A Bibliometric Analysis of Artificial Intelligence Technique in Financial Market

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

A Bibliometric Analysis of Artificial Intelligence Technique in Financial Market

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

A Bibliometric Analysis of Artificial Intelligence Technique in Financial Market

Popis výsledku anglicky

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.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

50206 - Finance

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Scientific Papers of the University of Pardubice, Series D

ISSN

1211-555X

e-ISSN

1804-8048

Svazek periodika

29

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

10

Strana od-do

1-10

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85115781648