Global energy and geopolitical risk: behavior of oil markets
Purpose The question being assessed is whether changes in the degree of global geopolitical risk (GPR), as defined by the framework developed by Iacoviello (2018), can be used to improve allocative efficiency, thereby increasing investment returns on oil commodities. Design/methodology/approach Usin...
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Published in | International journal of energy sector management Vol. 14; no. 2; pp. 358 - 371 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Bradford
Emerald Publishing Limited
11.02.2020
Emerald Group Publishing Limited |
Subjects | |
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Abstract | Purpose
The question being assessed is whether changes in the degree of global geopolitical risk (GPR), as defined by the framework developed by Iacoviello (2018), can be used to improve allocative efficiency, thereby increasing investment returns on oil commodities.
Design/methodology/approach
Using the linear and nonlinear model, this paper analyzes the impact of GPR on returns of oil prices (BRENT, WTI and Organization of Petroleum Exporting Countries), as well as the short- and long-run relationship between GPR and oil prices.
Findings
The results of the impulse response function indicates that oil prices do not respond to shocks in GPR. The results of the Granger causality test show that oil returns are not caused by GPR. The regression analysis and autoregressive distributed lag results show that there is no significant impact of GPR on the returns of oil.
Originality/value
This is unique among the literature in that it identifies and isolates the relationship between GPR and oil market pricing. Insight into the lag in market response and the degree to which GPR can be used to estimate oil prices using curvilinear models are derived from the analysis. |
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AbstractList | Purpose
The question being assessed is whether changes in the degree of global geopolitical risk (GPR), as defined by the framework developed by Iacoviello (2018), can be used to improve allocative efficiency, thereby increasing investment returns on oil commodities.
Design/methodology/approach
Using the linear and nonlinear model, this paper analyzes the impact of GPR on returns of oil prices (BRENT, WTI and Organization of Petroleum Exporting Countries), as well as the short- and long-run relationship between GPR and oil prices.
Findings
The results of the impulse response function indicates that oil prices do not respond to shocks in GPR. The results of the Granger causality test show that oil returns are not caused by GPR. The regression analysis and autoregressive distributed lag results show that there is no significant impact of GPR on the returns of oil.
Originality/value
This is unique among the literature in that it identifies and isolates the relationship between GPR and oil market pricing. Insight into the lag in market response and the degree to which GPR can be used to estimate oil prices using curvilinear models are derived from the analysis. PurposeThe question being assessed is whether changes in the degree of global geopolitical risk (GPR), as defined by the framework developed by Iacoviello (2018), can be used to improve allocative efficiency, thereby increasing investment returns on oil commodities.Design/methodology/approachUsing the linear and nonlinear model, this paper analyzes the impact of GPR on returns of oil prices (BRENT, WTI and Organization of Petroleum Exporting Countries), as well as the short- and long-run relationship between GPR and oil prices.FindingsThe results of the impulse response function indicates that oil prices do not respond to shocks in GPR. The results of the Granger causality test show that oil returns are not caused by GPR. The regression analysis and autoregressive distributed lag results show that there is no significant impact of GPR on the returns of oil.Originality/valueThis is unique among the literature in that it identifies and isolates the relationship between GPR and oil market pricing. Insight into the lag in market response and the degree to which GPR can be used to estimate oil prices using curvilinear models are derived from the analysis. |
Author | Taillard, Michael Alqahtani, Abdullah |
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Cites_doi | 10.1016/j.resourpol.2015.10.011 10.2139/ssrn.2918723 10.1016/j.frl.2017.07.017 10.1007/BF02941229 10.1086/261140 10.1007/978-1-4899-8008-3_9 10.1016/j.enpol.2011.10.012 10.1016/j.eneco.2016.04.018 10.1016/j.enpol.2009.08.043 10.1016/j.joep.2004.08.004 10.1111/j.1540-6261.1996.tb02691.x 10.1016/j.irfa.2009.03.003 10.1016/S0304-3932(96)01281-0 10.1016/j.intfin.2012.11.007 10.1080/13504851.2018.1494802 10.1016/j.jclepro.2016.06.030 10.1016/j.eneco.2008.09.006 10.1002/jae.616 10.3982/ECTA6248 10.1016/j.irfa.2017.01.004 10.1111/j.1468-0343.2009.00357.x 10.1016/j.enpol.2007.07.020 10.1016/S0304-4076(02)00207-5 |
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The question being assessed is whether changes in the degree of global geopolitical risk (GPR), as defined by the framework developed by Iacoviello... PurposeThe question being assessed is whether changes in the degree of global geopolitical risk (GPR), as defined by the framework developed by Iacoviello... |
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SubjectTerms | Correlation analysis Crude oil Crude oil prices Energy consumption Energy industry Foreign policy Friction Geopolitics Impact analysis Impulse response International relations Market prices Oil Political risk Regression analysis Response functions Risk taking Trends Volatility |
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