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Information Flow Analysis between EPU and Other Financial Time Series
We investigate the strength and direction of information flow among economic policy uncertainty (EPU), US imports and exports to China, and the CNY/US exchange rate by using the novel concept of effective transfer entropy (ETE) with a sliding window methodology. We verify that this new method can ca...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7517218/ https://www.ncbi.nlm.nih.gov/pubmed/33286453 http://dx.doi.org/10.3390/e22060683 |
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author | Yao, Can-Zhong |
author_facet | Yao, Can-Zhong |
author_sort | Yao, Can-Zhong |
collection | PubMed |
description | We investigate the strength and direction of information flow among economic policy uncertainty (EPU), US imports and exports to China, and the CNY/US exchange rate by using the novel concept of effective transfer entropy (ETE) with a sliding window methodology. We verify that this new method can capture dynamic orders effectively by validating them with the linear transfer entropy (TE) and Granger causality methods. Analysis shows that since 2016, US economic policy has contributed substantially to China-US bilateral trade and that China is making passive adjustments based on this trade volume. Unlike trade market conditions, China’s economic policy has significantly influenced the exchange rate fluctuation since 2016, which has, in turn, affected US economic policy. |
format | Online Article Text |
id | pubmed-7517218 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75172182020-11-09 Information Flow Analysis between EPU and Other Financial Time Series Yao, Can-Zhong Entropy (Basel) Article We investigate the strength and direction of information flow among economic policy uncertainty (EPU), US imports and exports to China, and the CNY/US exchange rate by using the novel concept of effective transfer entropy (ETE) with a sliding window methodology. We verify that this new method can capture dynamic orders effectively by validating them with the linear transfer entropy (TE) and Granger causality methods. Analysis shows that since 2016, US economic policy has contributed substantially to China-US bilateral trade and that China is making passive adjustments based on this trade volume. Unlike trade market conditions, China’s economic policy has significantly influenced the exchange rate fluctuation since 2016, which has, in turn, affected US economic policy. MDPI 2020-06-18 /pmc/articles/PMC7517218/ /pubmed/33286453 http://dx.doi.org/10.3390/e22060683 Text en © 2020 by the author. 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 (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Yao, Can-Zhong Information Flow Analysis between EPU and Other Financial Time Series |
title | Information Flow Analysis between EPU and Other Financial Time Series |
title_full | Information Flow Analysis between EPU and Other Financial Time Series |
title_fullStr | Information Flow Analysis between EPU and Other Financial Time Series |
title_full_unstemmed | Information Flow Analysis between EPU and Other Financial Time Series |
title_short | Information Flow Analysis between EPU and Other Financial Time Series |
title_sort | information flow analysis between epu and other financial time series |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7517218/ https://www.ncbi.nlm.nih.gov/pubmed/33286453 http://dx.doi.org/10.3390/e22060683 |
work_keys_str_mv | AT yaocanzhong informationflowanalysisbetweenepuandotherfinancialtimeseries |