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 inInternational journal of energy sector management Vol. 14; no. 2; pp. 358 - 371
Main Authors Alqahtani, Abdullah, Taillard, Michael
Format Journal Article
LanguageEnglish
Published Bradford Emerald Publishing Limited 11.02.2020
Emerald Group Publishing Limited
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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.
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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Crude oil
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StartPage 358
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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Title Global energy and geopolitical risk: behavior of oil markets
URI https://www.emerald.com/insight/content/doi/10.1108/IJESM-04-2019-0005/full/html
https://www.proquest.com/docview/2534243176
Volume 14
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