Risk assessment of oil price from static and dynamic modelling approaches

Mi, Zhi-Fu, Wei, Yi-Ming, Tang, Bao-Jun, Cong, Rong-Gang, Yu, Hao, Cao, Hong and Guan, Dabo (2017) Risk assessment of oil price from static and dynamic modelling approaches. Applied Economics, 49 (9). pp. 929-939. ISSN 0003-6846

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Abstract

The price gap between West Texas Intermediate (WTI) and Brent crude oil markets has been completely changed in the past several years. The price of WTI was always a little larger than that of Brent for a long time. However, the price of WTI has been surpassed by that of Brent since 2011. The new market circumstances and volatility of oil price require a comprehensive re-estimation of risk. Therefore, this study aims to explore an integrated approach to assess the price risk in the two crude oil markets through the value at risk (VaR) model. The VaR is estimated by the extreme value theory (EVT) and GARCH model on the basis of generalized error distribution (GED). The results show that EVT is a powerful approach to capture the risk in the oil markets. On the contrary, the traditional variance–covariance (VC) and Monte Carlo (MC) approaches tend to overestimate risk when the confidence level is 95%, but underestimate risk at the confidence level of 99%. The VaR of WTI returns is larger than that of Brent returns at identical confidence levels. Moreover, the GED-GARCH model can estimate the downside dynamic VaR accurately for WTI and Brent oil returns.

Item Type: Article
Uncontrolled Keywords: value at risk,ged-garch,extreme value theory,risk quantification,oil markets,c13,g32,q40
Faculty \ School: Faculty of Social Sciences > School of International Development
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Depositing User: Pure Connector
Date Deposited: 24 Sep 2016 00:11
Last Modified: 04 Nov 2020 00:46
URI: https://ueaeprints.uea.ac.uk/id/eprint/59894
DOI: 10.1080/00036846.2016.1208359

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