On the predictability of realized volatility using feasible GLS
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: | 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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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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7160 |
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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:RCAAP2024-07-07T02:51:06Zoai:repositorio.iscte-iul.pt:10071/9126Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-07-07T02:51:06Repositório 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 |
dc.relation.none.fl_str_mv |
1049-0078 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/embargoedAccess |
eu_rights_str_mv |
embargoedAccess |
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 |
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 |
_version_ |
1817546338218278912 |