Investment Decision Support Based on Interval Type-2 Fuzzy Expert System
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26510%2F21%3APU140764" target="_blank" >RIV/00216305:26510/21:PU140764 - isvavai.cz</a>
Result on the web
<a href="https://inzeko.ktu.lt/index.php/EE/article/view/24884" target="_blank" >https://inzeko.ktu.lt/index.php/EE/article/view/24884</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5755/j01.ee.32.2.24884" target="_blank" >10.5755/j01.ee.32.2.24884</a>
Alternative languages
Result language
angličtina
Original language name
Investment Decision Support Based on Interval Type-2 Fuzzy Expert System
Original language description
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.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
50204 - Business and management
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Engineering Economics
ISSN
1392-2785
e-ISSN
2029-5839
Volume of the periodical
32
Issue of the periodical within the volume
2
Country of publishing house
LT - LITHUANIA
Number of pages
12
Pages from-to
118-129
UT code for WoS article
000646046800003
EID of the result in the Scopus database
2-s2.0-85105587892