessORIGINALDissertação_Cassius_Figueiredo.pdfDissertação_Cassius_Figueiredo.pdfDissertação de 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| dc.title.por.fl_str_mv |
Determinantes de intervenção do Banco Central do Brasil no mercado de câmbio: uma abordagem empírica por regressão logística e redes neurais |
| title |
Determinantes de intervenção do Banco Central do Brasil no mercado de câmbio: uma abordagem empírica por regressão logística e redes neurais |
| spellingShingle |
Determinantes de intervenção do Banco Central do Brasil no mercado de câmbio: uma abordagem empírica por regressão logística e redes neurais Figueiredo, Cassius Marcellus do Carmo Central Bank of Brazil Exchange rate intervention Logit Banco Central do Brasil Câmbio Redes neurais (Computação) Neural networks Matemática Banco Central do Brasil Câmbio Redes neurais (Computação) |
| title_short |
Determinantes de intervenção do Banco Central do Brasil no mercado de câmbio: uma abordagem empírica por regressão logística e redes neurais |
| title_full |
Determinantes de intervenção do Banco Central do Brasil no mercado de câmbio: uma abordagem empírica por regressão logística e redes neurais |
| title_fullStr |
Determinantes de intervenção do Banco Central do Brasil no mercado de câmbio: uma abordagem empírica por regressão logística e redes neurais |
| title_full_unstemmed |
Determinantes de intervenção do Banco Central do Brasil no mercado de câmbio: uma abordagem empírica por regressão logística e redes neurais |
| title_sort |
Determinantes de intervenção do Banco Central do Brasil no mercado de câmbio: uma abordagem empírica por regressão logística e redes neurais |
| author |
Figueiredo, Cassius Marcellus do Carmo |
| author_facet |
Figueiredo, Cassius Marcellus do Carmo |
| author_role |
author |
| dc.contributor.unidadefgv.por.fl_str_mv |
Escolas::EMAp |
| dc.contributor.member.none.fl_str_mv |
Araújo, Gustavo Silva Branco, Antônio Carlos Saraiva Evsukoff, Alexandre Gonçalves Leão, Sérgio |
| dc.contributor.author.fl_str_mv |
Figueiredo, Cassius Marcellus do Carmo |
| dc.contributor.advisor1.fl_str_mv |
Cansino, Hugo Alexander de la Cruz |
| contributor_str_mv |
Cansino, Hugo Alexander de la Cruz |
| dc.subject.por.fl_str_mv |
Central Bank of Brazil Exchange rate intervention Logit Banco Central do Brasil Câmbio Redes neurais (Computação) |
| topic |
Central Bank of Brazil Exchange rate intervention Logit Banco Central do Brasil Câmbio Redes neurais (Computação) Neural networks Matemática Banco Central do Brasil Câmbio Redes neurais (Computação) |
| dc.subject.eng.fl_str_mv |
Neural networks |
| dc.subject.area.por.fl_str_mv |
Matemática |
| dc.subject.bibliodata.por.fl_str_mv |
Banco Central do Brasil Câmbio Redes neurais (Computação) |
| description |
A common scenario in countries with inflation targeting regimes is Central Bank intervention in exchange market to keep volatility under control. Those interventions are commom in developing countries. In Brazil interventions are mostly done through spot market, derivatives market (exchange rate swaps) and also through forward market operations, liquidity and borrowing lines. Due to low volumes related to the last three, we kept our efforts concentrated in interventions through spot and derivatives markets. There are several articles discussing how successful those interventions are but only a few evaluating which factors may lead Central Bank of Brazil to an intervention. We try to fill this gap using two different techniques: the ever present logistic regression and a new approach (as fas as we know) using artificial neural networks. In parallel we will try to define if there are specific factors affecting different scenarios of intervention. The dataset goes from 2005 to 2012, period where Central Bank of Brazil has been intervening based on market demand and not in a standardized way for longer periods of time. Our results show that there may be factors more relevant to one of the intervention decisions (buying or selling dollars) and we can highlight the relevance of exchange rate volatility, particularly in interventions where Central Bank of Brazil is buying dollars. This result is fully aligned with other papers on the subject. |
| publishDate |
2015 |
| dc.date.accessioned.fl_str_mv |
2015-10-13T13:12:33Z |
| dc.date.available.fl_str_mv |
2015-10-13T13:12:33Z |
| dc.date.issued.fl_str_mv |
2015-08-31 |
| 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 |
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FIGUEIREDO, Cassius Marcellus do Carmo. Determinantes de intervenção do Banco Central do Brasil no mercado de câmbio: uma abordagem empírica por regressão logística e redes neurais. Dissertação (Mestrado em Matemática Aplicada) - Escola de Matemática Aplicada, Fundação Getúlio Vargas - FGV, Rio de Janeiro, 2015. |
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http://hdl.handle.net/10438/14112 |
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FIGUEIREDO, Cassius Marcellus do Carmo. Determinantes de intervenção do Banco Central do Brasil no mercado de câmbio: uma abordagem empírica por regressão logística e redes neurais. Dissertação (Mestrado em Matemática Aplicada) - Escola de Matemática Aplicada, Fundação Getúlio Vargas - FGV, Rio de Janeiro, 2015. |
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