Prediction of European Stock Indexes Using Neuro-fuzzy Technique
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26510%2F20%3APU136740" target="_blank" >RIV/00216305:26510/20:PU136740 - isvavai.cz</a>
Result on the web
<a href="https://trends.fbm.vutbr.cz/index.php/trends/article/view/trends.2020.35.45" target="_blank" >https://trends.fbm.vutbr.cz/index.php/trends/article/view/trends.2020.35.45</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.13164/trends.2020.35.45" target="_blank" >10.13164/trends.2020.35.45</a>
Alternative languages
Result language
angličtina
Original language name
Prediction of European Stock Indexes Using Neuro-fuzzy Technique
Original language description
The paper is focused on the forecast of stock markets of the Central European countries, known as V4, by means of soft computing. The tested model is constructed by a combination of fuzzy logic and artificial neural networks. A total of four SAX, PX, BUX, WIG stock indices differing in their liquidity and efficiency are selected for the forecast. The paper discussed the design of the neuro-fuzzy model as a supporting tool for predicting the selected stock indexes listed on the European stock markets.
Czech name
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Czech description
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Classification
Type
J<sub>ost</sub> - Miscellaneous article in a specialist periodical
CEP classification
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OECD FORD branch
50202 - Applied Economics, Econometrics
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
TRENDY EKONOMIKY A MANAGEMENTU
ISSN
1802-8527
e-ISSN
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Volume of the periodical
35
Issue of the periodical within the volume
1
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
13
Pages from-to
45-57
UT code for WoS article
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EID of the result in the Scopus database
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