Equalizing seasonal time series using artificial neural networks in predicting the Euro-Yuan exchange rate

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F75081431%3A_____%2F19%3A00001559" target="_blank" >RIV/75081431:_____/19:00001559 - isvavai.cz</a>

Result on the web

<a href="http://apps.webofknowledge.com/full_record.do?product=WOS&search_mode=GeneralSearch&qid=18&SID=F6xnU9HOLRR1jfSCtjp&page=1&doc=1" target="_blank" >http://apps.webofknowledge.com/full_record.do?product=WOS&search_mode=GeneralSearch&qid=18&SID=F6xnU9HOLRR1jfSCtjp&page=1&doc=1</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/jrfm12020076" target="_blank" >10.3390/jrfm12020076</a>

Result language

angličtina

Original language name

Equalizing seasonal time series using artificial neural networks in predicting the Euro-Yuan exchange rate

Original language description

This contribution aims to propose a methodology for considering seasonal fluctuations in equalizing time series by means of artificial neural networks on the example of Euro and Chinese Yuan. Regression by means of neural networks is carried out. There are two network sets generated, of which the second one focuses on the seasonal fluctuations.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

50200 - Economics and Business

Project

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Continuities

N - Vyzkumna aktivita podporovana z neverejnych zdroju

Publication year

2019

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Journal of Risk and Financial Management

ISSN

1911-8066

e-ISSN

1911-8074

Volume of the periodical

12

Issue of the periodical within the volume

2

Country of publishing house

CH - SWITZERLAND

Number of pages

17

Pages from-to

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UT code for WoS article

000475294000027

EID of the result in the Scopus database

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