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A Bibliometric Analysis of Stock Trading Research: Unveiling Publication Trends and Future Direction Economic Alternatives
year
2025
Issue
4

A Bibliometric Analysis of Stock Trading Research: Unveiling Publication Trends and Future Direction

Abstract

This research aims to comprehensively analyze the landscape of stock trading research. The study seeks to understand the current state of publications, identify emerging trends, recognize key contributors, and explore potential future directions in the field. It also aims to elaborate on descriptive analysis, publication trends, author and institution profiling, collaboration networks, and factorial analysis to provide a multifaceted view of stock trading research. This research uses BiblioMagika and Biblioshiny, a shiny app for the Bibliometrix R package, to perform bibliometric analysis of stock trading studies. The data retrieved from the Scopus database is decoded into multiple visualized formats using the method applied in this study. This study’s review of stock trading studies encompasses all relevant papers from 1984 until early 2024, utilizes data from 396 sources, covering 578 documents, and involves 1,118 authors. An appropriate scan and refinement of the article’s record was performed. The study reveals substantial growth in stock trading publications, with notable peaks in recent years. Emerging trends include the increasing influence of technology, machine learning, and a global collaborative effort. The dynamics of stock trading are characterized by a symbiotic relationship between foundational knowledge, advanced analytics, automation, and digitalization. The interplay between these factors reflects the evolving nature of the stock trading ecosystem, where technology plays a pivotal role in shaping investment, trading behaviors, behavioral finance and artificial intelligence integration. The Scopus online database was the sole place where stock trading studies were examined from multiple perspectives. Other publications published in other databases are not included. Subsequent investigations may examine comparable publications found in other reputable databases. This research makes a significant contribution to the area by providing a thorough trend of stock trading research, highlighting technological breakthroughs, identifying important contributors, considering possible research future directions, and adding to the body of knowledge on stock trading.

Keywords

artificial intelligence, bibliometric analysis, stock trading, behavioral finance
Download EA.2025.4.01.pdf