Behavioral Biases In Investment Decision Making–A Bibliometric Analysis Of Twenty Years

Abstract

It is difficult to overstate the importance of behavioural biases in investment decision-making because they play the most crucial role. This article's primary objective is to assist researchers in developing a theoretical framework and to assist new research on behavioural biases in determining which themes, journals, and authors to consider when researching this subject. In this research, 934 articles from 228 Web of Science (WoS) sources published between 2002 and 2022 are subjected to bibliometric analysis. The analysis was conducted using the R statistical programming language package Bibliometrix. Using bibliometric analysis, researchers identified and interpreted five thematic research clusters describing factors influencing financial decision-making, such as market efficiency and momentum; various emotional and cognitive biases, such as overconfidence and anchoring bias; theories, such as prospect theory; and general domains, such as behavioural finance, behavioural economics, and experimental economics. In the literature, cognitive biases were examined more frequently than emotional biases, but when researchers compared the three most prevalent types of cognitive and emotional biases, emotional biases came out on top. In addition, the results have confirmed the significance of Hirshleifer D, Kumar A, Wang Y, and Zhang H to this research field. In the present study, Overconfidence was the most prevalent bias in behavioural finance.