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JANKOVÁ, Z.
Original Title
Adaptive Neuro-Fuzzy Inference System (ANFIS) for Forecasting: The Case of the Czech Stock Market
English Title
Type
Paper in proceedings (conference paper)
Original Abstract
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.
English abstract
Keywords
ANFIS; financial market; fuzzy logic; neural networks; soft computing
Key words in English
Authors
RIV year
2020
Released
07.11.2019
Publisher
Tomas Bata University of Zlin
Location
Zlin, Czech Republic
ISBN
978-80-7454-893-2
Book
Conference Proceedings DOKBAT 15th Annual International Bata Conference for Ph.D. Students and Young Researchers
Edition
15
Pages from
457
Pages to
465
Pages count
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" }