Detail publikace

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

JANKOVÁ, Z.

Originální název

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

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

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.

Klíčová slova

ANFIS; financial market; fuzzy logic; neural networks; soft computing

Autoři

JANKOVÁ, Z.

Vydáno

7. 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

Číslo edice

1

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"
}