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This paper aims to identify psychological factors that influence people to be involved in Ponzi and pyramid schemes.

A psychological approach to finance or behavioural finance is applied in this research because of the assumption that human beings are not always rational. The sample consisted of 98 investors in 11 cities in Indonesia who were or had invested in an investment program with a Ponzi or pyramid scheme. The snowball sampling technique was applied.

The conclusion is that optimism (emotional bias), confirmation bias, representativeness bias, framing bias and overconfidence (cognitive bias) positively influenced investment decisions related to Ponzi and pyramid schemes.

The novelty aspect of this research is the implementation of a behavioural finance perspective to answer and express the fascinating phenomenon of Ponzi and pyramid investment schemes.

This paper attempts to identify the biases in decision-making of individual investors. The paper aims to develop and validate a higher-order behavioral biases scale.

Scale development is done by identifying the relevant items of the scale through existing literature and then, adding new items for some biases. In phase 1, using a structured questionnaire, data was collected from 274 investors who invest in financial markets. The major dimensions of the scale have been pruned by using exploratory factor analysis administered on data collected in phase 1. Higher-order CFA is used to analyze the data and to validate the scale on another set of data (collected in phase 2) containing 576 investors.

The study reveals that the scale for measuring behavioral biases has many dimensions. It has two second-order factors and 13 zero-order constructs. Two second-order constructs have been modeled on the basis of cause of errors in investment decision-making, that is, biases caused due to cognition, biases caused due to emotions.

Behavioral biases are yet to receive a due attention, especially, in the Indian context. The present research is focusing on providing an empirically tested scale to test the behavioral biases. Some of the biases, which have been analyzed using secondary data in previous studies, have been tested with the help of statements in this study.

This paper examines the relation between the Big Five model of personality traits and behavioral biases (overconfidence, disposition effect, anchoring, representativeness, metal accounting, emotional bias and herding) of Indian individual investors when making investment decisions.

The authors use a structured questionnaire to obtain responses from 515 stock investors in India between August 2016 and January 2017. Based on components identified through factor analysis, the authors use structural equation modeling to examine the effect of specific personality traits.

The findings indicate a significant association between the traits of neuroticism, extroversion and conscientiousness as well as behavioral biases of individual investors. Openness has a significant relation with only mental accounting and the agreeableness trait has no relation with the behavioral biases examined.

The findings imply that understanding investor personality differences and investment psychology can help financial advisors and wealth managers modify products and services to better suit client needs.

To the best of the authors’ knowledge, no previous study has examined the impact of the Big Five model of personality traits on various behavioral biases among Indian investors.

In earlier studies, research has shown that EI is the only element, which influences the ways in which people develop in their lives, jobs and social skills control their emotions and get along with other people. It is EI that dictates the way people deal with one another and understand emotions. The research gap is to explore the impact of behavioral factors and investors psychology on their investment decision-making.

The information was gathered from 500 financial specialists. The region of research was the financial specialists who contribute through LSC Securities Ltd. in Punjab State. The purposive testing system was used in this examination.

The investigation found that the positive connection between the conduct predispositions of the financial specialists and venture choices of the speculators and positive connection between enthusiastic insight of the financial specialists and their venture choices. Yet, the authors found that the enthusiastic insight better foresees the venture choices of the financial specialists than the conduct predispositions of the speculators. Among the different elements of conduct inclinations of the speculator’s lament and carelessness are identified with the financial specialist’s venture choices. Among the various estimations of eager understanding – care, dealing with emotions, motivation, empathy and social aptitudes are related to the hypothesis decisions of the monetary pros.

The sample selection was based on purposive sampling, rather than a random probability sample. The sample was area specific, restricted only to Ludhiana Stock Exchange in Punjab state. Therefore, the results of the study cannot be generalized with certainty to all the investors investing through other exchanges in other states. The inferences are based on the assumption that the data provided by the investors are true and correct. The findings may be relevant for other stock exchanges as that of the Ludhiana Stock Exchange. However, the authors do not claim the generalization of the results.

This study also helps to understand the relationship between investment decision-making and risk tolerance of investors. It will helpful for the financial advisors to know the behavioral biases of investors while making an investment decision, and therefore, they can advise investors properly to mitigate such biases. It may help the investors in understanding the subjective part of their behavior and control their emotions while taking decisions for their investment in stock market options.

This research will help investment advisors and finance professionals to judge investors’ attitudes toward risk in a better way, which leads to better investment decisions.

This study is my own study and it is original and has not been published anywhere.

What is the discipline's current grasp of cognitive biases in negotiation processes? What lessons can be drawn from this body of literature? The purpose of this paper is to review and discuss the limited research on cognitive biases in the context of negotiations.

This article reviews research from judgment and decision-making, conflict management, psychology, and management literatures to systematize what we already know about cognitive biases in negotiations.

Decision-making studies have mainly identified 21 biases that may lead to lower quality decisions. Only five of those biases have been studied relating to negotiations: the anchoring, the overconfidence, the framing, the status quo and the self-serving bias. Moreover, negotiation literature has identified five additional biases that affect negotiation processes: the fixed-pie error, the incompatibility error, the intergroup bias, the relationship bias and the toughness bias. Biased behavior differs across cultures and emotional mood.

Implications for future research include building comprehensive models of how negotiators can overcome cognitive biases, studying interconnections between different biases, and increasing complexity of the studies to provide practitioners with more practical advice.

The literature reviewed in this paper spans diverse disciplines and perspectives. This paper can be a starting point for researchers interested in understanding how cognitive biases affect negotiations. Moreover, it could be a starting point for future research on this field.

The purpose of this paper is to examine how financial literacy and demographic variables (gender, age, income level, education, occupation, marital status and investment experience) related to behavioral biases.

The study uses one-way analysis of variance (ANOVA), factor analysis and multiple regression analysis to examine survey data from more than 500 individual investors in India.

The results reveal the presence of different behavioral biases including overconfidence and self-attribution, the disposition effect, anchoring bias, representativeness, mental accounting, emotional biases and herding among Indian investors. Hence, the findings support the view that individual investors do not always act rationally. The results also show that financial literacy has a negative association with the disposition effect and herding bias, a positive relation with mental accounting bias, but no significant relation with overconfidence and emotional biases. Age, occupation and investment experience are the most important demographic variables that relate to the behavioral biases of individual investors in the sample. Regarding gender, males are more overconfident than are females about their knowledge of the stock market.

The study does not test for causality, only association between the variables. Thus, the findings in this study should not be interpreted as suggesting causality. The study may have implications for financial educators in promoting the financial awareness programs for individuals. Financial advisors can potentially become more effective by understanding their clients’ decision-making processes.

Despite an extensive literature on behavioral finance, limited academic research attempts to unravel the relation of how financial literacy and demographic variates relate to behavioral biases. This study contributes to this literature by trying to fill this gap.

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.

Current research in the field of behavioural finance has attempted to discover behavioural biases and their characteristics in individual investors’ irrational decision-making. This study aims to find out how biases in information based on knowledge affect decisions about investments.

In step one, through existing research and consultation with specialists, 13 relevant items covering major aspects of bias were determined. In the second step, multiple linear regression and artificial neural network were used to analyse the data of 337 retail investors.

The investment choice was heavily impacted by regret aversion, followed by loss aversion, overconfidence and the Barnum effect. It was observed that the Barnum effect has a statistically significant negative link with investing choices. The research also found that investors’ fear of making mistakes and their tendency to be too sure of themselves were the most significant factors in their decisions about where to put their money.

This research contributes to the expansion of the knowledge base in behavioural finance theory by highlighting the significance of cognitive psychological traits in how leading investors end up making irrational decisions. Portfolio managers, financial institutions and investors in developing markets may all significantly benefit from the information offered.

This research is a one-of-a-kind study, as it analyses the emotional biases along with the cognitive biases of investor decision-making. Investor decisions generally consider the shadowy side of knowledge management.

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.