Publication detail

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

JANKOVÁ, Z.

Original Title

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

Type

conference paper

Language

English

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.

Keywords

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

Authors

JANKOVÁ, Z.

Released

7. 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

Edition number

1

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"
}