Forecasting volatility in gold returns under the GARCH, IGARCH and FIGARCH frameworks: new evidence
Autor(a) principal: | |
---|---|
Data de Publicação: | 2015 |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10071/11254 |
Resumo: | This study employs three volatility models of the GARCH family to examine the volatility behavior of gold returns. Much of the literature on this topic suggests that gold plays a fundamental role as a hedge and safe haven against adverse market conditions, which is particularly relevant in periods of high volatility. This makes understanding gold volatility important for a number of theoretical and empirical applications, namely investment valuation, portfolio selection, risk management, monetary policy-making, futures and option pricing, hedging strategies and value-at-risk (VaR) policies (e.g. Baur and Lucey (2010)). We use daily data from August 2, 1976 to February 6, 2015 and divide the full sample into two periods: the in-sample period (August 2, 1976-October 24, 2008) is used to estimate model coefficients, while the out-of-sample period (October 27, 2008-February 6, 2015) is for forecasting purposes. Specifically, we employ the GARCH(1,1), IGARCH(1,1) and FIGARCH(1,d,1) specifications. The results show that the FIGARCH(1,d,1) is the best model to capture linear dependence in the conditional variance of the gold returns as given by the information criteria. It is also found to be the best model to forecast the volatility of gold returns. |
id |
RCAP_79bea3997bfc6bda5e5bfc1b24e3e9c2 |
---|---|
oai_identifier_str |
oai:repositorio.iscte-iul.pt:10071/11254 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
spelling |
Forecasting volatility in gold returns under the GARCH, IGARCH and FIGARCH frameworks: new evidenceGold returnsLong-memoryShock persistenceVolatility forecastsConditional varianceFIGARCHThis study employs three volatility models of the GARCH family to examine the volatility behavior of gold returns. Much of the literature on this topic suggests that gold plays a fundamental role as a hedge and safe haven against adverse market conditions, which is particularly relevant in periods of high volatility. This makes understanding gold volatility important for a number of theoretical and empirical applications, namely investment valuation, portfolio selection, risk management, monetary policy-making, futures and option pricing, hedging strategies and value-at-risk (VaR) policies (e.g. Baur and Lucey (2010)). We use daily data from August 2, 1976 to February 6, 2015 and divide the full sample into two periods: the in-sample period (August 2, 1976-October 24, 2008) is used to estimate model coefficients, while the out-of-sample period (October 27, 2008-February 6, 2015) is for forecasting purposes. Specifically, we employ the GARCH(1,1), IGARCH(1,1) and FIGARCH(1,d,1) specifications. The results show that the FIGARCH(1,d,1) is the best model to capture linear dependence in the conditional variance of the gold returns as given by the information criteria. It is also found to be the best model to forecast the volatility of gold returns.Elsevier2016-05-05T16:50:27Z2015-01-01T00:00:00Z20152019-05-13T15:55:25Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/11254eng0378-437110.1016/j.physa.2015.07.011Bentes, S. 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:RCAAP2023-11-09T17:54:23Zoai:repositorio.iscte-iul.pt:10071/11254Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:27:24.402495Repositório 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 volatility in gold returns under the GARCH, IGARCH and FIGARCH frameworks: new evidence |
title |
Forecasting volatility in gold returns under the GARCH, IGARCH and FIGARCH frameworks: new evidence |
spellingShingle |
Forecasting volatility in gold returns under the GARCH, IGARCH and FIGARCH frameworks: new evidence Bentes, S. R. Gold returns Long-memory Shock persistence Volatility forecasts Conditional variance FIGARCH |
title_short |
Forecasting volatility in gold returns under the GARCH, IGARCH and FIGARCH frameworks: new evidence |
title_full |
Forecasting volatility in gold returns under the GARCH, IGARCH and FIGARCH frameworks: new evidence |
title_fullStr |
Forecasting volatility in gold returns under the GARCH, IGARCH and FIGARCH frameworks: new evidence |
title_full_unstemmed |
Forecasting volatility in gold returns under the GARCH, IGARCH and FIGARCH frameworks: new evidence |
title_sort |
Forecasting volatility in gold returns under the GARCH, IGARCH and FIGARCH frameworks: new evidence |
author |
Bentes, S. R. |
author_facet |
Bentes, S. R. |
author_role |
author |
dc.contributor.author.fl_str_mv |
Bentes, S. R. |
dc.subject.por.fl_str_mv |
Gold returns Long-memory Shock persistence Volatility forecasts Conditional variance FIGARCH |
topic |
Gold returns Long-memory Shock persistence Volatility forecasts Conditional variance FIGARCH |
description |
This study employs three volatility models of the GARCH family to examine the volatility behavior of gold returns. Much of the literature on this topic suggests that gold plays a fundamental role as a hedge and safe haven against adverse market conditions, which is particularly relevant in periods of high volatility. This makes understanding gold volatility important for a number of theoretical and empirical applications, namely investment valuation, portfolio selection, risk management, monetary policy-making, futures and option pricing, hedging strategies and value-at-risk (VaR) policies (e.g. Baur and Lucey (2010)). We use daily data from August 2, 1976 to February 6, 2015 and divide the full sample into two periods: the in-sample period (August 2, 1976-October 24, 2008) is used to estimate model coefficients, while the out-of-sample period (October 27, 2008-February 6, 2015) is for forecasting purposes. Specifically, we employ the GARCH(1,1), IGARCH(1,1) and FIGARCH(1,d,1) specifications. The results show that the FIGARCH(1,d,1) is the best model to capture linear dependence in the conditional variance of the gold returns as given by the information criteria. It is also found to be the best model to forecast the volatility of gold returns. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-01-01T00:00:00Z 2015 2016-05-05T16:50:27Z 2019-05-13T15:55:25Z |
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/10071/11254 |
url |
http://hdl.handle.net/10071/11254 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0378-4371 10.1016/j.physa.2015.07.011 |
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 |
|
_version_ |
1799134836987789312 |