Forecasting output growth tail risk using quantile regression framework

Detalhes bibliográficos
Autor(a) principal: Quattrini, Filippo
Data de Publicação: 2022
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/156104
Resumo: This thesis examines which financial indicator is the most accurate to model and predict the tail risk of output growth in the euro area. The CISS is more informative than other indicators that only focus on specific segment of the financial market. To capture the tail distribution information, the thesis implements quantile regression, capturing determined quantile of the output growth distribution. The forecast produced with the quantile regression for the 10th and the 5th quantile outperformed the standard OLS model in terms of forecasting evaluation metrics in predicting the 2008 output growth downfall, concluding that the quantile specification, combined with the CISS as financial indicator, improves the modeling and forecasting accuracy of tail risk output growth in the euro area.
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spelling Forecasting output growth tail risk using quantile regression frameworkQuantile regressionGrowth at riskMacro-financial linkagesTime seriesDomínio/Área Científica::Ciências Sociais::Economia e GestãoThis thesis examines which financial indicator is the most accurate to model and predict the tail risk of output growth in the euro area. The CISS is more informative than other indicators that only focus on specific segment of the financial market. To capture the tail distribution information, the thesis implements quantile regression, capturing determined quantile of the output growth distribution. The forecast produced with the quantile regression for the 10th and the 5th quantile outperformed the standard OLS model in terms of forecasting evaluation metrics in predicting the 2008 output growth downfall, concluding that the quantile specification, combined with the CISS as financial indicator, improves the modeling and forecasting accuracy of tail risk output growth in the euro area.Rodrigues, Paulo Manuel MarquesRUNQuattrini, Filippo2023-08-01T13:44:12Z2023-01-132022-12-162023-01-13T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/156104TID:203311051enginfo: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:RCAAP2024-05-22T18:13:32Zoai:run.unl.pt:10362/156104Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-05-22T18:13:32Repositório 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 Forecasting output growth tail risk using quantile regression framework
title Forecasting output growth tail risk using quantile regression framework
spellingShingle Forecasting output growth tail risk using quantile regression framework
Quattrini, Filippo
Quantile regression
Growth at risk
Macro-financial linkages
Time series
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
title_short Forecasting output growth tail risk using quantile regression framework
title_full Forecasting output growth tail risk using quantile regression framework
title_fullStr Forecasting output growth tail risk using quantile regression framework
title_full_unstemmed Forecasting output growth tail risk using quantile regression framework
title_sort Forecasting output growth tail risk using quantile regression framework
author Quattrini, Filippo
author_facet Quattrini, Filippo
author_role author
dc.contributor.none.fl_str_mv Rodrigues, Paulo Manuel Marques
RUN
dc.contributor.author.fl_str_mv Quattrini, Filippo
dc.subject.por.fl_str_mv Quantile regression
Growth at risk
Macro-financial linkages
Time series
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
topic Quantile regression
Growth at risk
Macro-financial linkages
Time series
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
description This thesis examines which financial indicator is the most accurate to model and predict the tail risk of output growth in the euro area. The CISS is more informative than other indicators that only focus on specific segment of the financial market. To capture the tail distribution information, the thesis implements quantile regression, capturing determined quantile of the output growth distribution. The forecast produced with the quantile regression for the 10th and the 5th quantile outperformed the standard OLS model in terms of forecasting evaluation metrics in predicting the 2008 output growth downfall, concluding that the quantile specification, combined with the CISS as financial indicator, improves the modeling and forecasting accuracy of tail risk output growth in the euro area.
publishDate 2022
dc.date.none.fl_str_mv 2022-12-16
2023-08-01T13:44:12Z
2023-01-13
2023-01-13T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/156104
TID:203311051
url http://hdl.handle.net/10362/156104
identifier_str_mv TID:203311051
dc.language.iso.fl_str_mv eng
language eng
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.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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