Artificial Stock Markets: A Literature Review

Abstract

This study aims to carry out a bibliometric analysis and systematic review of publications on artificial stock markets. The final sample consists of 52 articles. Such articles are obtained from the WoS and Scopus databases. Bibliometric analysis describes the frequency, citations and relationships between the main data of articles -authors, journals, keywords, etc. In addition, bibliometric laws are verified -Lotka (1926( ), Bradford (1934 and Zipf (1949). The bibliometric analysis is carried out using the Rstudio and Biblioshiny software. In turn, the systematic review seeks to identify knowledge gaps in the existing literature. This part of the research is still under development. The partial results of the research -resulting from the bibliometric analysis -indicate that the most prominent keywords are artificial stock market, genetic programming and agent-based modeling. Shu-Heng Chen appears as the most relevant author and co-author. When considering the institutions to which these authors are linked, it appears that the country with the largest number of published articles is China. However, the articles with the highest number of citations are linked to authors from institutions in the United States. The three bibliometric laws were confirmed.