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新冠疫情对原油价格的影响：来自经济物理学方法的证据。

Impact of COVID-19 pandemic on crude oil prices: Evidence from Econophysics approach.

作者信息

Gharib Cheima, Mefteh-Wali Salma, Serret Vanessa, Ben Jabeur Sami

机构信息

Laboratoire Interdisciplinaire des Environnements Continentaux (LIEC), UMR 7360 CNRS, Université de Lorraine, Bâtiment IBiSE - Campus Bridoux - 8 rue du Général Delestraint, F-57070, METZ, France.

ESSCA School of Management, 1 rue Lakanal, 49003, Angers, France.

出版信息

Resour Policy. 2021 Dec;74:102392. doi: 10.1016/j.resourpol.2021.102392. Epub 2021 Oct 4.

DOI:10.1016/j.resourpol.2021.102392
PMID:34658485
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8507600/
Abstract

This paper provides an analysis of crude oil, diesel, and gasoline prices for the period from November 1, 2019 to December 31, 2020. We apply Log Periodic Power-Law Singularity (LPPLS) and Discrete Scale LPPLS bubble indicators to explore the dynamic bubbles of oil prices and predict their crash times. The results indicate that West Texas Light crude oil and North Sea Brent crude oil experienced a statistically significant negative financial bubble during the COVID-19 outbreak. In addition, gasoline and diesel prices are mainly driven by fundamentals. Our findings are expected to be useful to oil market investors, policymakers, and energy experts.

摘要

本文分析了2019年11月1日至2020年12月31日期间的原油、柴油和汽油价格。我们应用对数周期幂律奇点（LPPLS）和离散尺度LPPLS泡沫指标来探索油价的动态泡沫，并预测其崩溃时间。结果表明，在新冠疫情爆发期间，西德克萨斯轻质原油和北海布伦特原油经历了具有统计学意义的负金融泡沫。此外，汽油和柴油价格主要由基本面因素驱动。我们的研究结果有望对石油市场投资者、政策制定者和能源专家有所帮助。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3b4/8507600/811ec9dd55a8/fx4_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3b4/8507600/086b07f189fe/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3b4/8507600/7df21f71ffef/gr2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3b4/8507600/c2b7ed4fc315/gr3a_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3b4/8507600/ebead48843ae/gr4a_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3b4/8507600/400242d06e09/fx1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3b4/8507600/ac53aea1bbc0/fx2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3b4/8507600/a4755d4b7fd6/fx3_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3b4/8507600/811ec9dd55a8/fx4_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3b4/8507600/086b07f189fe/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3b4/8507600/7df21f71ffef/gr2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3b4/8507600/c2b7ed4fc315/gr3a_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3b4/8507600/ebead48843ae/gr4a_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3b4/8507600/400242d06e09/fx1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3b4/8507600/ac53aea1bbc0/fx2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3b4/8507600/a4755d4b7fd6/fx3_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3b4/8507600/811ec9dd55a8/fx4_lrg.jpg

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The impact of COVID-19 news, panic and media coverage on the oil and gold prices: An ARDL approach.新冠疫情新闻、恐慌及媒体报道对石油和黄金价格的影响：自回归分布滞后模型方法
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Volatility forecasting of crude oil futures based on a genetic algorithm regularization online extreme learning machine with a forgetting factor: The role of news during the COVID-19 pandemic.
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A singular value decomposition entropy approach to assess the impact of Covid-19 on the informational efficiency of the WTI crude oil market.一种用于评估新冠疫情对西德克萨斯中质原油市场信息效率影响的奇异值分解熵方法。
Chaos Solitons Fractals. 2022 Jul;160:112238. doi: 10.1016/j.chaos.2022.112238. Epub 2022 May 23.
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Analyzing the nexus of COVID-19 and natural resources and commodities: Evidence from time-varying causality.分析新冠疫情与自然资源和商品之间的联系：来自时变因果关系的证据。
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