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Research Article | Open Access

Decomposing and reconstructing dynamic risks in the crude oil market based on the VMD and Lempel–Ziv algorithms

Hao Dong1Zhehao Huang2( )
Lingnan College, Sun Yat-Sen University, Guangzhou 510275, China
Guangzhou Institute of International Finance, Guangzhou University, Guangzhou 510010, China
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Abstract

Crude oil markets have become increasingly uncertain. To study them, we first employ the decomposition-ensemble framework based on the variational mode decomposition (VMD) and Lempel–Ziv algorithms to assess the crude oil dual attributes. Three steps are involved: 1) conditional autoregressive value at risk measures the crude oil risk; 2) they are decomposed by the VMD algorithm into submodes; 3) the Lempel–Ziv algorithm is applied to analyze the crude oil risk for each, thereby identifying the oil commodity or oil financial risks. The results of the empirical analysis reveal significantly different amplitudes for the high- and low-frequency crude oil risk. By summarizing the crude oil risk components, we also conclude that the mean value for the oil commodity risk is 0.04, while that for the oil financial risk is 0. What is more, the oil commodity risk is highly related to downward trends in oil prices, while the oil financial risk exerts the same clustering effect as oil returns.

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Electronic Research Archive
Pages 4674-4696

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Cite this article:
Dong H, Huang Z. Decomposing and reconstructing dynamic risks in the crude oil market based on the VMD and Lempel–Ziv algorithms. Electronic Research Archive, 2022, 30(12): 4674-4696. https://doi.org/10.3934/era.2022237

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Received: 05 September 2022
Revised: 12 October 2022
Accepted: 13 October 2022
Published: 15 December 2022
©2022 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)