A Bibliometric Analysis of Artificial Intelligence Technique in Financial Market
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26510%2F21%3APU141585" target="_blank" >RIV/00216305:26510/21:PU141585 - isvavai.cz</a>
Result on the web
<a href="https://editorial.upce.cz/1804-8048/29/3/1268" target="_blank" >https://editorial.upce.cz/1804-8048/29/3/1268</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.46585/sp29031268" target="_blank" >10.46585/sp29031268</a>
Alternative languages
Result language
angličtina
Original language name
A Bibliometric Analysis of Artificial Intelligence Technique in Financial Market
Original language description
This article aims to explore the main areas of research, development trends and provide a systematic overview of publications in the field of artificial intelligence in financial markets. The bibliometric tool VOSViewer is used in this paper. We analyzed 353 articles and contributions obtained from the database of Web of Science, and summarized our findings as follows: artificial intelligence is becoming increasingly widespread in the field of finance and interdisciplinary interconnection; artificial intelligence tools such as neural networks and fuzzy logic are most often used to predict the development of financial time series, or to create decision models; the most important cited authors in this field are Markowitz and Lebaron. Expert System with Application is the cradle of a significant part of fundamental research in the field of artificial intelligence. By using effective bibliometric methods, we provide comprehensive analysis and in-depth insight into the subject area of research, which allows individuals and especially new beginners interested in this area to obtain valuable information and possible direction of future research. The study is recommended to focus on hybrid models prediction of individual sectors of the financial markets, which are present in the current research on the rise.
Czech name
—
Czech description
—
Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
—
OECD FORD branch
50206 - Finance
Result continuities
Project
—
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
Scientific Papers of the University of Pardubice, Series D
ISSN
1211-555X
e-ISSN
1804-8048
Volume of the periodical
29
Issue of the periodical within the volume
3
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
10
Pages from-to
1-10
UT code for WoS article
—
EID of the result in the Scopus database
2-s2.0-85115781648