Foreign exchange rates forecasting based on high-frequency data using neural networks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A_____%2F02%3A11800009" target="_blank" >RIV/62156489:_____/02:11800009 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Foreign exchange rates forecasting based on high-frequency data using neural networks
Original language description
In this paper, a neural network based foreign exchange rates forecasting method is discussed. The data set used in this study contains 15-minute prices of US dollar against other major currencies. We tested feed-forward neural networks with back-propagation algorithm. The study shows, that it is possible to forecast short-term future FX movements without the use of extensive market data.
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
AH - Economics
OECD FORD branch
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Result continuities
Project
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Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2002
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
ACTA UNIVERSITATIS AGRICULTURAE ET SILVICULTURAE MENDELIANAE BRUNENSIS
ISSN
1211-8516
e-ISSN
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Volume of the periodical
Neuveden
Issue of the periodical within the volume
6
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
9
Pages from-to
175-183
UT code for WoS article
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EID of the result in the Scopus database
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