Herding Behavior in Financial Markets: Tracing the Evolution of Knowledge Through a Systematic Review and Bibliometric Analysis

This study examines how research on herding behavior in financial markets evolved between ۱۹۹۰ and ۲۰۲۵. The study included bibliometric analysis and a systematic review based on the SPAR-۴-SLR methodology. VOSviewer and Bibliometrix software were used to map the themes, trends and collaboration of the research. Keyword clusters and conceptual maps indicated a transition from simple market explanations to interdisciplinary approaches including behavioral economics, social learning and digital information pathways. There were four periods. Between ۱۹۹۰ and ۲۰۰۰, the leading explanations of herding were information cascades and reputational concerns. Work from the period ۲۰۰۰-۲۰۱۰ included psychological elements such as loss aversion and overconfidence, as well as agent-based modeling. Systemic risk was still a potential worry. The literature after the ۲۰۰۸ crisis during ۲۰۱۰-۲۰۱۵ highlighted the market crashes and systemic risks as the main effects of the crisis. The asset price bubbles were the precursors of the crises rather than the consequences of the crises. Asset price bubbles resurfaced with the emergence of cryptocurrencies, NFTs, and meme-stock markets driven by social media and algorithmic herding over the period of ۲۰۱۵–۲۰۲۵. Researchers explored systemic vulnerabilities in algorithmic trading, high-frequency data, and machine learning. The findings shed light on the changing link between market microstructure and behavioral finance.

کلیدواژه ها:

Behavioral Finance ، Bibliometric Analysis ، Financial markets ، Herding Behavior ، Systematic Review