THE LEVERAGE EFFECT AND THE ASYMMETRY OF THE ERROR DISTRIBUTION IN GARCH-BASED MODELS: THE CASE OF BRAZILIAN MARKET RELATED SERIES

Detalhes bibliográficos
Autor(a) principal: Almeida,Daniel de
Data de Publicação: 2014
Outros Autores: Hotta,Luiz K.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Pesquisa operacional (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382014000200237
Resumo: Traditional GARCH models fail to explain at least two of the stylized facts found in financial series: the asymmetry of the distribution of errors and the leverage effect. The leverage effect stems from the fact that losses have a greater influence on future volatilities than do gains. Asymmetry means that the distribution of losses has a heavier tail than the distribution of gains. We test whether these features are present in some series related to the Brazilian market. To test for the presence of these features, the series were fitted by GARCH(1,1), TGARCH(1,1), EGARCH(1,1), and GJR-GARCH(1,1) models with standardized Student t distribution errors with and without asymmetry. Information criteria and statistical tests of the significance of the symmetry and leverage parameters are used to compare the models. The estimates of the VaR (value-at-risk) are also used in the comparison. The conclusion is that both stylized facts are present in some series, mostly simultaneously.
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spelling THE LEVERAGE EFFECT AND THE ASYMMETRY OF THE ERROR DISTRIBUTION IN GARCH-BASED MODELS: THE CASE OF BRAZILIAN MARKET RELATED SERIESasymmetry in volatility modelsasymmetric Garch family modelsVaR (Value-at-Risk)Traditional GARCH models fail to explain at least two of the stylized facts found in financial series: the asymmetry of the distribution of errors and the leverage effect. The leverage effect stems from the fact that losses have a greater influence on future volatilities than do gains. Asymmetry means that the distribution of losses has a heavier tail than the distribution of gains. We test whether these features are present in some series related to the Brazilian market. To test for the presence of these features, the series were fitted by GARCH(1,1), TGARCH(1,1), EGARCH(1,1), and GJR-GARCH(1,1) models with standardized Student t distribution errors with and without asymmetry. Information criteria and statistical tests of the significance of the symmetry and leverage parameters are used to compare the models. The estimates of the VaR (value-at-risk) are also used in the comparison. The conclusion is that both stylized facts are present in some series, mostly simultaneously.Sociedade Brasileira de Pesquisa Operacional2014-08-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382014000200237Pesquisa Operacional v.34 n.2 2014reponame:Pesquisa operacional (Online)instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)instacron:SOBRAPO10.1590/0101-7438.2014.034.02.0237info:eu-repo/semantics/openAccessAlmeida,Daniel deHotta,Luiz K.eng2015-10-09T00:00:00Zoai:scielo:S0101-74382014000200237Revistahttp://www.scielo.br/popehttps://old.scielo.br/oai/scielo-oai.php||sobrapo@sobrapo.org.br1678-51420101-7438opendoar:2015-10-09T00:00Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)false
dc.title.none.fl_str_mv THE LEVERAGE EFFECT AND THE ASYMMETRY OF THE ERROR DISTRIBUTION IN GARCH-BASED MODELS: THE CASE OF BRAZILIAN MARKET RELATED SERIES
title THE LEVERAGE EFFECT AND THE ASYMMETRY OF THE ERROR DISTRIBUTION IN GARCH-BASED MODELS: THE CASE OF BRAZILIAN MARKET RELATED SERIES
spellingShingle THE LEVERAGE EFFECT AND THE ASYMMETRY OF THE ERROR DISTRIBUTION IN GARCH-BASED MODELS: THE CASE OF BRAZILIAN MARKET RELATED SERIES
Almeida,Daniel de
asymmetry in volatility models
asymmetric Garch family models
VaR (Value-at-Risk)
title_short THE LEVERAGE EFFECT AND THE ASYMMETRY OF THE ERROR DISTRIBUTION IN GARCH-BASED MODELS: THE CASE OF BRAZILIAN MARKET RELATED SERIES
title_full THE LEVERAGE EFFECT AND THE ASYMMETRY OF THE ERROR DISTRIBUTION IN GARCH-BASED MODELS: THE CASE OF BRAZILIAN MARKET RELATED SERIES
title_fullStr THE LEVERAGE EFFECT AND THE ASYMMETRY OF THE ERROR DISTRIBUTION IN GARCH-BASED MODELS: THE CASE OF BRAZILIAN MARKET RELATED SERIES
title_full_unstemmed THE LEVERAGE EFFECT AND THE ASYMMETRY OF THE ERROR DISTRIBUTION IN GARCH-BASED MODELS: THE CASE OF BRAZILIAN MARKET RELATED SERIES
title_sort THE LEVERAGE EFFECT AND THE ASYMMETRY OF THE ERROR DISTRIBUTION IN GARCH-BASED MODELS: THE CASE OF BRAZILIAN MARKET RELATED SERIES
author Almeida,Daniel de
author_facet Almeida,Daniel de
Hotta,Luiz K.
author_role author
author2 Hotta,Luiz K.
author2_role author
dc.contributor.author.fl_str_mv Almeida,Daniel de
Hotta,Luiz K.
dc.subject.por.fl_str_mv asymmetry in volatility models
asymmetric Garch family models
VaR (Value-at-Risk)
topic asymmetry in volatility models
asymmetric Garch family models
VaR (Value-at-Risk)
description Traditional GARCH models fail to explain at least two of the stylized facts found in financial series: the asymmetry of the distribution of errors and the leverage effect. The leverage effect stems from the fact that losses have a greater influence on future volatilities than do gains. Asymmetry means that the distribution of losses has a heavier tail than the distribution of gains. We test whether these features are present in some series related to the Brazilian market. To test for the presence of these features, the series were fitted by GARCH(1,1), TGARCH(1,1), EGARCH(1,1), and GJR-GARCH(1,1) models with standardized Student t distribution errors with and without asymmetry. Information criteria and statistical tests of the significance of the symmetry and leverage parameters are used to compare the models. The estimates of the VaR (value-at-risk) are also used in the comparison. The conclusion is that both stylized facts are present in some series, mostly simultaneously.
publishDate 2014
dc.date.none.fl_str_mv 2014-08-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382014000200237
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382014000200237
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0101-7438.2014.034.02.0237
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Pesquisa Operacional
publisher.none.fl_str_mv Sociedade Brasileira de Pesquisa Operacional
dc.source.none.fl_str_mv Pesquisa Operacional v.34 n.2 2014
reponame:Pesquisa operacional (Online)
instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
instacron:SOBRAPO
instname_str Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
instacron_str SOBRAPO
institution SOBRAPO
reponame_str Pesquisa operacional (Online)
collection Pesquisa operacional (Online)
repository.name.fl_str_mv Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
repository.mail.fl_str_mv ||sobrapo@sobrapo.org.br
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