Modelling and forecasting the volatility of brazilian asset returns: a realized variance approach

Detalhes bibliográficos
Autor(a) principal: Medeiros, Marcelo C.
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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spelling 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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dc.relation.ispartofseries.por.fl_str_mv Seminários de pesquisa econômica da EPGE
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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
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