Forecasting Models for Malaysia KLCI - Price Index Based on Advanced Statistical Models vs. SC Models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F15%3A86096476" target="_blank" >RIV/61989100:27510/15:86096476 - 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
Forecasting Models for Malaysia KLCI - Price Index Based on Advanced Statistical Models vs. SC Models
Original language description
We evaluate statistical and machine learning methods for predicting Malaysia KLCI - Price Index and consider the accuracy of forecasting models based on statistical (stochastic), machine learning methods and an intelligent methodology based on soft or granular computing. In this paper, we apply the ARIMA-ARCH methodology on the developing forecast models and compare their forecast accuracy with the class of RBF neural network models. We found that it is possible to enhance forecast accuracy and also achieve significant risk reduction in managerial decision-making by applying intelligent forecasting models based on latest information technologies. In a comparative study is shown that the presented approach is able to model and predict high frequency data with reasonable accuracy and more efficient than statistical methods.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/EE2.3.20.0296" target="_blank" >EE2.3.20.0296: Research team for modelling of economic and financial processes at VSB-TU Ostrava</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Financial Management of Firms and Financial Institutions : 10th international scientific conference : 7th - 8th September 2015, Ostrava, Czech Republic : proceedings. [Part I - IV]
ISBN
978-80-248-3865-6
ISSN
2336-162X
e-ISSN
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Number of pages
7
Pages from-to
740-746
Publisher name
VŠB - Technical University of Ostrava
Place of publication
Ostrava
Event location
Ostrava
Event date
Sep 7, 2015
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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