Publication detail

Application of Artificial Neural Networks and Fuzzy Logic in Stock Trading

JANKOVÁ, Z.

Original Title

Application of Artificial Neural Networks and Fuzzy Logic in Stock Trading

Type

conference paper

Language

English

Original Abstract

The paper discusses the design of a neuro-fuzzy model for decision-making support in free money investment in investment instruments listed on the stock exchange in the Czech Republic. Basic financial indicators, such as return, risk, P/E ratio and EPS have been used for this purpose. Based on the obtained results, it can be stated that the proposed ANFIS model is a suitable tool, in particular for modelling complex and non-linear problems. A neuro-fuzzy model behaves more naturally than other statistical tools, which simulates the decision-making process in stock trading, without increasing the risk in the form of investor's subjective judgment.

Keywords

fuzzy logic; artificial neural networks; stock market; stock trading; soft computing; Czech stock market; ANFIS

Authors

JANKOVÁ, Z.

Released

11. 4. 2019

Publisher

IBIMA

Location

Granada, Spain

ISBN

978-0-9998551-2-6

Book

Proceedings of the 33rd International Business Information Management Association Conference (IBIMA)

Pages from

2610

Pages to

2619

Pages count

10

BibTex

@inproceedings{BUT157197,
  author="Zuzana {Janková}",
  title="Application of Artificial Neural Networks and Fuzzy Logic in Stock Trading",
  booktitle="Proceedings of the 33rd International Business Information Management Association Conference (IBIMA)",
  year="2019",
  pages="2610--2619",
  publisher="IBIMA",
  address="Granada, Spain",
  isbn="978-0-9998551-2-6"
}