Managerial Forecasting System Based on RBF Neural Network for Financial Data

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F47813059%3A19240%2F12%3A%230004399" target="_blank" >RIV/47813059:19240/12:#0004399 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Managerial Forecasting System Based on RBF Neural Network for Financial Data
Original language description
Forecasting systems are applied which are based on the latest statistical theory and artificial neural networks. The impact of these methods to risk reduction is judged in managerial decision-making. The fundamental question arises whether non-linear methods like neural networks can help modeling any non-linearities being inherent within the estimated statistical model. The proposed novel modeling approach is applied to high frequency time series of USD/CAD exchange rates. Our results show that the proposed neural approach achieves better forecast accuracy on the validation dataset than most available statistical techniques.
Czech name
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Czech description
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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
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
2013 International Conference on Information, Businessand Education Technology - ICIBET 2013
ISBN
978-90-78677-56-7
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
225-228
Publisher name
Atlantis Press Paris
Place of publication
Peking, Čína
Event location
Peking, Čína
Event date
Jan 1, 2012
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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