Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autor principal: Yao, Can-Zhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
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
_version_ 1783587179573805056
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