Energy pricing during the COVID-19 pandemic: Predictive information-based uncertainty indexes with machine learning algorithm

被引:17
作者
Olubusoye, Olusanya E. [1 ,2 ,3 ,4 ]
Akintande, Olalekan J. [1 ,2 ,4 ]
Yaya, OlaOluwa S. [2 ,3 ,4 ]
Ogbonna, Ahamuefula E. [3 ,4 ,5 ]
Adenikinju, Adeola F. [6 ,7 ]
机构
[1] Univ Ibadan, Dept Stat, Lab Interdisciplinary Stat Anal, Ibadan, Nigeria
[2] Univ Ibadan, Dept Stat, Computat Stat Unit, Ibadan, Nigeria
[3] Univ Ibadan, Ctr Econometr & Allied Res, Ibadan, Nigeria
[4] Univ Ibadan, Ctr Petr Energy Econ & Law, Ibadan, Nigeria
[5] Univ Ibadan, Dept Stat, Econ & Stat Unit, Ibadan, Nigeria
[6] Univ Ibadan, Ctr Petr Energy Econ & Law CPEEL, Ibadan, Nigeria
[7] Univ Ibadan, Dept Econ, Ibadan, Nigeria
来源
INTELLIGENT SYSTEMS WITH APPLICATIONS | 2021年 / 12卷
关键词
Coronavirus pandemic; Energy market; Machine learning; Uncertainty;
D O I
10.1016/j.iswa.2021.200050
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The study investigates the impact of uncertainties on energy pricing during the COVID-19 pandemic using five uncertainty measures that include the COVID-Induced Uncertainty (CIU), Economic Policy Uncertainty (EPU), Global Fear Index (GFI); Volatility Index (VIX), and the Misinformation Index of Uncertainty (MIU). The data, which span between 2-January, 2020 and 19-January, 2021, corresponding to the period of the COVID-19 pandemic. The study finds energy prices to respond significantly to the examined uncertainty measures, with EPU seen to affect the prices of most energy types during the pandemic. We also find predictive potentials inherent in VIX, CIU, and MIU for global energy sources. (c) 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ )
引用
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页数:10
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