Modeling stock markets' volatility using GARCH models with normal, student's t and stable paretian distributions
Autor(a) principal: | |
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Data de Publicação: | 2009 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10071/5541 |
Resumo: | As GARCH models and stable Paretian distributions have been revisited in the recent past with the papers of Hansen and Lunde (J Appl Econom 20: 873–889, 2005) and Bidarkota and McCulloch (Quant Finance 4: 256–265, 2004), respectively, in this paper we discuss alternative conditional distributional models for the daily returns of the US, German and Portuguese main stock market indexes, considering ARMA-GARCH models driven by Normal, Student’s t and stable Paretian distributed innovations. We find that a GARCH model with stable Paretian innovations fits returns clearly better than the more popular Normal distribution and slightly better than the Student’s t distribution. However, the Student’s t outperforms the Normal and stable Paretian distributions when the out-of-sample density forecasts are considered. |
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Modeling stock markets' volatility using GARCH models with normal, student's t and stable paretian distributionsNon-Gaussian distributionsConditional heteroskedasticityAs GARCH models and stable Paretian distributions have been revisited in the recent past with the papers of Hansen and Lunde (J Appl Econom 20: 873–889, 2005) and Bidarkota and McCulloch (Quant Finance 4: 256–265, 2004), respectively, in this paper we discuss alternative conditional distributional models for the daily returns of the US, German and Portuguese main stock market indexes, considering ARMA-GARCH models driven by Normal, Student’s t and stable Paretian distributed innovations. We find that a GARCH model with stable Paretian innovations fits returns clearly better than the more popular Normal distribution and slightly better than the Student’s t distribution. However, the Student’s t outperforms the Normal and stable Paretian distributions when the out-of-sample density forecasts are considered.Springer2013-09-06T14:49:50Z2009-01-01T00:00:00Z20092019-03-26T16:30:47Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/5541eng0932-502610.1007/s00362-007-0080-5Curto, J.Pinto, J. C.Tavares, G. N.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-09T17:47:43Zoai:repositorio.iscte-iul.pt:10071/5541Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:23:11.454830Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Modeling stock markets' volatility using GARCH models with normal, student's t and stable paretian distributions |
title |
Modeling stock markets' volatility using GARCH models with normal, student's t and stable paretian distributions |
spellingShingle |
Modeling stock markets' volatility using GARCH models with normal, student's t and stable paretian distributions Curto, J. Non-Gaussian distributions Conditional heteroskedasticity |
title_short |
Modeling stock markets' volatility using GARCH models with normal, student's t and stable paretian distributions |
title_full |
Modeling stock markets' volatility using GARCH models with normal, student's t and stable paretian distributions |
title_fullStr |
Modeling stock markets' volatility using GARCH models with normal, student's t and stable paretian distributions |
title_full_unstemmed |
Modeling stock markets' volatility using GARCH models with normal, student's t and stable paretian distributions |
title_sort |
Modeling stock markets' volatility using GARCH models with normal, student's t and stable paretian distributions |
author |
Curto, J. |
author_facet |
Curto, J. Pinto, J. C. Tavares, G. N. |
author_role |
author |
author2 |
Pinto, J. C. Tavares, G. N. |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Curto, J. Pinto, J. C. Tavares, G. N. |
dc.subject.por.fl_str_mv |
Non-Gaussian distributions Conditional heteroskedasticity |
topic |
Non-Gaussian distributions Conditional heteroskedasticity |
description |
As GARCH models and stable Paretian distributions have been revisited in the recent past with the papers of Hansen and Lunde (J Appl Econom 20: 873–889, 2005) and Bidarkota and McCulloch (Quant Finance 4: 256–265, 2004), respectively, in this paper we discuss alternative conditional distributional models for the daily returns of the US, German and Portuguese main stock market indexes, considering ARMA-GARCH models driven by Normal, Student’s t and stable Paretian distributed innovations. We find that a GARCH model with stable Paretian innovations fits returns clearly better than the more popular Normal distribution and slightly better than the Student’s t distribution. However, the Student’s t outperforms the Normal and stable Paretian distributions when the out-of-sample density forecasts are considered. |
publishDate |
2009 |
dc.date.none.fl_str_mv |
2009-01-01T00:00:00Z 2009 2013-09-06T14:49:50Z 2019-03-26T16:30:47Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10071/5541 |
url |
http://hdl.handle.net/10071/5541 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0932-5026 10.1007/s00362-007-0080-5 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Springer |
publisher.none.fl_str_mv |
Springer |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799134793654337536 |