Literature Review of Fundamental and Technical Indicators Prediction of Financial Market Using Artificial Intelligence Technique
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26510%2F20%3APU137642" target="_blank" >RIV/00216305:26510/20:PU137642 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.7441/dokbat.2020.21" target="_blank" >http://dx.doi.org/10.7441/dokbat.2020.21</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.7441/dokbat.2020.21" target="_blank" >10.7441/dokbat.2020.21</a>
Alternative languages
Result language
angličtina
Original language name
Literature Review of Fundamental and Technical Indicators Prediction of Financial Market Using Artificial Intelligence Technique
Original language description
The stock market plays a key role in national economies. The goal of every investor is to maximize the return and minimize the risk arising from the investment. As a result, many studies have been conducted to predict stock market developments using indicators derived from classical stock market analyzes - fundamental and technical through methods and means of artificial intelligence and others. This study attempted to conduct a systematic and critical literature review of 40 articles and contributions from relevant research and scientific papers indexed in world databases. The results revealed the most common fundamental and technical indicators that serve as inputs to artificial intelligence models with a focus on fuzzy logic, neural networks or hybrid models.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
50206 - Finance
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Conference Proceedings DOKBAT 16th Annual International Bata Conference for Ph.D. Students and Young Researchers
ISBN
9788074549359
ISSN
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e-ISSN
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Number of pages
14
Pages from-to
242-254
Publisher name
Tomas Bata University of Zlin
Place of publication
Zlin, Czech Republic
Event location
Zlín
Event date
Nov 6, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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