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...
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Format: | Article |
Language: | English |
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EDP Sciences
2020-01-01
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Series: | SHS Web of Conferences |
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Online Access: | https://www.shs-conferences.org/articles/shsconf/pdf/2020/01/shsconf_ies_2019_01008.pdf |
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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 |
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