Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F47813059%3A19240%2F16%3A%230005528" target="_blank" >RIV/47813059:19240/16:#0005528 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1155/2016/3460293" target="_blank" >http://dx.doi.org/10.1155/2016/3460293</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1155/2016/3460293" target="_blank" >10.1155/2016/3460293</a>

Result language

angličtina

Original language name

Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network

Original language description

This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in decision-making process of financial managers. The work focuses mainly on one representative of the intelligent soft computing techniques ? artificial neural networks. Authors suggest the new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm and a moving average. The moving average is supposes to to enhance the outputs of the network using the error part of the original RBF. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day.To determine the forecasting efficiency, they perform the comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimiz

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

IN - Informatics

OECD FORD branch

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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

2016

Confidentiality

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

Name of the periodical

The Scientific World Journal

ISSN

2356-6140

e-ISSN

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Volume of the periodical

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Issue of the periodical within the volume

2016

Country of publishing house

US - UNITED STATES

Number of pages

15

Pages from-to

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UT code for WoS article

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EID of the result in the Scopus database

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