Stock Market Anomalies through the Lens of Behavioural Finance: Themes, research clusters from bibliometric analysis

Abstract The presence of irregularities in stock price behaviour, known as market anomalies, reflects deviations from traditional finance theory such as the Efficient Market Hypothesis, which assumes fully rational investor decision-making. Guided by behavioural finance, this study identifies the anomalies that influence individual investor behaviour and provides a systematic bibliometric assessment of research on stock market anomalies within this domain. In this study, we aim to map performance trends, most influential journals, citations, prolific authors and co-occurrence analysis in the domain of stock market anomalies. We extracted data from Scopus along with Web of Science, and filtered for Q1 and Q2 journals listed in the 2024 Scimago Journal Rankings (SSCI), a final dataset of 331 articles published covering the period from 2000 to 2025. We employed the R bibliometric package and VOSviewer for scientific mapping, followed SPAR-4-SLR protocol adapted from Paul et al. (2021), to ensure rigour, transparency, and reproducibility. We found significant publication trends show that the annual production of articles increases tremendously over the year in the field of behavioural finance and stock market anomalies. Furthermore, thematic analysis highlights six major research clusters, emphasising core areas such as market anomalies, investor sentiment, market efficiency, and behavioural finance. The study offers valuable insights for academicians and practitioners by outlining intellectual structure, thematic evolution, and research trajectories of the field, thereby providing a comprehensive foundation and roadmap for future research on stock market anomalies within behavioural finance.