The study of behavioural finance has garnered significant interest from many researchers, showing a growing

trend in the publication of research articles in recent times. This paper presents a systematic review and

bibliometric analysis of the existing literature in the field of behavioural finance. The study utilized RStudio and

VOS viewer software to perform a bibliometric analysis of data retrieved from the Scopus database following

the PRISMA protocol. It also systematically reviewed existing literature to identify key behavioural biases,

methodologies, and findings of the selected articles. The findings reveal a growing trend in the publication of

The origins of behavioural finance can be traced back to the groundbreaking work of psychologists Daniel

Kahneman and Amos Tversky, who introduced the concepts of prospect theory and heuristics in decision-making

(Kahneman and Tversky, 1979). Their research revealed that people often rely on cognitive shortcuts and exhibit

predictable biases, such as overconfidence, loss aversion, and herd behaviour (Tversky and Kahneman, 1981).

These biases can lead to suboptimal investment decisions and market anomalies, including bubbles and crashes

(Shiller, 2000). Behavioural finance has developed as a framework that replaced the assumptions of standard

finance theory by incorporating psychological factors into the analysis of financial markets (Sayed & Sayed,

2014). Behavioural finance has merged concepts from finance, economics, and psychology to better understand

human behaviour while investing in various investment avenues and has developed more effective investment

strategies (Sayed & Sayed, 2014). Unlike several conventional finance theories, such as Expected Utility Theory,

logical or rational decisions and drag them into irrationality. The term behavioural bias is derived from the

concept of Behavioural Finance. It addresses how emotional and cognitive aspects hinder investment decisions

of an Individual. The success of the investment is largely driven by the influences of these biases as such it is

essential for investors to recognize their presence and actively strive to limit their effects to make better-informed

and effective investment decisions.

Research on behavioural biases has experienced significant growth over the past two decades, driven by

increasing interest and a surge in publications from academic scholars (Jain, 2021). This surge in scholarly

interest highlights the importance of systematically reviewing and synthesizing existing knowledge to delineate

the current status of the discipline and identify potential research trajectories. This paper aims to give an

overview of the current state of research conducted in the field of behavioural finance. By conducting a

biases. As such, the Systematic literature review (SLR) method is being adopted in the present study. SLR

provides a concise and thorough assessment of the existing evidence and help identify research gaps. They can

also highlight methodological issues to improve future work in a particular topic area (Pericic and Tanveer,

2019). The study also followed the PRISMA protocol to identify the most relevant papers from the database.

The PRISMA model aids in creating a flow diagram that clearly and consistently outlines the process of selecting

and including pertinent studies in a systematic review (Motahari-Nezhad et al., 2021). Further, a bibliometric

analysis is being conducted to determine the publication trend, top contributing countries, impactful Journals

and authors, most cited research papers, and most frequently used keywords. Bibliometric reviews utilize

statistical tools to analyse a large volume of published research, identifying trends, citations, and co-citations

related to a specific theme by year, country, author, journal, methodology, theory, and research problem (Rialp

Due to comprehensive coverage of peer-reviewed literature, access to high quality research articles, and advance

search tools allowing for precise retrieval of relevant articles by title, abstract, and keywords, the Scopus database

was being used in the present study. The data were extracted from the database by selecting "article title, abstract,

keywords" from the search options and entering "Behavioural biases in investment decision making" into the

search document field of the Scopus interface. Further, the search strategy included only those papers with the

keywords behavioural finance, investment decision, investments, behavioural biases, overconfidence bias,

cognitive bias, psychological bias, disposition effect, loss aversion, cognitive biases, regret aversion, anchoring,

herding, overconfidence bias, heuristic, prospect theory, illusion of control, home bias, mental accounting,

framing, conservatism, and availability bias

which includes publication trends, contributing countries, contributing organisations, impactful journals, most

influential studies, impactful authors, and frequently used keywords. In the second section, the result of content

analysis of the selected studies is presented. This includes themes, research methodologies, and key findings of

the selected studies. Together, these sections provide an overview of the current state of research in the field of

behavioural finance.

Source: Authors’ Computation

Figure 1 shows the published trend of articles each year from 2003 to 2024. Although there was possibility of

started to increase gradually from 2007, with notable jumps in 2013, 2019, 2020, and 2022. The highest articles

were published in 2023 (32 articles). The trendline, represented by the equation (y = 1.087x - 6), indicates a

moderate positive linear relationship between the years and the number of articles. The coefficient of

determination, (R² = 0.66416), implies that 66% of the variation in the number of articles can be explained by

the year. This upward trend highlights a growing interest of the researcher over time, with projections showing

Table 1: Top 10 Contributing Countries

Table 1 provides a ranking of the top 10 contributing countries based on the number of research papers published.

Qualitative Research in Financial Markets follows closely with an H-index of 5, 281 citations, and 8 publications.

Other notable journals include the Indian Journal of Finance and Frontiers in Psychology, each with an H-index

of 4 and 3 respectively. The table highlights the prominence of these journals in contributing to research, with

varying levels of impact and publication frequency.

Table 5: Top 10 Impactful Authors

Table 5 shows the top 10 impactful authors based on total number of articles published, their H-index, and total

citations. Goyal N and Kumar S lead with 5 articles each, an H-index of 5, and 396 total citations. Jain J and

Table 6: Most frequently used keywords

theory, risk perception, financial market, and anchoring. Less frequent terms include regret aversion, mental

accounting, confirmation bias, framing, home bias, and familiarity.

A content analysis, which systematically, objectively, and quantitatively analyses the content of existing

literature, was conducted, and while doing so, several key behavioural biases were identified, indicating the

existence of various behavioural biases. Following the foundational work of Kahneman and Tversky (1974,

1979, 1981), these biases are categorized into two main types: Heuristic-Driven Biases and Frame-Dependent

Biases. Table 6 provides a detailed list of the identified behavioural biases under these two categories.

Table 6: Behavioural Biases identified from the literature

Table 7: Statistical Method used by authors in the top 20 papers