Using RBF neural networks to identify relationship between development of oil prices in world market and value of Chinese currency

The objective of the contribution is to identify a possible relationship between the development of the price of Brent oil (Brent in USD/barrel) and the CNY / USD Exchange rate by means of artificial neural networks. Understanding future fluctuation characteristics and the trend in oil prices is the...

Full description

Bibliographic Details
Main Authors: Horák Jakub, Vrbka Jaromír, Krulický Tomáš
Format: Article
Language:English
Published: EDP Sciences 2020-01-01
Series:SHS Web of Conferences
Subjects:
Online Access:https://www.shs-conferences.org/articles/shsconf/pdf/2020/01/shsconf_ies_2019_01008.pdf
_version_ 1818644366360576000
author Horák Jakub
Vrbka Jaromír
Krulický Tomáš
author_facet Horák Jakub
Vrbka Jaromír
Krulický Tomáš
author_sort Horák Jakub
collection DOAJ
description The objective of the contribution is to identify a possible relationship between the development of the price of Brent oil (Brent in USD/barrel) and the CNY / USD Exchange rate by means of artificial neural networks. Understanding future fluctuation characteristics and the trend in oil prices is the basis for a deep understanding of systemic mechanisms and trends in related research areas. However, given the complexities of oil prices, it is very difficult to obtain accurate forecasts. Within the experiment, a total of 50,000 artificial RBF neural networks were generated. Was found the CNY / USD price will play a significant role in creating China's real product. Given that it was already proven that the CNY / USD exchange depends on Brent in USD / barrel, it is important to focus the further research on finding out the time lag with which the price of Brent in USD / barrel is actually reflected in the price of CNY / USD.
first_indexed 2024-12-17T00:13:42Z
format Article
id doaj.art-9b58c693f832465b9f2dc2cfa0b64333
institution Directory Open Access Journal
issn 2261-2424
language English
last_indexed 2024-12-17T00:13:42Z
publishDate 2020-01-01
publisher EDP Sciences
record_format Article
series SHS Web of Conferences
spelling doaj.art-9b58c693f832465b9f2dc2cfa0b643332022-12-21T22:10:45ZengEDP SciencesSHS Web of Conferences2261-24242020-01-01730100810.1051/shsconf/20207301008shsconf_ies_2019_01008Using RBF neural networks to identify relationship between development of oil prices in world market and value of Chinese currencyHorák Jakub0Vrbka Jaromír1Krulický Tomáš2Institute of Technology and Business School of Expertness and Valuation Okružní 517/10Institute of Technology and Business School of Expertness and Valuation Okružní 517/10Institute of Technology and Business School of Expertness and Valuation Okružní 517/10The objective of the contribution is to identify a possible relationship between the development of the price of Brent oil (Brent in USD/barrel) and the CNY / USD Exchange rate by means of artificial neural networks. Understanding future fluctuation characteristics and the trend in oil prices is the basis for a deep understanding of systemic mechanisms and trends in related research areas. However, given the complexities of oil prices, it is very difficult to obtain accurate forecasts. Within the experiment, a total of 50,000 artificial RBF neural networks were generated. Was found the CNY / USD price will play a significant role in creating China's real product. Given that it was already proven that the CNY / USD exchange depends on Brent in USD / barrel, it is important to focus the further research on finding out the time lag with which the price of Brent in USD / barrel is actually reflected in the price of CNY / USD.https://www.shs-conferences.org/articles/shsconf/pdf/2020/01/shsconf_ies_2019_01008.pdfrbf neural networksvalueoil pricesexchange rate
spellingShingle Horák Jakub
Vrbka Jaromír
Krulický Tomáš
Using RBF neural networks to identify relationship between development of oil prices in world market and value of Chinese currency
SHS Web of Conferences
rbf neural networks
value
oil prices
exchange rate
title Using RBF neural networks to identify relationship between development of oil prices in world market and value of Chinese currency
title_full Using RBF neural networks to identify relationship between development of oil prices in world market and value of Chinese currency
title_fullStr Using RBF neural networks to identify relationship between development of oil prices in world market and value of Chinese currency
title_full_unstemmed Using RBF neural networks to identify relationship between development of oil prices in world market and value of Chinese currency
title_short Using RBF neural networks to identify relationship between development of oil prices in world market and value of Chinese currency
title_sort using rbf neural networks to identify relationship between development of oil prices in world market and value of chinese currency
topic rbf neural networks
value
oil prices
exchange rate
url https://www.shs-conferences.org/articles/shsconf/pdf/2020/01/shsconf_ies_2019_01008.pdf
work_keys_str_mv AT horakjakub usingrbfneuralnetworkstoidentifyrelationshipbetweendevelopmentofoilpricesinworldmarketandvalueofchinesecurrency
AT vrbkajaromir usingrbfneuralnetworkstoidentifyrelationshipbetweendevelopmentofoilpricesinworldmarketandvalueofchinesecurrency
AT krulickytomas usingrbfneuralnetworkstoidentifyrelationshipbetweendevelopmentofoilpricesinworldmarketandvalueofchinesecurrency