Time series analysis and data prediction: An ECM neuronal approach applied to EUR/USD currency

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F47813059%3A19240%2F14%3A%230005350" target="_blank" >RIV/47813059:19240/14:#0005350 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.4028/www.scientific.net/AMR.918.30" target="_blank" >http://dx.doi.org/10.4028/www.scientific.net/AMR.918.30</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.4028/www.scientific.net/AMR.918.30" target="_blank" >10.4028/www.scientific.net/AMR.918.30</a>

Result language
angličtina
Original language name
Time series analysis and data prediction: An ECM neuronal approach applied to EUR/USD currency
Original language description
Several approaches to dynamic modeling in economic such as ARIMA, GARCH, neural nets and error corrected models have become popular in recent years. We evaluate statistical and neuronal methods for daily EUR/USD currency prediction using daily EUR/USD time series data. Both techniques are reviewed and contrasted from the accuracy of forecasting models point of view. We show that an RBF neural network can achieve better prediction results than the latest statistical methodologies. Following fruitful applications of neural networks to predict financial data this work goes ahead by using neural networks for modeling any non-linearities within the estimated statistical models.
Czech name
—
Czech description
—

Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
—

Project
<a href="/en/project/ED1.1.00%2F02.0070" target="_blank" >ED1.1.00/02.0070: IT4Innovations Centre of Excellence</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Similar results(10)