A comparative scientometric analysis of investor sentiment and trading behaviour research

Abstract

The purpose of this study is to conduct a comparative analysis of investor sentiment and trading behavior in the field of behavioral finance. This study analyzes and compares the research evolution within these two domains using various scientometric analysis methods. The analysis reveals that the number of publications in the field of investor sentiment has grown exponentially while research activity in trading behavior has slowed down in recent years. Investor sentiment research has attracted more attention and generated more publications despite a relatively late start. The USA and China are the major countries conducting research in these two fields and the research output is primarily derived from economically developed regions. Investor sentiment and trading behavior research shows a convergence trend with common research hotspots including COVID-19, Bitcoin and machine learning. Both fields are concentrated in financial market research and have emerging research frontiers such as financial crises, social media and cryptocurrencies. Highly cited articles indicate a degree of overlap between the two fields wherein the domain of trading behavior is predominantly linked to investor sentiment. This study provides valuable insights into the research progress on investor sentiment and trading behavior.