Open Access Article SciPap-1268
A Bibliometric Analysis of Artificial Intelligence Technique in Financial Market
by Zuzana Janková 1,* iD icon

1 Faculty of Business and Management, Institute of Informatics, Brno University of Technology, Kolejní 2906/4, Královo Pole, Brno 612 00, Czechia

* Authors to whom correspondence should be addressed.

Abstract: 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.

Keywords: Fuzzy Logic, Ann, Neural Network, Artificial Intelligence, Ai, Bibliometric Analysis, Financial Market, Stock Market.

JEL classification:   G12 - Asset Pricing • Trading Volume • Bond Interest Rates,   G15 - International Financial Markets,   G17 - Financial Forecasting and Simulation

SciPap 2021, 29(3), 1268;

Received: 7 March 2021 / Revised: 18 August 2021 / Accepted: 23 August 2021 / Published: 15 September 2021