文章基本信息

标题：Using RBF neural networks to identify relationship between development of oil prices in world market and value of Chinese currency
本地全文：下载
作者：akub Horák ; Jaromír Vrbka ; Tomáš Krulický 等
期刊名称：SHS Web of Conferences
印刷版ISSN：2416-5182
电子版ISSN：2261-2424
出版年度：2020
卷号：73
页码：1-12
DOI：10.1051/shsconf/20207301008
语种：English
出版社：EDP Sciences
摘要：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.
关键词：RBF neural networks;value;oil prices;exchange rate