Optimal alarm systems for FIAPARCH processes

Detalhes bibliográficos
Autor(a) principal: Costa, C
Data de Publicação: 2010
Outros Autores: Scotto, MG, Pereira, I
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10773/4425
Resumo: In this work, an optimal alarm system is developed to predict whether a financial time series modeled via Fractionally Integrated Asymmetric Power ARCH (FIAPARCH) models, up/downcrosses some particular level and give an alarm whenever this crossing is predicted. The paper presents classical and Bayesian methodology for producing optimal alarm systems. Both methodologies are illustrated and their performance compared through a simulation study. The work finishes with an empirical application to a set of data concerning daily returns of the Sao Paulo Stock Market.
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spelling Optimal alarm systems for FIAPARCH processesFIAPARCH processesOptimal alarm systemsEconometricsIn this work, an optimal alarm system is developed to predict whether a financial time series modeled via Fractionally Integrated Asymmetric Power ARCH (FIAPARCH) models, up/downcrosses some particular level and give an alarm whenever this crossing is predicted. The paper presents classical and Bayesian methodology for producing optimal alarm systems. Both methodologies are illustrated and their performance compared through a simulation study. The work finishes with an empirical application to a set of data concerning daily returns of the Sao Paulo Stock Market.Instituto Nacional de Estatística2011-11-28T12:30:28Z2010-01-01T00:00:00Z2010info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10773/4425eng1645-6726Costa, CScotto, MGPereira, Iinfo: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:RCAAP2024-05-06T03:33:42Zoai:ria.ua.pt:10773/4425Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-05-06T03:33:42Repositório 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 Optimal alarm systems for FIAPARCH processes
title Optimal alarm systems for FIAPARCH processes
spellingShingle Optimal alarm systems for FIAPARCH processes
Costa, C
FIAPARCH processes
Optimal alarm systems
Econometrics
title_short Optimal alarm systems for FIAPARCH processes
title_full Optimal alarm systems for FIAPARCH processes
title_fullStr Optimal alarm systems for FIAPARCH processes
title_full_unstemmed Optimal alarm systems for FIAPARCH processes
title_sort Optimal alarm systems for FIAPARCH processes
author Costa, C
author_facet Costa, C
Scotto, MG
Pereira, I
author_role author
author2 Scotto, MG
Pereira, I
author2_role author
author
dc.contributor.author.fl_str_mv Costa, C
Scotto, MG
Pereira, I
dc.subject.por.fl_str_mv FIAPARCH processes
Optimal alarm systems
Econometrics
topic FIAPARCH processes
Optimal alarm systems
Econometrics
description In this work, an optimal alarm system is developed to predict whether a financial time series modeled via Fractionally Integrated Asymmetric Power ARCH (FIAPARCH) models, up/downcrosses some particular level and give an alarm whenever this crossing is predicted. The paper presents classical and Bayesian methodology for producing optimal alarm systems. Both methodologies are illustrated and their performance compared through a simulation study. The work finishes with an empirical application to a set of data concerning daily returns of the Sao Paulo Stock Market.
publishDate 2010
dc.date.none.fl_str_mv 2010-01-01T00:00:00Z
2010
2011-11-28T12:30:28Z
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/10773/4425
url http://hdl.handle.net/10773/4425
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1645-6726
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 Instituto Nacional de Estatística
publisher.none.fl_str_mv Instituto Nacional de Estatística
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 mluisa.alvim@gmail.com
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