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Risk Transmission of Trade Price Fluctuations from a Nickel Chain Perspective: Based on Systematic Risk Entropy and Granger Causality Networks
Nickel is a strategic mineral resource, with 65% of nickel being used in stainless steel. The situation in Ukraine starting in February 2022 has led to significant fluctuations in nickel prices, with prices of nickel products along the same chain affecting and passing through each other. Using syste...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9497779/ https://www.ncbi.nlm.nih.gov/pubmed/36141107 http://dx.doi.org/10.3390/e24091221 |
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author | Zhou, Xuanru Zheng, Shuxian Zhang, Hua Liu, Qunyi Xing, Wanli Li, Xiaotong Han, Yawen Zhao, Pei |
author_facet | Zhou, Xuanru Zheng, Shuxian Zhang, Hua Liu, Qunyi Xing, Wanli Li, Xiaotong Han, Yawen Zhao, Pei |
author_sort | Zhou, Xuanru |
collection | PubMed |
description | Nickel is a strategic mineral resource, with 65% of nickel being used in stainless steel. The situation in Ukraine starting in February 2022 has led to significant fluctuations in nickel prices, with prices of nickel products along the same chain affecting and passing through each other. Using systematic risk entropy and granger causality networks, we measure the volatility risk of trade prices of nickel products using the nickel industry chain trade data from 2000–2019 and explore the transmission patterns of different volatility risk prices from the industry chain perspective. The findings show that: (1) Nickel ore has the highest risk of import trade price volatility and a strong influence, but low risk transmission. Stainless steel has the highest trade price impact but is also subject to the strongest passive influence. (2) The Americas have a higher risk of trade price volatility but a weaker influence. The influence and sensitivity of trade prices is stronger in Asia and Europe. (3) Indonesia’s stainless steel export prices have a high rate of transmission and strong influence. Germany’s ferronickel export prices are highly susceptible to external influences and can continue to spread loudly. Russian nickel ore export prices are able to quickly spread their impact to other regions. |
format | Online Article Text |
id | pubmed-9497779 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-94977792022-09-23 Risk Transmission of Trade Price Fluctuations from a Nickel Chain Perspective: Based on Systematic Risk Entropy and Granger Causality Networks Zhou, Xuanru Zheng, Shuxian Zhang, Hua Liu, Qunyi Xing, Wanli Li, Xiaotong Han, Yawen Zhao, Pei Entropy (Basel) Article Nickel is a strategic mineral resource, with 65% of nickel being used in stainless steel. The situation in Ukraine starting in February 2022 has led to significant fluctuations in nickel prices, with prices of nickel products along the same chain affecting and passing through each other. Using systematic risk entropy and granger causality networks, we measure the volatility risk of trade prices of nickel products using the nickel industry chain trade data from 2000–2019 and explore the transmission patterns of different volatility risk prices from the industry chain perspective. The findings show that: (1) Nickel ore has the highest risk of import trade price volatility and a strong influence, but low risk transmission. Stainless steel has the highest trade price impact but is also subject to the strongest passive influence. (2) The Americas have a higher risk of trade price volatility but a weaker influence. The influence and sensitivity of trade prices is stronger in Asia and Europe. (3) Indonesia’s stainless steel export prices have a high rate of transmission and strong influence. Germany’s ferronickel export prices are highly susceptible to external influences and can continue to spread loudly. Russian nickel ore export prices are able to quickly spread their impact to other regions. MDPI 2022-08-31 /pmc/articles/PMC9497779/ /pubmed/36141107 http://dx.doi.org/10.3390/e24091221 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zhou, Xuanru Zheng, Shuxian Zhang, Hua Liu, Qunyi Xing, Wanli Li, Xiaotong Han, Yawen Zhao, Pei Risk Transmission of Trade Price Fluctuations from a Nickel Chain Perspective: Based on Systematic Risk Entropy and Granger Causality Networks |
title | Risk Transmission of Trade Price Fluctuations from a Nickel Chain Perspective: Based on Systematic Risk Entropy and Granger Causality Networks |
title_full | Risk Transmission of Trade Price Fluctuations from a Nickel Chain Perspective: Based on Systematic Risk Entropy and Granger Causality Networks |
title_fullStr | Risk Transmission of Trade Price Fluctuations from a Nickel Chain Perspective: Based on Systematic Risk Entropy and Granger Causality Networks |
title_full_unstemmed | Risk Transmission of Trade Price Fluctuations from a Nickel Chain Perspective: Based on Systematic Risk Entropy and Granger Causality Networks |
title_short | Risk Transmission of Trade Price Fluctuations from a Nickel Chain Perspective: Based on Systematic Risk Entropy and Granger Causality Networks |
title_sort | risk transmission of trade price fluctuations from a nickel chain perspective: based on systematic risk entropy and granger causality networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9497779/ https://www.ncbi.nlm.nih.gov/pubmed/36141107 http://dx.doi.org/10.3390/e24091221 |
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