The Latest Statistical and Computational Methods: Applications in Management Prediction Systems

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F47813059%3A19240%2F09%3A%230002968" target="_blank" >RIV/47813059:19240/09:#0002968 - 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
The Latest Statistical and Computational Methods: Applications in Management Prediction Systems
Original language description
We examine the statistical forecasting models based on the Bayesian method and ARCH-GARCH models for prediction of the demand for new products and the bond price time series provided by VUB bank respectively. In the case of Bayesian methods, we make comparisons the forecast accuracy with the class of exponential smoothing methods. In the second case we compare the forecast accuracy of the ARCH-GARCH models with RBF neural network models. In a comparative study is shown that the presented approaches areable to model and predict a process in which there is little or no useful historical information available and processes with high frequency data, by reasonable accuracy and more efficient than classic statistical methods.
Czech name
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Czech description
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Project
<a href="/en/project/GA402%2F08%2F0022" target="_blank" >GA402/08/0022: The Latest Intelligent Methodologies for Economic Time Series Modelling and Forecasting</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2009
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Interdisciplinary Relationships in the Theory and Practice of Informatics, management, economics and Mathematics
ISBN
978-80-8084-471-4
ISSN
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e-ISSN
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Number of pages
118
Pages from-to
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Publisher name
Catholic University in Ruzomberok, Faculty of Education
Place of publication
Rožomberok
Event location
Spišská kapitule
Event date
Jan 1, 2009
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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