Publication detail

Prediction of European Stock Indexes Using Neuro-fuzzy Technique

JANKOVÁ, Z. DOSTÁL, P.

Original Title

Prediction of European Stock Indexes Using Neuro-fuzzy Technique

Type

journal article - other

Language

English

Original Abstract

The paper is focused on the forecast of stock markets of the Central European countries, known as V4, by means of soft computing. The tested model is constructed by a combination of fuzzy logic and artificial neural networks. A total of four SAX, PX, BUX, WIG stock indices differing in their liquidity and efficiency are selected for the forecast. The paper discussed the design of the neuro-fuzzy model as a supporting tool for predicting the selected stock indexes listed on the European stock markets.

Keywords

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

Authors

JANKOVÁ, Z.; DOSTÁL, P.

Released

30. 6. 2020

Publisher

Brno University of Technology, Faculty of Business and Management,, Czech Republic

Location

Brno

ISBN

1802-8527

Periodical

TRENDY EKONOMIKY A MANAGEMENTU

Year of study

35

Number

1

State

Czech Republic

Pages from

45

Pages to

57

Pages count

13

URL

BibTex

@article{BUT164375,
  author="Zuzana {Janková} and Petr {Dostál}",
  title="Prediction of European Stock Indexes Using Neuro-fuzzy Technique",
  journal="TRENDY EKONOMIKY A MANAGEMENTU",
  year="2020",
  volume="35",
  number="1",
  pages="45--57",
  doi="10.13164/trends.2020.35.45",
  issn="1802-8527",
  url="https://trends.fbm.vutbr.cz/index.php/trends/article/view/trends.2020.35.45"
}