Downside risk management and VaR-based optimal portfolios for precious metals, oil and stocks

Detalhes bibliográficos
Autor(a) principal: Hammoudeh, Shawkat
Data de Publicação: 2013
Outros Autores: Araújo Santos, Paulo, Al-Hassan, Abdullah
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.15/2981
Resumo: Value-at-Risk (VaR) is used to analyze the market downside risk associated with investments in six key individual assets including four precious metals, oil and the S&P 500 index, and three diversified portfolios. Using combinations of these assets, three optimal portfolios and their efficient frontiers within a VaR framework are constructed and the returns and downside risks for these portfolios are also analyzed. One-day-ahead VaR forecasts are computed with nine risk models including calibrated RiskMetrics, asymmetric GARCH type models, the filtered Historical Simulation approach, methodologies from statistics of extremes and a risk management strategy involving combinations of models. These risk models are evaluated and compared based on the unconditional coverage, independence and conditional coverage criteria. The economic importance of the results is also highlighted by assessing the daily capital charges under the Basel Accord rule. The best approaches for estimating the VaR for the individual assets under study and for the three VaR-based optimal portfolios and efficient frontiers are discussed. The VaR-based performance measure ranks the most diversified optimal portfolio (Portfolio #2) as the most efficient and the pure precious metals.
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spelling Downside risk management and VaR-based optimal portfolios for precious metals, oil and stocksEfficient frontiersKey assetsOptimal portfoliosRisk managementValue-at-RiskValue-at-Risk (VaR) is used to analyze the market downside risk associated with investments in six key individual assets including four precious metals, oil and the S&P 500 index, and three diversified portfolios. Using combinations of these assets, three optimal portfolios and their efficient frontiers within a VaR framework are constructed and the returns and downside risks for these portfolios are also analyzed. One-day-ahead VaR forecasts are computed with nine risk models including calibrated RiskMetrics, asymmetric GARCH type models, the filtered Historical Simulation approach, methodologies from statistics of extremes and a risk management strategy involving combinations of models. These risk models are evaluated and compared based on the unconditional coverage, independence and conditional coverage criteria. The economic importance of the results is also highlighted by assessing the daily capital charges under the Basel Accord rule. The best approaches for estimating the VaR for the individual assets under study and for the three VaR-based optimal portfolios and efficient frontiers are discussed. The VaR-based performance measure ranks the most diversified optimal portfolio (Portfolio #2) as the most efficient and the pure precious metals.ElsevierRepositório Científico do Instituto Politécnico de SantarémHammoudeh, ShawkatAraújo Santos, PauloAl-Hassan, Abdullah2020-07-13T09:50:12Z20132013-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.15/2981engHammoudeh, S., Araújo Santos, P., & Al-Hassan, A. (2013). Downside risk management and VaR-based optimal portfolios for precious metals, oil and stocks. North American Journal of Economics & Finance, 25, 318–334. doi: 10.1016/j.najef.2012.06.0121062-940810.1016/j.najef.2012.06.012metadata 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:10400.15/2981Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:54:51.085577Repositório 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 Downside risk management and VaR-based optimal portfolios for precious metals, oil and stocks
title Downside risk management and VaR-based optimal portfolios for precious metals, oil and stocks
spellingShingle Downside risk management and VaR-based optimal portfolios for precious metals, oil and stocks
Hammoudeh, Shawkat
Efficient frontiers
Key assets
Optimal portfolios
Risk management
Value-at-Risk
title_short Downside risk management and VaR-based optimal portfolios for precious metals, oil and stocks
title_full Downside risk management and VaR-based optimal portfolios for precious metals, oil and stocks
title_fullStr Downside risk management and VaR-based optimal portfolios for precious metals, oil and stocks
title_full_unstemmed Downside risk management and VaR-based optimal portfolios for precious metals, oil and stocks
title_sort Downside risk management and VaR-based optimal portfolios for precious metals, oil and stocks
author Hammoudeh, Shawkat
author_facet Hammoudeh, Shawkat
Araújo Santos, Paulo
Al-Hassan, Abdullah
author_role author
author2 Araújo Santos, Paulo
Al-Hassan, Abdullah
author2_role author
author
dc.contributor.none.fl_str_mv Repositório Científico do Instituto Politécnico de Santarém
dc.contributor.author.fl_str_mv Hammoudeh, Shawkat
Araújo Santos, Paulo
Al-Hassan, Abdullah
dc.subject.por.fl_str_mv Efficient frontiers
Key assets
Optimal portfolios
Risk management
Value-at-Risk
topic Efficient frontiers
Key assets
Optimal portfolios
Risk management
Value-at-Risk
description Value-at-Risk (VaR) is used to analyze the market downside risk associated with investments in six key individual assets including four precious metals, oil and the S&P 500 index, and three diversified portfolios. Using combinations of these assets, three optimal portfolios and their efficient frontiers within a VaR framework are constructed and the returns and downside risks for these portfolios are also analyzed. One-day-ahead VaR forecasts are computed with nine risk models including calibrated RiskMetrics, asymmetric GARCH type models, the filtered Historical Simulation approach, methodologies from statistics of extremes and a risk management strategy involving combinations of models. These risk models are evaluated and compared based on the unconditional coverage, independence and conditional coverage criteria. The economic importance of the results is also highlighted by assessing the daily capital charges under the Basel Accord rule. The best approaches for estimating the VaR for the individual assets under study and for the three VaR-based optimal portfolios and efficient frontiers are discussed. The VaR-based performance measure ranks the most diversified optimal portfolio (Portfolio #2) as the most efficient and the pure precious metals.
publishDate 2013
dc.date.none.fl_str_mv 2013
2013-01-01T00:00:00Z
2020-07-13T09:50:12Z
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/10400.15/2981
url http://hdl.handle.net/10400.15/2981
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Hammoudeh, S., Araújo Santos, P., & Al-Hassan, A. (2013). Downside risk management and VaR-based optimal portfolios for precious metals, oil and stocks. North American Journal of Economics & Finance, 25, 318–334. doi: 10.1016/j.najef.2012.06.012
1062-9408
10.1016/j.najef.2012.06.012
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
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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)
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collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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