On the predictability of realized volatility using feasible GLS

Detalhes bibliográficos
Autor(a) principal: Bentes, S.
Data de Publicação: 2013
Outros Autores: Menezes, R.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://ciencia.iscte-iul.pt/public/pub/id/22759
http://hdl.handle.net/10071/9126
Resumo: This study deals with the out-of-sample predictability of realized volatility induced by implied volatility using FGLS. The original dataset was collected from Bloomberg and includes price and implied volatility indices from the US, Hong Kong, China, South Korea and India. Prices were then transformed into realized volatility indices. The relation between realized and implied volatility is important insofar as market expectations about future turbulence may affect the investor's behavior in advance. However, there are some features of the financial data which turn problematic the choice of the OLS estimator. These features include endogeneity and persistence of the predictor, and also conditional heteroskedasticity of the predicted innovations. Consequently, OLS becomes biased and inefficient. The FGLS estimator accounts for these characteristics and, therefore, performs better than OLS-based estimators, as indicated by many of our results.
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spelling On the predictability of realized volatility using feasible GLSFeasible GLSForecastingImplied volatilityRealized volatilityThis study deals with the out-of-sample predictability of realized volatility induced by implied volatility using FGLS. The original dataset was collected from Bloomberg and includes price and implied volatility indices from the US, Hong Kong, China, South Korea and India. Prices were then transformed into realized volatility indices. The relation between realized and implied volatility is important insofar as market expectations about future turbulence may affect the investor's behavior in advance. However, there are some features of the financial data which turn problematic the choice of the OLS estimator. These features include endogeneity and persistence of the predictor, and also conditional heteroskedasticity of the predicted innovations. Consequently, OLS becomes biased and inefficient. The FGLS estimator accounts for these characteristics and, therefore, performs better than OLS-based estimators, as indicated by many of our results.Elsevier2015-06-26T17:04:22Z2013-01-01T00:00:00Z20132015-06-26T17:03:26Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://ciencia.iscte-iul.pt/public/pub/id/22759http://hdl.handle.net/10071/9126eng1049-0078Bentes, S.Menezes, R.info:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-09T17:37:45Zoai:repositorio.iscte-iul.pt:10071/9126Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:17:14.471247Repositório 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 On the predictability of realized volatility using feasible GLS
title On the predictability of realized volatility using feasible GLS
spellingShingle On the predictability of realized volatility using feasible GLS
Bentes, S.
Feasible GLS
Forecasting
Implied volatility
Realized volatility
title_short On the predictability of realized volatility using feasible GLS
title_full On the predictability of realized volatility using feasible GLS
title_fullStr On the predictability of realized volatility using feasible GLS
title_full_unstemmed On the predictability of realized volatility using feasible GLS
title_sort On the predictability of realized volatility using feasible GLS
author Bentes, S.
author_facet Bentes, S.
Menezes, R.
author_role author
author2 Menezes, R.
author2_role author
dc.contributor.author.fl_str_mv Bentes, S.
Menezes, R.
dc.subject.por.fl_str_mv Feasible GLS
Forecasting
Implied volatility
Realized volatility
topic Feasible GLS
Forecasting
Implied volatility
Realized volatility
description This study deals with the out-of-sample predictability of realized volatility induced by implied volatility using FGLS. The original dataset was collected from Bloomberg and includes price and implied volatility indices from the US, Hong Kong, China, South Korea and India. Prices were then transformed into realized volatility indices. The relation between realized and implied volatility is important insofar as market expectations about future turbulence may affect the investor's behavior in advance. However, there are some features of the financial data which turn problematic the choice of the OLS estimator. These features include endogeneity and persistence of the predictor, and also conditional heteroskedasticity of the predicted innovations. Consequently, OLS becomes biased and inefficient. The FGLS estimator accounts for these characteristics and, therefore, performs better than OLS-based estimators, as indicated by many of our results.
publishDate 2013
dc.date.none.fl_str_mv 2013-01-01T00:00:00Z
2013
2015-06-26T17:04:22Z
2015-06-26T17:03:26Z
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 https://ciencia.iscte-iul.pt/public/pub/id/22759
http://hdl.handle.net/10071/9126
url https://ciencia.iscte-iul.pt/public/pub/id/22759
http://hdl.handle.net/10071/9126
dc.language.iso.fl_str_mv eng
language eng
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dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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