Modelling and forecasting the volatility of brazilian asset returns: a realized variance approach
Autor(a) principal: | |
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Data de Publicação: | 2004 |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Repositório Institucional do FGV (FGV Repositório Digital) |
Texto Completo: | http://hdl.handle.net/10438/12567 |
Resumo: | The goal of this paper is twofold. First, using five of the most actively traded stocks in the Brazilian financial market, this paper shows that the normality assumption commonly used in the risk management area to describe the distributions of returns standardized by volatilities is not compatible with volatilities estimated by EWMA or GARCH models. In sharp contrast, when the information contained in high frequency data is used to construct the realized volatilies measures, we attain the normality of the standardized returns, giving promise of improvements in Value at Risk statistics. We also describe the distributions of volatilities of the Brazilian stocks, showing that the distributions of volatilities are nearly lognormal. Second, we estimate a simple linear model to the log of realized volatilities that differs from the ones in other studies. The main difference is that we do not find evidence of long memory. The estimated model is compared with commonly used alternatives in an out-of-sample experiment. |
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Medeiros, Marcelo C.Escolas::EPGEFGV2014-11-24T13:24:14Z2014-11-24T13:24:14Z2004-06-03http://hdl.handle.net/10438/12567The goal of this paper is twofold. First, using five of the most actively traded stocks in the Brazilian financial market, this paper shows that the normality assumption commonly used in the risk management area to describe the distributions of returns standardized by volatilities is not compatible with volatilities estimated by EWMA or GARCH models. In sharp contrast, when the information contained in high frequency data is used to construct the realized volatilies measures, we attain the normality of the standardized returns, giving promise of improvements in Value at Risk statistics. We also describe the distributions of volatilities of the Brazilian stocks, showing that the distributions of volatilities are nearly lognormal. Second, we estimate a simple linear model to the log of realized volatilities that differs from the ones in other studies. The main difference is that we do not find evidence of long memory. The estimated model is compared with commonly used alternatives in an out-of-sample experiment.porEscola de Pós-Graduação em Economia da FGVSeminários de pesquisa econômica da EPGETodo cuidado foi dispensado para respeitar os direitos autorais deste trabalho. Entretanto, caso esta obra aqui depositada seja protegida por direitos autorais externos a esta instituição, contamos com a compreensão do autor e solicitamos que o mesmo faça contato através do Fale Conosco para que possamos tomar as providências cabíveisinfo:eu-repo/semantics/openAccessHigh frequency dataRisk analysisVolatility forecastingGARCH modelsRealized volatilityEconomiaMercado financeiroRisco (Economia)Modelling and forecasting the volatility of brazilian asset returns: a realized variance approachCaracterização dos retornos e das volatilidades de ativos financeiros do mercado Brasileiro : uma abordagem baseada na volatilidade realizadainfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlereponame:Repositório Institucional do FGV (FGV Repositório Digital)instname:Fundação Getulio Vargas 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|
dc.title.por.fl_str_mv |
Modelling and forecasting the volatility of brazilian asset returns: a realized variance approach |
dc.title.alternative.por.fl_str_mv |
Caracterização dos retornos e das volatilidades de ativos financeiros do mercado Brasileiro : uma abordagem baseada na volatilidade realizada |
title |
Modelling and forecasting the volatility of brazilian asset returns: a realized variance approach |
spellingShingle |
Modelling and forecasting the volatility of brazilian asset returns: a realized variance approach Medeiros, Marcelo C. High frequency data Risk analysis Volatility forecasting GARCH models Realized volatility Economia Mercado financeiro Risco (Economia) |
title_short |
Modelling and forecasting the volatility of brazilian asset returns: a realized variance approach |
title_full |
Modelling and forecasting the volatility of brazilian asset returns: a realized variance approach |
title_fullStr |
Modelling and forecasting the volatility of brazilian asset returns: a realized variance approach |
title_full_unstemmed |
Modelling and forecasting the volatility of brazilian asset returns: a realized variance approach |
title_sort |
Modelling and forecasting the volatility of brazilian asset returns: a realized variance approach |
author |
Medeiros, Marcelo C. |
author_facet |
Medeiros, Marcelo C. |
author_role |
author |
dc.contributor.unidadefgv.por.fl_str_mv |
Escolas::EPGE |
dc.contributor.affiliation.none.fl_str_mv |
FGV |
dc.contributor.author.fl_str_mv |
Medeiros, Marcelo C. |
dc.subject.eng.fl_str_mv |
High frequency data Risk analysis Volatility forecasting GARCH models Realized volatility |
topic |
High frequency data Risk analysis Volatility forecasting GARCH models Realized volatility Economia Mercado financeiro Risco (Economia) |
dc.subject.area.por.fl_str_mv |
Economia |
dc.subject.bibliodata.por.fl_str_mv |
Mercado financeiro Risco (Economia) |
description |
The goal of this paper is twofold. First, using five of the most actively traded stocks in the Brazilian financial market, this paper shows that the normality assumption commonly used in the risk management area to describe the distributions of returns standardized by volatilities is not compatible with volatilities estimated by EWMA or GARCH models. In sharp contrast, when the information contained in high frequency data is used to construct the realized volatilies measures, we attain the normality of the standardized returns, giving promise of improvements in Value at Risk statistics. We also describe the distributions of volatilities of the Brazilian stocks, showing that the distributions of volatilities are nearly lognormal. Second, we estimate a simple linear model to the log of realized volatilities that differs from the ones in other studies. The main difference is that we do not find evidence of long memory. The estimated model is compared with commonly used alternatives in an out-of-sample experiment. |
publishDate |
2004 |
dc.date.issued.fl_str_mv |
2004-06-03 |
dc.date.accessioned.fl_str_mv |
2014-11-24T13:24:14Z |
dc.date.available.fl_str_mv |
2014-11-24T13:24:14Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
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article |
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http://hdl.handle.net/10438/12567 |
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http://hdl.handle.net/10438/12567 |
dc.language.iso.fl_str_mv |
por |
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por |
dc.relation.ispartofseries.por.fl_str_mv |
Seminários de pesquisa econômica da EPGE |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Escola de Pós-Graduação em Economia da FGV |
publisher.none.fl_str_mv |
Escola de Pós-Graduação em Economia da FGV |
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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