Modelling stock returns with AR-GARCH processes

Financial returns are often modelled as autoregressive time series with random disturbances having conditional heteroscedastic variances, especially with GARCH type processes. GARCH processes have been intensely studying in financial and econometric literature as risk models of many financial time s...

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Detalles Bibliográficos
Autores: Ferenstein, Elzbieta, Gasowski, Miroslaw
Tipo de recurso: artículo
Fecha de publicación:2004
País:España
Institución:Universitat Autònoma de Barcelona
Repositorio:Dipòsit Digital de Documents de la UAB
Idioma:inglés
OAI Identifier:oai:ddd.uab.cat:93938
Acceso en línea:https://ddd.uab.cat/record/93938
Access Level:acceso abierto
Palabra clave:Autoregressive process
GARCH and EGARCH models
Conditional heteroscedastic variance
Financial log returns
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spelling Modelling stock returns with AR-GARCH processesFerenstein, ElzbietaGasowski, MiroslawAutoregressive processGARCH and EGARCH modelsConditional heteroscedastic varianceFinancial log returnsFinancial returns are often modelled as autoregressive time series with random disturbances having conditional heteroscedastic variances, especially with GARCH type processes. GARCH processes have been intensely studying in financial and econometric literature as risk models of many financial time series. Analyzing two data sets of stock prices we try to fit AR(1) processes with GARCH or EGARCH errors to the log returns. Moreover, hyperbolic or generalized error distributions occur to be good models of white noise distributions. 22004-01-0120042004-01-01Articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://ddd.uab.cat/record/93938reponame:Dipòsit Digital de Documents de la UABinstname:Universitat Autònoma de BarcelonaInglésengopen accesshttp://purl.org/coar/access_right/c_abf2Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.https://creativecommons.org/licenses/by-nc-nd/3.0/info:eu-repo/semantics/openAccessoai:ddd.uab.cat:939382026-06-06T12:50:31Z
dc.title.none.fl_str_mv Modelling stock returns with AR-GARCH processes
title Modelling stock returns with AR-GARCH processes
spellingShingle Modelling stock returns with AR-GARCH processes
Ferenstein, Elzbieta
Autoregressive process
GARCH and EGARCH models
Conditional heteroscedastic variance
Financial log returns
title_short Modelling stock returns with AR-GARCH processes
title_full Modelling stock returns with AR-GARCH processes
title_fullStr Modelling stock returns with AR-GARCH processes
title_full_unstemmed Modelling stock returns with AR-GARCH processes
title_sort Modelling stock returns with AR-GARCH processes
dc.creator.none.fl_str_mv Ferenstein, Elzbieta
Gasowski, Miroslaw
author Ferenstein, Elzbieta
author_facet Ferenstein, Elzbieta
Gasowski, Miroslaw
author_role author
author2 Gasowski, Miroslaw
author2_role author
dc.subject.none.fl_str_mv Autoregressive process
GARCH and EGARCH models
Conditional heteroscedastic variance
Financial log returns
topic Autoregressive process
GARCH and EGARCH models
Conditional heteroscedastic variance
Financial log returns
description Financial returns are often modelled as autoregressive time series with random disturbances having conditional heteroscedastic variances, especially with GARCH type processes. GARCH processes have been intensely studying in financial and econometric literature as risk models of many financial time series. Analyzing two data sets of stock prices we try to fit AR(1) processes with GARCH or EGARCH errors to the log returns. Moreover, hyperbolic or generalized error distributions occur to be good models of white noise distributions.
publishDate 2004
dc.date.none.fl_str_mv 2
2004-01-01
2004
2004-01-01
dc.type.none.fl_str_mv Article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://ddd.uab.cat/record/93938
url https://ddd.uab.cat/record/93938
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
https://creativecommons.org/licenses/by-nc-nd/3.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
https://creativecommons.org/licenses/by-nc-nd/3.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Dipòsit Digital de Documents de la UAB
instname:Universitat Autònoma de Barcelona
instname_str Universitat Autònoma de Barcelona
reponame_str Dipòsit Digital de Documents de la UAB
collection Dipòsit Digital de Documents de la UAB
repository.name.fl_str_mv
repository.mail.fl_str_mv
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