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.
Highlights
Financial markets play an important role in the economic and social organization of modern society
It is necessary to reveal which issues remain open in this area and in the part of the work to focus on these white spaces in research
The hybrid approach based on GA and SA significantly improves the accuracy of the prediction and surpasses the traditional BP training algorithm
Summary
Financial markets play an important role in the economic and social organization of modern society. In these types of markets, information is an invaluable asset. Many scientists have attempted to develop computational intelligent methods and algorithms to support decision-making in various segments of the financial market, as described by Cavalcande et al (2016). The issue of capital market decision-making using data mining techniques is one of the most important areas of financing. This attracted great scientific interest and became a key point of research to ensure a more accurate predictive and decision-making process (Cibulskiene and Brazauskas, 2017)
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