Adaptive Neuro-Fuzzy Inference System (ANFIS) for Forecasting: The Case of the Czech Stock Market

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26510%2F19%3APU135002" target="_blank" >RIV/00216305:26510/19:PU135002 - 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
Adaptive Neuro-Fuzzy Inference System (ANFIS) for Forecasting: The Case of the Czech Stock Market
Original language description
The paper discusses the use of an adaptive neuro-fuzzy inference system (ANFIS) for modelling and forecasting the return of stock index in a typical financial market. Artificial intelligence models are suitable for modelling systems of complex, dynamic and non-linear relationships common in financial markets. Forecasting is performed for the PX stock index listed on the exchange of the Czech Republic with five selected variables demonstrating high interdependence with the selected index. Based on the research results it can be stated that the proposed ANFIS model is an effective system for forecasting financial time series even in a market with limited liquidity and effectiveness such as the Czech stock market.
Czech name
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Czech description
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Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Conference Proceedings DOKBAT 15th Annual International Bata Conference for Ph.D. Students and Young Researchers
ISBN
978-80-7454-893-2
ISSN
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e-ISSN
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Number of pages
9
Pages from-to
457-465
Publisher name
Tomas Bata University of Zlin
Place of publication
Zlin, Czech Republic
Event location
Zlín
Event date
Nov 6, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000692876300044

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