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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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
Description
Summary: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.
ISSN:2261-2424