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This paper describes how financial professionals' behavioral biases influence their financial forecast and decision-making process. Most of the earlier studies are focused on well-developed financial markets, and little is researched about financial professionals, such as institutional investors, portfolio managers, investment advisors, financial analysts, etc., in emerging markets.

An expert-validated questionnaire measure four prominent behavioral biases and Indian financial professionals' rational decision-making process. The final sample consists of 274 valid responses using the purposive sampling technique. IBM SPSS and AMOS structural equation modeling (SEM) software are used to build measurement and structural models, multivariate analysis including regression, factor analysis, etc.

The results provide empirical insights into the relationship between behavioral biases and the decision-making process. The results suggest that the structural path model closely fits the sample data. The presence of behavioral biases indicates that financial professionals' forecasting and decision-making is not always rational but bounded rational or irrational due to these factors. Furthermore, these biases (except overconfidence bias) have a markedly significant and positive relationship with irrational decision-making.

It is critical to eradicate these psychological errors, but awareness and attentiveness toward behavioral biases may help financial professionals to make informed decisions. Investors can improve their portfolio decisions and investments by recognizing their judgment errors and focusing on specific investment strategies to mitigate the impact of these biases. It is necessary to incorporate behavioral insights while developing training techniques for financial professionals. Rules of thumb, visual tools, financial coaching and implementing social-cultural elements in training programs enable financial professionals to develop simple, engaging, appealing and customized approaches for their clients.

This novel study is the first of this kind of research that examines the relationship between financial professionals' behavioral biases and rational decision-making process. This study significantly and remarkably provides insights into irrationality in financial professionals' decision-making.

This paper aims to review, systematize and integrate existing research on disposition effect and investments. This study conducts bibliometric analysis, including performance analysis and science mapping and thematic analysis of studies on disposition effect.

This study adopted a thematic and bibliometric analysis of the papers related to the disposition effect. A total of 231 papers published from 1971 to 2021 were retrieved from the Scopus database for the study, and bibliometric analysis and thematic analysis were performed.

This study’s findings demonstrate that research on the disposition effect is interdisciplinary and influences the research in the domain of both corporate and behavioral finance. This review indicates limited research on cross-country data. This study indicates a strong presence of work on investor psychology and behavioral finance when it comes to the disposition effect. The findings of thematic analysis further highlight that most of the research has focused on prospect theory, trading strategies and a few cognitive and emotional biases.

The findings of this study can be used by investors to minimize their biases and losses. The study also highlights new techniques in machine learning and neurosciences, which can help investment firms better understand their clients’ behavior. Policymakers can use the study’s findings to nudge investors’ behavior, focusing on minimizing the effects of the disposition effect.

This study has performed the quantitative bibliometric and thematic analysis of existing studies on the disposition effect and identified areas of future research on the phenomenon of disposition effect in investments.

The disposition effect remains one of the most significant investor behavior puzzles. This study aims to consolidate the knowledge, explore current dynamics, elicit trends and offer future research directions to demystify the disposition effect.

This study applies the hybrid review method. It first used bibliometric analysis (212 documents), followed by content analysis (54 articles) to analyze the breadth and depth of literature on the disposition effect.

This study presents performance analysis and science mapping. It identifies five main research streams: evidence, implications and mitigation techniques; theoretical explanations; investor biases and hedonic framing; attributes, beliefs and preferences; and implications for asset pricing and market efficiency. This study further offers future research directions for disposition effect research.

This study deploys sequential bibliometric and content analysis. A meta-analysis of quantitative articles could provide specific insights regarding the disposition effect. Besides, this study is based on Scopus-indexed journals only.

This study benefits investors and portfolio managers as they learn effective ways to guard against the disposition effect. Policymakers may tweak tax laws to incentivize long-term holding, and regulators can run investor education campaigns to minimize the disposition effect’s consequences effectively.

To the best of the authors’ knowledge, this is probably the first hybrid review of high-quality, contemporary articles on the disposition effect that offers science mapping, research streams, future research directions and a succinct summary of theories, contexts, characteristics and methods deployed in the field of research.

In the stock market, herding behavior occurs when investors mimic the actions of others in their investment decisions. As a result, the market becomes inefficient and speculative bubbles form. This study aims to investigate the relationship between information, overconfidence, market sentiment, experience and national culture, and herding behavior among Malaysian investors. A total of 400 questionnaires are distributed to bank institutions' investors. The survey design based on cross-sectional data is analyzed using the Partial Least Squares Structural Equation Model. The results indicate that information, market sentiment, experience, and national culture are positively related to herding behavior, while overconfidence has no effect. With this, the government should strengthen regulations to prevent the dissemination of misleading information. Moreover, investors are encouraged to overcome narrow thinking by expanding their understanding of different cultures when making investment decisions.

This paper aims to investigate the behaviour determinants towards cash waqf for productive purposes between two different classes of Muslims: the upper-middle class and the lower-middle class.

Under the Theory of Planned Behavior framework, this study modified previous literature to investigate the determinants of two Muslim classes’ behaviour towards cash waqf for productive purposes. A structural equation model was applied to test the hypothesis, and an in-depth interview was conducted to explain the findings further.

The behaviour of participating in cash waqf for productive purposes differs between the two Muslim segments. Upper-middle-class Muslims’ intentions will not necessarily consider subjective norms, even though they will consider religiosity as their deciding factor. Meanwhile, this study found different results on the influence of attitude, religiosity and subjective norms to intention in the lower-middle-income group. Other attributes such as perceived behaviour control, knowledge, trust and perceived benefits show positive and significant effects on the intention for both income classes of Muslims.

The current findings may not accurately reflect ideal conditions due to the low level of waqf literacy and actual participation of Muslims in cash waqf for productive purposes. Researchers can conduct further studies based on other criteria, such as gender, age, education level or area of residence, using experimental or simulation methods to complement the research.

This study’s findings can support policymakers and related waqf stakeholders to set strategies for cash waqf literacy and participation by providing more detailed information about the differences in Muslims characteristics based on the income classes.

This study specifically modifies the behavioural framework to investigate differences in the behaviour of two classes of Muslims towards their participation in cash waqf for productive purposes in Indonesia.

This study explores the economic impact of the COVID-19 crisis on herding behaviour in the Australian equity market by considering liquidity, government interventions and sentiment contagion.

This study utilizes a daily dataset of the top 500 stocks in the Australian market from January 2009 to December 2021. Both predictive regression and portfolio approaches are employed to consider the impact of COVID-19 on herding intention.

This study confirms that herding propensity is more pronounced at the beginning of the crisis and becomes less significant towards later phases when reverse herding is more visible. Investors herd more toward sectors with less available information on financial support from the government during the financial meltdown. Conditioning the stock liquidity, herding is only detectable during highly liquid periods and high-liquid stocks, which is more observable during the initial phases of the crisis. Further, the mood contagion from the United States (US) market to Australian market and asymmetric herding intention are evident during the pandemic.

This is the first study to shed further light on the impact of a health crisis on the trading behaviour of Australian investors, which is driven by liquidity, public information and sentiment. Notwithstanding the theoretical contributions to the prior literature, several practical implications are proposed for businesses, policymakers and investors during uncertainty periods.

This study aims to analyse the impact of the big five personality traits on the financial risk tolerance of individuals. Furthermore, it also examines the differences in personality traits and financial risk tolerance across four generations: baby boomers, Generation X, millennials and Generation Z.

The data constituted 869 responses from Indian individuals, collected using a self-administered structured questionnaire using a convenience sampling technique.

Structural equation modelling analysis showed that openness to experience, extraversion and neuroticism had a significant impact on financial risk tolerance. Multivariate analysis revealed the role of specific personality traits in predicting the financial risk tolerance of generational cohorts. Mean difference showed that millennials and Generation Z had the greatest risk tolerance, whereas the tolerance levels were lower for Generation X and baby boomers.

This research provides insights into the role of personality on financial risk-taking among generational cohorts in India. Thus, these results cannot be generalised for other risk-taking domains or outside the Indian context.

This study’s results align with the pulse rate hypothesis of generational theory and contribute to the growing field of behavioural economics and finance. It provides a perspective of the emerging economy of India, where behavioural finance studies are still at a nascent stage.

This study aims to systematically review various behavioral biases that impact an investor’s decision-making process. The prime objective of this paper is to thematically explore the behavioral bias literature and propose a comprehensive framework that can elucidate a more reasonable explanation of changes in financial markets and investors’ behavior.

Systematic literature review (SLR) methodology is applied to a portfolio of 71 peer-reviewed articles collected from different electronic databases between 2007 and 2021. Content analysis of the extant literature is performed to identify the research themes and existing gaps in the literature.

This research identifies publication trends of the behavioral biases literature and uncovers 24 different biases that impact individual investors’ decision-making. Through thematic analysis, an attribute–consequence–impact framework is proposed that explains different biases leading to individual investors’ irrationality. The study further proposes directions for future research by applying the theory–characteristics–context–methodology framework.

The results of this research will help scholars and practitioners in understanding the existence of various behavioral biases and assist them in identifying potential strategies which can evade the negative effects of these biases. The findings will further help the financial service providers to understand these biases and improve the landscape of financial services.

The essence of the current paper is the application of the SLR method on 24 biases in the area of behavioral finance. To the best of the authors’ knowledge, this study is the first attempt of its kind which provides a methodical and comprehensive compilation of both cognitive and emotional behavioral biases that affect the individual investor’s decision-making.

This paper aims to survey literature on behavioral economics and finance, with particular emphasis on a selection of models, methods and tools that this strand of thought uses to approach and explain observable phenomena.

After a brief discussion on the meaning and context of behavioral economics, the manuscript identifies five topics of special interest: time preference, heuristics, emotions, finance and macro behavior. For each of these topics, relevant models, methods and tools are identified and scrutinized.

Behavioral economics and finance establish an effective bridge between orthodox economic thinking and new and revolutionary methods of analysis. Exploring the intricacies of human behavior can frequently be done by adapting the trivial and conventional intertemporal utility maximization models that economists insistently resort to, but to fully grasp such intricacies, a step forward is required. Agent-based models and other tools from complexity sciences constitute the analytical arsenal that is needed to improve our understanding of how behavioral issues attach to heterogeneity, local interaction, path-dependence, out-of-equilibrium dynamics and emergence.

Although surveys on behavioral economics and finance abound in the specialized literature, this study has the peculiarity of emphasizing five relevant topics that are particularly illustrative of the pivotal role of behavioral science in promoting the transition from the strict neoclassical perspective to a less mechanic and more organic view of economics and finance.

This paper aims to study and discover the unsearched area in behavioral finance in the new era of technology enhancement. The study has been done with two significant methodologies of reviews. This study also covers the whole structure of the investment decision scenario.

A systematic and bibliometric analysis has been done to make this study conceptual. Data collection sources are highly indexed journals, Scopus, Web of Science and Google Scholar. The “R” package has been used to do bibliometric analysis. Start with data cleaning and import the data in biblioshiny to get and interpret the result. A total of 642 data has been finalized from 1973 to 2022.

Various noticeable results have been found to accomplish the objectives and fill the gap in the study. There is a need to research both technological and psychological factors to determine the relation of these two variables with the investment decision-making of investors.

This study has done a systematic literature review and a bibliometric analysis that shows the importance of technology enhancement for further research, which has been searchable throughout this study.