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

Authors :
Horák Jakub
Vrbka Jaromír
Krulický Tomáš
Source :
SHS Web of Conferences, Vol 73, p 01008 (2020)
Publication Year :
2020
Publisher :
EDP Sciences, 2020.

Abstract

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.

Details

Language :
English, French
ISSN :
22612424 and 20207301
Volume :
73
Database :
Directory of Open Access Journals
Journal :
SHS Web of Conferences
Publication Type :
Academic Journal
Accession number :
edsdoj.9b58c693f832465b9f2dc2cfa0b64333
Document Type :
article
Full Text :
https://doi.org/10.1051/shsconf/20207301008