Investment Decision Support Based on Interval Type-2 Fuzzy Expert System

Zuzana Janková; Dipak Kumar Jana; Petr Dostál

doi:10.5755/j01.ee.32.2.24884

Authors

Zuzana Janková Brno University of Technology, Czech Republic
Dipak Kumar Jana Haldia Institute of Technology, School of Applied Science & Humanities, India
Petr Dostál Brno University of Technology, Czech Republic

DOI:

https://doi.org/10.5755/j01.ee.32.2.24884

Keywords:

fuzzy logic, interval type-2 fuzzy logic, investment analysis, soft computing, T2FLS

Abstract

The decision-making process on investing in financial markets is a very complex and difficult task, mainly due to the chaotic behavior and high uncertainty in the development of the prices of investment instruments. For this reason, financial markets are increasingly using means of artificial intelligence, namely fuzzy logic, which is able to capture the nonlinear behavior.Fuzzy logic provides a way to draw definitive conclusions from vague, ambiguous, or inaccurate information.However, there are some drawbacks associated with type-1 fuzzy logic, so the type-2 fuzzy logic comes forward, which can work with greater uncertainty. Type-2 fuzzy logic works with a new third dimension fuzzy set that provides additional degrees of freedom and allows to model and process numerical and linguistic uncertainties directly. The paper applies type-2 fuzzy logic to the stock market with the aim to create a simple and understandable model for deciding on investing in investment instruments, which is important for investors in this area. The proposed type-2 fuzzy model uses return, risk, dividend and total expense ratio of ETF as input variables. The created system is able to generate aggregated models from a certain number of language rules, which allows the investor to understand the created financial model. Using type-2 fuzzy logic can lead to more realistic and accurate results than type-1 fuzzy logic.

Author Biographies

Zuzana Janková, Brno University of Technology, Czech Republic

Zuzana Janková is a Ph.D. student at Brno University of Technology (BUT), Faculty of Business and Management, Institute of Informatics. She deals with finance and investment management. Above all, she focuses on the creation of models for decision support and prediction in financial markets through artificial intelligence tools, especially fuzzy logic, artificial neural networks and hybrid neuro-fuzzy models. She has lectured at the National Chengchi University, Taiwan and at the University of Economics in Bratislava, Slovakia.

Dipak Kumar Jana, Haldia Institute of Technology, School of Applied Science & Humanities, India

Dipak Kumar Jana did Ph.D. from Indian Institute of Engineering Science and Technology, Shibpur and did his post-graduation (M.Sc) in Applied Mathematics with specialization in Operations Research from Vidyasagar University, West Bengal. He has qualified in National Eligibility Test (NET-CSIR) for Junior Research Fellow (JRF) and GATE. He is working as Professor & HOD in School of Applied Science & Humanities, Haldia Institute of Technology. Dr. Jana is a member of Operational Research Society of India, Indian Science Congress Association, Calcutta Mathematical Society. Dr. Jana has published more than 86 papers in esteemed International Journals and 6 books. At 17th China Uncertain System annual meeting Jana won the Outstanding Thesis Award of Uncertain Theory, China Operational Research Association, Uncertain System Branch, 19 July, 2019.

Petr Dostál, Brno University of Technology, Czech Republic

Petr Dostál is a Professor of economics and management at Brno University of Technology (BUT), Faculty of Business and Management, Institute of Informatics. Field of interest is the use of soft computing and artificial intelligence such as fuzzy logic, artificial neural networks, evolutionary algorithms, and the theory of chaos in business and public services. As an economic and organization adviser, he has worked in private firms and institutions. He is a member of international institutions, program and organizing committees, scientific and editorial advisory boards.