High quantiles estimation with Quasi-PORT and DPOT:an application to value-at-risk for financial variables
Autor(a) principal: | |
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Data de Publicação: | 2013 |
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/10400.15/2978 |
Resumo: | Recurrent “black swans” financial events are a major concern for both investors and regulators because of the extreme price changes they cause, despite their very low probability of occurrence. In this paper, we use unconditional and conditional methods, such as the recently proposed high quantile (HQ) extreme value theory (EVT) models of DPOT (Duration-based Peak Over Threshold) and quasi-PORT (peaks over random threshold), to estimate the Value-at-Risk with very small probability values for an adequately long and major financial time series to obtain a reasonable number of violations for backtesting. We also compare these models and other alternative strategies through an out-of-sample accuracy investigation to determine their relative performance within the HQ context. Policy implications relevant to estimation of risk for extreme events are also provided. |
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High quantiles estimation with Quasi-PORT and DPOT:an application to value-at-risk for financial variablesFinancial time seriesHigh quantilesQuantitative risk managementStatistics of extremesRecurrent “black swans” financial events are a major concern for both investors and regulators because of the extreme price changes they cause, despite their very low probability of occurrence. In this paper, we use unconditional and conditional methods, such as the recently proposed high quantile (HQ) extreme value theory (EVT) models of DPOT (Duration-based Peak Over Threshold) and quasi-PORT (peaks over random threshold), to estimate the Value-at-Risk with very small probability values for an adequately long and major financial time series to obtain a reasonable number of violations for backtesting. We also compare these models and other alternative strategies through an out-of-sample accuracy investigation to determine their relative performance within the HQ context. Policy implications relevant to estimation of risk for extreme events are also provided.ElsevierRepositório Científico do Instituto Politécnico de SantarémSantos, Paulo AraújoAlves, Isabel FragaHammoudeh, Shawkat2020-07-10T14:06:02Z20132013-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.15/2978engSantos, P. A., Alves, I. F., & Hammoudeh, S. (2013). High quantiles estimation with Quasi-PORT and DPOT : an application to value-at-risk for financial variables. North American Journal of Economics & Finance, 26, 487–496. doi: 10.1016/j.najef.2013.02.0171062-940810.1016/j.najef.2013.02.017metadata only accessinfo: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:RCAAP2024-01-21T07:34:25Zoai:repositorio.ipsantarem.pt:10400.15/2978Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:54:50.942738Repositório 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 |
High quantiles estimation with Quasi-PORT and DPOT:an application to value-at-risk for financial variables |
title |
High quantiles estimation with Quasi-PORT and DPOT:an application to value-at-risk for financial variables |
spellingShingle |
High quantiles estimation with Quasi-PORT and DPOT:an application to value-at-risk for financial variables Santos, Paulo Araújo Financial time series High quantiles Quantitative risk management Statistics of extremes |
title_short |
High quantiles estimation with Quasi-PORT and DPOT:an application to value-at-risk for financial variables |
title_full |
High quantiles estimation with Quasi-PORT and DPOT:an application to value-at-risk for financial variables |
title_fullStr |
High quantiles estimation with Quasi-PORT and DPOT:an application to value-at-risk for financial variables |
title_full_unstemmed |
High quantiles estimation with Quasi-PORT and DPOT:an application to value-at-risk for financial variables |
title_sort |
High quantiles estimation with Quasi-PORT and DPOT:an application to value-at-risk for financial variables |
author |
Santos, Paulo Araújo |
author_facet |
Santos, Paulo Araújo Alves, Isabel Fraga Hammoudeh, Shawkat |
author_role |
author |
author2 |
Alves, Isabel Fraga Hammoudeh, Shawkat |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Repositório Científico do Instituto Politécnico de Santarém |
dc.contributor.author.fl_str_mv |
Santos, Paulo Araújo Alves, Isabel Fraga Hammoudeh, Shawkat |
dc.subject.por.fl_str_mv |
Financial time series High quantiles Quantitative risk management Statistics of extremes |
topic |
Financial time series High quantiles Quantitative risk management Statistics of extremes |
description |
Recurrent “black swans” financial events are a major concern for both investors and regulators because of the extreme price changes they cause, despite their very low probability of occurrence. In this paper, we use unconditional and conditional methods, such as the recently proposed high quantile (HQ) extreme value theory (EVT) models of DPOT (Duration-based Peak Over Threshold) and quasi-PORT (peaks over random threshold), to estimate the Value-at-Risk with very small probability values for an adequately long and major financial time series to obtain a reasonable number of violations for backtesting. We also compare these models and other alternative strategies through an out-of-sample accuracy investigation to determine their relative performance within the HQ context. Policy implications relevant to estimation of risk for extreme events are also provided. |
publishDate |
2013 |
dc.date.none.fl_str_mv |
2013 2013-01-01T00:00:00Z 2020-07-10T14:06:02Z |
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/10400.15/2978 |
url |
http://hdl.handle.net/10400.15/2978 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Santos, P. A., Alves, I. F., & Hammoudeh, S. (2013). High quantiles estimation with Quasi-PORT and DPOT : an application to value-at-risk for financial variables. North American Journal of Economics & Finance, 26, 487–496. doi: 10.1016/j.najef.2013.02.017 1062-9408 10.1016/j.najef.2013.02.017 |
dc.rights.driver.fl_str_mv |
metadata only access info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
metadata only access |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
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 |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799137038280163328 |