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Detail publikačního výsledku
JANKOVÁ, Z.
Originální název
Adaptive Neuro-Fuzzy Inference System (ANFIS) for Forecasting: The Case of the Czech Stock Market
Anglický název
Druh
Stať ve sborníku v databázi WoS či Scopus
Originální abstrakt
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.
Anglický abstrakt
Klíčová slova
ANFIS; financial market; fuzzy logic; neural networks; soft computing
Klíčová slova v angličtině
Autoři
Rok RIV
2020
Vydáno
07.11.2019
Nakladatel
Tomas Bata University of Zlin
Místo
Zlin, Czech Republic
ISBN
978-80-7454-893-2
Kniha
Conference Proceedings DOKBAT 15th Annual International Bata Conference for Ph.D. Students and Young Researchers
Edice
15
Strany od
457
Strany do
465
Strany počet
9
BibTex
@inproceedings{BUT161518, author="Zuzana {Janková}", title="Adaptive Neuro-Fuzzy Inference System (ANFIS) for Forecasting: The Case of the Czech Stock Market", booktitle="Conference Proceedings DOKBAT 15th Annual International Bata Conference for Ph.D. Students and Young Researchers", year="2019", series="15", number="1", pages="457--465", publisher="Tomas Bata University of Zlin", address="Zlin, Czech Republic", isbn="978-80-7454-893-2" }