Smooth Transition Regression models: Theory and Applications in JMulti

This tutorial aims to analyze nonlinear models of Smooth Transition Regression with JMulTi and contribute to the understanding of STR specification, from the estimation until the evaluation cycle of these models. It provides pedagogical explanations, combining theoretical concepts and empirical resu...

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Detalles Bibliográficos
Autores: Menezes, Rui, Ferreira, Nuno, Souza, Adriano Mendonça, Souza, Francisca Mendonça
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2020
País:Brasil
Institución:Universidade Federal de Santa Maria (UFSM)
Repositorio:Revista Ciência e Natura (Online)
Idioma:inglés
OAI Identifier:oai:ojs.pkp.sfu.ca:article/40466
Acceso en línea:https://periodicos.ufsm.br/cienciaenatura/article/view/40466
Access Level:acceso abierto
Palabra clave:Smooth transition
Structural Break
Nonlinearity
Time Series
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spelling Smooth Transition Regression models: Theory and Applications in JMultiSmooth transitionStructural BreakNonlinearityTime Series This tutorial aims to analyze nonlinear models of Smooth Transition Regression with JMulTi and contribute to the understanding of STR specification, from the estimation until the evaluation cycle of these models. It provides pedagogical explanations, combining theoretical concepts and empirical results coherently. Especially in economic relationships, where an asymmetric behaviour with distinct effects is often found on contractions and expansions. As economic series generally present asymmetric/nonlinear behaviour, Smooth Transition Regression (STR) models provide a flexible empirical strategy that allows capturing the impacts of possible types of asymmetry in the data, Souza (2016).An overview of theory and applications in software is described. These nonlinear models describe in-sample movements of the stock returns series better than the corresponding linear model. The data used in this study consist of daily prices index from January 02, 1995 to March 29, 2013, a total of 4761 observations, from Germany (DAX30). The data was collected from the DataStream database considering 5 days a week. The data (price index) is converted to base 100 and the yields are then calculated based on the first differences in the log price series. 10-year interest rates treasury bond regarding the same markets identified has also been collected for the same period. Universidade Federal de Santa Maria2020-12-29info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlapplication/pdfhttps://periodicos.ufsm.br/cienciaenatura/article/view/4046610.5902/2179460X40466Ciência e Natura; Vol. 42 (2020): Edição especial de aniversário 10 ANOS - bacharelado e 30 - especialização em estatística; e18Ciência e Natura; v. 42 (2020): CIÊNCIA E NATURA: Edição Comemorativa – Estatística; e182179-460X0100-8307reponame:Revista Ciência e Natura (Online)instname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMenghttps://periodicos.ufsm.br/cienciaenatura/article/view/40466/htmlhttps://periodicos.ufsm.br/cienciaenatura/article/view/40466/pdfCopyright (c) 2020 Ciência e Naturainfo:eu-repo/semantics/openAccessMenezes, RuiFerreira, NunoSouza, Adriano MendonçaSouza, Francisca Mendonça2021-02-10T04:54:57Zoai:ojs.pkp.sfu.ca:article/40466Revistahttps://periodicos.ufsm.br/cienciaenatura/indexPUBhttps://periodicos.ufsm.br/cienciaenatura/oaicienciaenatura@ufsm.br || centraldeperiodicos@ufsm.br2179-460X0100-8307opendoar:2021-02-10T04:54:57Revista Ciência e Natura (Online) - Universidade Federal de Santa Maria (UFSM)false
dc.title.none.fl_str_mv Smooth Transition Regression models: Theory and Applications in JMulti
title Smooth Transition Regression models: Theory and Applications in JMulti
spellingShingle Smooth Transition Regression models: Theory and Applications in JMulti
Menezes, Rui
Smooth transition
Structural Break
Nonlinearity
Time Series
title_short Smooth Transition Regression models: Theory and Applications in JMulti
title_full Smooth Transition Regression models: Theory and Applications in JMulti
title_fullStr Smooth Transition Regression models: Theory and Applications in JMulti
title_full_unstemmed Smooth Transition Regression models: Theory and Applications in JMulti
title_sort Smooth Transition Regression models: Theory and Applications in JMulti
dc.creator.none.fl_str_mv Menezes, Rui
Ferreira, Nuno
Souza, Adriano Mendonça
Souza, Francisca Mendonça
author Menezes, Rui
author_facet Menezes, Rui
Ferreira, Nuno
Souza, Adriano Mendonça
Souza, Francisca Mendonça
author_role author
author2 Ferreira, Nuno
Souza, Adriano Mendonça
Souza, Francisca Mendonça
author2_role author
author
author
dc.subject.por.fl_str_mv Smooth transition
Structural Break
Nonlinearity
Time Series
topic Smooth transition
Structural Break
Nonlinearity
Time Series
description This tutorial aims to analyze nonlinear models of Smooth Transition Regression with JMulTi and contribute to the understanding of STR specification, from the estimation until the evaluation cycle of these models. It provides pedagogical explanations, combining theoretical concepts and empirical results coherently. Especially in economic relationships, where an asymmetric behaviour with distinct effects is often found on contractions and expansions. As economic series generally present asymmetric/nonlinear behaviour, Smooth Transition Regression (STR) models provide a flexible empirical strategy that allows capturing the impacts of possible types of asymmetry in the data, Souza (2016).An overview of theory and applications in software is described. These nonlinear models describe in-sample movements of the stock returns series better than the corresponding linear model. The data used in this study consist of daily prices index from January 02, 1995 to March 29, 2013, a total of 4761 observations, from Germany (DAX30). The data was collected from the DataStream database considering 5 days a week. The data (price index) is converted to base 100 and the yields are then calculated based on the first differences in the log price series. 10-year interest rates treasury bond regarding the same markets identified has also been collected for the same period.
publishDate 2020
dc.date.none.fl_str_mv 2020-12-29
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://periodicos.ufsm.br/cienciaenatura/article/view/40466
10.5902/2179460X40466
url https://periodicos.ufsm.br/cienciaenatura/article/view/40466
identifier_str_mv 10.5902/2179460X40466
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://periodicos.ufsm.br/cienciaenatura/article/view/40466/html
https://periodicos.ufsm.br/cienciaenatura/article/view/40466/pdf
dc.rights.driver.fl_str_mv Copyright (c) 2020 Ciência e Natura
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2020 Ciência e Natura
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Santa Maria
publisher.none.fl_str_mv Universidade Federal de Santa Maria
dc.source.none.fl_str_mv Ciência e Natura; Vol. 42 (2020): Edição especial de aniversário 10 ANOS - bacharelado e 30 - especialização em estatística; e18
Ciência e Natura; v. 42 (2020): CIÊNCIA E NATURA: Edição Comemorativa – Estatística; e18
2179-460X
0100-8307
reponame:Revista Ciência e Natura (Online)
instname:Universidade Federal de Santa Maria (UFSM)
instacron:UFSM
instname_str Universidade Federal de Santa Maria (UFSM)
instacron_str UFSM
institution UFSM
reponame_str Revista Ciência e Natura (Online)
collection Revista Ciência e Natura (Online)
repository.name.fl_str_mv Revista Ciência e Natura (Online) - Universidade Federal de Santa Maria (UFSM)
repository.mail.fl_str_mv cienciaenatura@ufsm.br || centraldeperiodicos@ufsm.br
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score 15,300724

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