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Gigerenzer, Gerd. "The Bias Bias in Behavioral Economics." Review of Behavioral Economics 5, no. 3-4 (2018): 303–36. http://dx.doi.org/10.1561/105.00000092.
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Nkukpornu, Etse, Prince Gyimah, and Linda Sakyiwaa. "Behavioural Finance and Investment Decisions: Does Behavioral Bias Matter?" International Business Research 13, no. 11 (2020): 65. http://dx.doi.org/10.5539/ibr.v13n11p65.
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This paper examines the nexus between behavioural bias and investment decisions in a developing country context. Specifically, this study tests the effect of four behavioural biases (overconfidence, regret, belief, and “snakebite”) on investment decisions. Descriptive statistics and inferential statistics including multiple regression are used to examine the behavioural biases-investment decisions nexus. The study reveals that the four bias have a significant positive and robust relationship with investment decision making. The result also shows that the "snakebite" effect contributes more to the decision making, followed by belief bias then regret bias. Overconfidence bias, however, contributes the least effect on investment decisions. Our contribution confirms the prospect theory and that behavioural bias influences investment decisions in the developing country perspective. 
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Handriani, Eka Handriani. "Behavioral Bias Investors in Indonesia." Jurnal Riset Akuntansi dan Keuangan 13, no. 1 (2025): 1363–80. https://doi.org/10.17509/jrak.v13i1.80576.
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The purpose of this study is to examine the impact of behavioral biases (risk-aversion bias; overconfidence bias; disposition bias; and herding bias) on gender-based Invesment decisions. Also attempts to empirically prove the mediating influence of financial literacy in the relationships between behavioral biases and gender-based Invesment decisions.This study data was collected using a questionnaire from 329 Investors in Indonesia in seven cities, including Jakarta, Semarang, Surabaya, Bandung, Medan, Palembang, and Samarinda. The results reveal that among male Investors, risk-aversion bias and herding bias have a negative and significant impact on the invesmentdecisions; the overconfidence bias has a positive and significant impact on the invesmentdecisions; and however, the disposition bias has no significant. Among female Investors the risk-aversion bias and herding bias have a negative and significant impact on the invesmentdecisions; while the overconfidence bias and disposition bias have no significant impact on the invesmentdecisions. Among the male Investors , the financial literacy also has a significant impact on the influence of overconfidence bias on invesmentdecisions. However, the financial literacy has no significant impact on the remaining three biases, including the risk-aversion bias, disposition bias, and herding bias. Among the female Investors , the financial literacy has a significant impact on all overconfidence bias, risk-aversion bias, disposition bias and herding bias.
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Feldman, Todd. "The Most Destructive Behavioral Bias." Journal of Investing 21, no. 2 (2012): 49–56. http://dx.doi.org/10.3905/joi.2012.21.2.049.
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MENG, Zhenzhen, Fuming XU, Shixiao KONG, Haijun LI, and Peng XIANG. "Ratio Bias in Behavioral Decision." Advances in Psychological Science 21, no. 5 (2013): 886–92. http://dx.doi.org/10.3724/sp.j.1042.2013.00886.
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Patel, Chirag B. "The Most Destructive Behavioral Bias." CFA Digest 42, no. 4 (2012): 15–17. http://dx.doi.org/10.2469/dig.v42.n4.44.
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Stamps, J. A. "Density bias in behavioral ecology." Behavioral Ecology 22, no. 2 (2011): 231–32. http://dx.doi.org/10.1093/beheco/arq174.
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Alpaca Salvador, Hugo Antonio, and Angel Polo Campos. "Behavioral Economics: Behavioral Model Proposal in the HealthSector." SCIÉNDO 26, no. 1 (2023): 13–23. http://dx.doi.org/10.17268/sciendo.2023.002.
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This research proposes a behavioral model that would allow society to modify its behavior towards preventive health, looking for adequate components based on behavioral economics. The investigated problem was: how to modify the current behavior of the users in the health services in Trujillo? The population consisted of patients who used health services before the start of the covid-19 pandemic, being 884,700 people. The methodology used was a cross-sectional descriptive research, divided into four stages: Determination of the level of knowledge in health, Measurement of cognitive bias, Determination of the key factors that generate cognitive bias; and, Structuring of the behavioral model. The results found to elaborate a behavioral proposal were that there is a cognitive bias, mainly in preventive physical health and in the health of physical controls, in turn the factors that must be modified in behavior are: overconfidence, aversion to loss, availability heuristics, anchoring, present bias, ego depletion, and social norms; while the factors that should only be reinforced in the behavioral model are: status quo, framing and affect heuristics
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Vuong, Quan Duc Hoang, and Phuc Quy Dao. "AN EMPIRICAL STUDY OF INDIVIDUAL INVESTORS’ BEHAVIORAL BIASES IN THE VIETNAMESE STOCK MARKET." Science and Technology Development Journal 15, no. 1 (2012): 5–13. http://dx.doi.org/10.32508/stdj.v15i1.1779.
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The study aims to determine individual investors’ behavioral biases at individual level in the Vietnamese stock market and investigate the relationships between mutual behavioral biases, between demographic variables and behavioral biases, between stock investment variables and behavioral biases. This is a quantitative research in behavioral finance with the survey conducted in forms of questionnaire. Each question is a problem which requires investors to make decision. The research finds out that there are specific behavioral biases which influence investors’ investment decisions. Furthermore, there are relationships between gender and illusion of control bias, gender and optimism bias, gender and self-control bias. We also realize relationships between average value per trading times and investment experience, average value per trading times and loss aversion bias, trading frequency and optimism bias, investment experience and optimism bias, monthly income and optimism, age and cognitive dissonance bias. Our findings confirm relationships between mutual behavioral biases mentioned in behavioral finance such as relationships between framing bias and mental accounting bias, illusion of control bias and overconfidence bias. Additionally, we find out relationships between ambiguity aversion bias and confirmation bias.
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De Houwer, Jan. "Implicit Bias Is Behavior: A Functional-Cognitive Perspective on Implicit Bias." Perspectives on Psychological Science 14, no. 5 (2019): 835–40. http://dx.doi.org/10.1177/1745691619855638.
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Implicit bias is often viewed as a hidden force inside people that makes them perform inappropriate actions. This perspective can induce resistance against the idea that people are implicitly biased and complicates research on implicit bias. I put forward an alternative perspective that views implicit bias as a behavioral phenomenon. more specifically, it is seen as behavior that is automatically influenced by cues indicative of the social group to which others belong. This behavioral perspective is less likely to evoke resistance because implicit bias is seen as something that people do rather than possess and because it clearly separates the behavioral phenomenon from its normative implications. Moreover, performance on experimental tasks such as the Implicit Association Test is seen an instance of implicitly biased behavior rather than a proxy of hidden mental biases. Because these tasks allow for experimental control, they provide ideal tools for studying the automatic impact of social cues on behavior, for predicting other instances of biased behavior, and for educating people about implicitly biased behavior. The behavioral perspective not only changes the way we think about implicit bias but also shifts the aims of research on implicit bias and reveals links with other behavioral approaches such as network modeling.
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Anurag, Shukla, Dadhich Manish, Vaya Dipesh, and Goel Anuj. "Impact of Behavioral Biases on Investors' Stock Trading Decisions: A Comprehensive Quantitative Analysis." Indian Journal of Science and Technology 17, no. 8 (2024): 670–78. https://doi.org/10.17485/IJST/v17i8.2845.
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Abstract <strong>Objective:</strong> This paper aims to investigate the impact of specified behavioral biases on investors' stock trading decisions in North India. It has been observed that most of the research works are based on financial theories, which affect investment decisions. But besides the theories nowadays, behavioral biases also play an important role in investment decisions, which was less focused in the previous literature. <strong>Methods:</strong> The study used primary data collected from a sample from North Indian States (Uttar Pradesh, Delhi, Haryana, and Punjab) through a structured questionnaire to analyze the impact of specified behavioral biases on investors' stock trading decisions. We used structural equation modelling to find out the significant impact of behavioral biases on stock trading and investment decisions. <strong>Findings:</strong> The investigation determined that the majority of the designated cognitive biases, such as the Overconfidence Bias, the Representativeness Bias, and the Herding Bias, exert a significant influence on the decisions about stock trading and investment made by investors. <strong>Novelty:</strong> The ample research in this domain has primarily occurred in various countries, with only a limited number of studies conducted specifically at the Indian level. Nevertheless, based on the literature review, it is evident that this study is groundbreaking in North India. The objective of this research is to enhance the effectiveness of financial advisors by gaining a deeper understanding of the psychological aspects of clients. This, in turn, will aid in developing portfolios tailored to individual behavior, aligning with client preferences. Recognizing and addressing behavioral biases is crucial for individual investors as they strive to make informed and successful financial decisions. <strong>Keywords:</strong> Behavioral Biases, Overconfidence (OC) bias, Representativeness Bias (RB), Herding Bias (HB), Structural Equation Modelling
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Ko, Eun-Ha, and Sok-Tae Kim. "The Effect of the Behavioral Biases of Korean Invertors on Performance with Financial Literacy as a Moderator." International Academy of Global Business and Trade 18, no. 4 (2022): 1–12. http://dx.doi.org/10.20294/jgbt.2022.18.4.1.
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Purpose – The purpose of this study is to analyze how the behavioral characteristics of Korean individual investors affect investment performance.
 Design/Methodology/Approach – Through the survey method, we tried to examine the behavioral bias characteristics and behavioral bias investment decisions on performance during the COVID-19 period. Multiple regression and SPSS PROCESS were used to find the effect of the behavioral characteristics and behavioral decisions on performance with financial literacy as the moderator.
 Findings – As a result of multiple regression analysis, it was found that among the biased investment characteristics, overconfidence and mental accounting statistically affect investment results. In the analysis through the SPSS PROCESS model, the level of financial literacy was found to be significant as a moderating variable, and it was also found that biased investment decision plays a role as a mediating parameter in investment performance.
 Research Implications – This study is meaningful in providing insight into the behavioral investment characteristics of individual investors by presenting an empirical analysis of the behaviorally biased characteristics and behaviorally biased investment decisions of individual investors on investment performance in Korea.
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Sullivan, Edgar J. "Behavioral Bias, Valuation, and Active Management." CFA Digest 30, no. 1 (2000): 27–28. http://dx.doi.org/10.2469/dig.v30.n1.610.
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Hsu, Yuan-Lin. "Financial advice seeking and behavioral bias." Finance Research Letters 46 (May 2022): 102505. http://dx.doi.org/10.1016/j.frl.2021.102505.
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Scott, James, Mark Stumpp, and Peter Xu. "Behavioral Bias, Valuation, and Active Management." Financial Analysts Journal 55, no. 4 (1999): 49–57. http://dx.doi.org/10.2469/faj.v55.n4.2284.
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Lee, Carol S., and Sarah A. Hayes-Skelton. "Social Cost Bias, Probability Bias, and Self-Efficacy as Correlates of Behavioral Action in Social Anxiety." Behavior Modification 42, no. 2 (2017): 175–95. http://dx.doi.org/10.1177/0145445517720447.
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The present study investigated the role of social cost bias, probability bias, and self-efficacy as correlates of behavioral action in a nonclinical sample of 197 individuals, using a series of vignettes and self-report measures. The findings indicated that, as hypothesized, social cost bias, probability bias, and self-efficacy were associated with social anxiety. While social anxiety was associated with behavioral action, the three cognitive factors were associated with behavioral action above and beyond the contribution of social anxiety. However, contrary to the hypothesis, self-efficacy was the only cognitive factor directly associated with behavioral action when all variables were in the model. This information has implications for potential methods and target mechanisms for increasing client engagement with exposures and behavioral experiments in treatments for social anxiety.
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Willie Kurnijanto, Aldo, Joni Joni, Karen Videlia Sumbodo, Liliana Inggrit Wijaya, and Bertha Silvia Sutejo. "Influence of Behavioral Bias on Investment Decision with Risk Perception as a Mediating Variable: A Study on Generation Z at the Indonesia Stock Exchange." Dinasti International Journal of Economics, Finance & Accounting 5, no. 6 (2025): 5741–52. https://doi.org/10.38035/dijefa.v5i6.3643.
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This study uses structural equation modeling to examine the direct and indirect relationships between behavioral biases and investment decisions with the mediating role of risk perception. This study was conducted among Generation Z individual investors who have been investing on the Indonesia Stock Exchange for several months to years. The behavioral biases examined include overconfidence bias, herding bias, and loss aversion bias, with data from 300 respondents collected through purposive sampling. The results show that risk perception mediates the relationship between overconfidence bias, herding bias, and loss aversion bias with investment decisions. Herding bias and loss aversion bias were found to have a direct relationship with risk perception. In addition, it was also found that herding bias, loss aversion bias, and risk perception have a direct relationship with investment decisions. This research is essential for investors to make more rational investment decisions and improve investment performance by recognizing the risks associated with behavioral biases. The increasing number of retail investors and Generation Z on the Indonesia Stock Exchange demands sound investment decisions. Behavioral biases often trigger irrational decisions and errors in portfolio management, while risk perception can strengthen or weaken the impact of behavioral biases on investment decisions. This study contributes theoretically to investment and behavioral finance, particularly regarding the mediating effect of risk perception.
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Bashir, Taqadus, Faisal Mehmood, and Altamash Khan. "Comforting Investments are Rarely Profitable: Impediments in Investor Decision Making." Global Social Sciences Review IV, no. II (2019): 51–59. http://dx.doi.org/10.31703/gssr.2019(iv-ii).07.
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This research aims at testing and confirming existence of selected behavioral biases of investors that affect their decisions. Five behavioral biases affecting irrational behavior of investors were selected: overconfidence bias, illusion of control bias, confirmation bias and recency bias and optimism bias. Primary data was collected through a questionnaire from 300 investors from banks, insurance companies, stock exchanges etc. The results were obtained by employing a correlation and regression analysis for the presence of behavioral biases and to detect degrees of their influence on decision making. Correlation results indicate moderate association between behavioral biases and decisions of investors. Outcome of the research indicates that while making financial decisions investors are moderately affected by behavioral biases.
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Taqadus, Bashir. "Comforting Investments are Rarely Profitable: Impediments in Investor Decision Making." Global Social Sciences Review 4, no. 2 (2019): 51–59. https://doi.org/10.5281/zenodo.4381138.
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This research aims at testing and confirming existence of selected behavioral biases of investors that affect their decisions. Five behavioral biases affecting irrational behavior of investors were selected: overconfidence bias, illusion of control bias, confirmation bias and recency bias and optimism bias. Primary data was collected through a questionnaire from 300 investors from banks, insurance companies, stock exchanges etc. The results were obtained by employing a correlation and regression analysis for the presence of behavioral biases and to detect degrees of their influence on decision making. Correlation results indicate moderate association between behavioral biases and decisions of investors. Outcome of the research indicates that while making financial decisions investors are moderately affected by behavioral biases.
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Taqadus, Bashir, Mehmood Faisal, and Khan Altamash. "Comforting Investments are Rarely Profitable: Impediments in Investor Decision Making." GLOBAL SOCIAL SCIENCES REVIEW (GSSR) IV, no. II (2019): 71–82. https://doi.org/10.31703/gssr.2019(IV-II).07.
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This research aims at testing and confirming existence of selected behavioral biases of investors that affect their decisions. Five behavioral biases affecting irrational behavior of investors were selected: overconfidence bias, illusion of control bias, confirmation bias and recency bias and optimism bias. Primary data was collected through a questionnaire from 300 investors from banks, insurance companies, stock exchanges etc. The results were obtained by employing a correlation and regression analysis for the presence of behavioral biases and to detect degrees of their influence on decision making. Correlation results indicate moderate association between behavioral biases and decisions of investors. Outcome of the research indicates that while making financial decisions investors are moderately affected by behavioral biases.
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Jain, Nidhi, and Bikrant Kesari. "Evaluating The Connection of Behavioral Biases and Investment Decisions of Equity Market Investors Using SEM Approach." Tobacco Regulatory Science 7, no. 5 (2021): 2766–76. http://dx.doi.org/10.18001/trs.7.5.1.46.
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Objective: The key objective of the paper is to study the magnitude of the disparity in actions between stock holders for short-term and long-term. Methods: Investor traits and how the judgement on investments and behavioral bias are interconnected are contrasted by using a systemic model, as well as to compare relative behavioral bias variations including Framing Bias, Endowment Bias, Representative Bias, Cognitive Dissonance Bias, Self-Control Bias and Overconfidence Bias. Distinguishing evidence of behavioral characteristics that are normally related to investment venture helps to provide assessments and confine trading techniques. Results: Between July 2020 and August 2020, the cognitive effect of investor decision-making is contrasted via test review of 300 substantive responders from deliberate Indian stock market investors. Taking into account the structural equation modelling (SEM), a route study is carried out of the manner in which stock investment and proposed behavioral inclinations are concomitant. Conclusions: Observational outcomes suggest that the systemic path model deliberately correlates with the survey content, demonstrating the influence of behavioral discrimination in decision-making for individual investments. Our results also indicate that short-term and long-term investors’ behavioral patterns vary substantially.
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Flyvbjerg, Bent. "Top Ten Behavioral Biases in Project Management: An Overview." Project Management Journal 52, no. 6 (2021): 531–46. http://dx.doi.org/10.1177/87569728211049046.
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Behavioral science has witnessed an explosion in the number of biases identified by behavioral scientists, to more than 200 at present. This article identifies the 10 most important behavioral biases for project management. First, we argue it is a mistake to equate behavioral bias with cognitive bias, as is common. Cognitive bias is half the story; political bias the other half. Second, we list the top 10 behavioral biases in project management: (1) strategic misrepresentation, (2) optimism bias, (3) uniqueness bias, (4) the planning fallacy, (5) overconfidence bias, (6) hindsight bias, (7) availability bias, (8) the base rate fallacy, (9) anchoring, and (10) escalation of commitment. Each bias is defined, and its impacts on project management are explained, with examples. Third, base rate neglect is identified as a primary reason that projects underperform. This is supported by presentation of the most comprehensive set of base rates that exist in project management scholarship, from 2,062 projects. Finally, recent findings of power law outcomes in project performance are identified as a possible first stage in discovering a general theory of project management, with more fundamental and more scientific explanations of project outcomes than found in conventional theory.
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Valsan, Calin. "B is for Bias." International Journal of Applied Behavioral Economics 3, no. 2 (2014): 35–47. http://dx.doi.org/10.4018/ijabe.2014040103.
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Standard economic theory assumes rational agents. Individuals are expected to have rational expectations and constantly optimize their choices. Modern economic and financial theory is build under the assumption of rationality. There is plenty of evidence from psychology, however, that individuals are biased and rely heavily on heuristics in order to make decisions. Yet, this is not a mere fluke, a behavioral oddity. Because the social and economic environment in which individuals evolve is complex, behavioral biases represent evolutionary adaptations allowing economic agents to deal with undecidability and computational irreducibility.
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Effendi, Kharisya Ayu, and Shendy Amalia. "MBTI personality type and financial behavioral bias." International Journal of Social and Administrative Sciences 9, no. 2 (2024): 64–77. https://doi.org/10.55493/5051.v9i2.5236.
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Studies on behavioral financial theory found that the individual investment decision process involves many behavioral biases. This behavioral bias can cause investors to deviate from rational decision-making. The purpose of this study is to see whether there is an influence of gender factors on financial behavioral biases in this study, namely overconfidence bias, herding, and regret aversion. Then this study also aims to see whether MBTI personality types influence financial behavioral biases in this study, namely overconfidence bias, herding, and regret aversion. This study aims to identify the relationship between gender variables, MBTI personality assessments, and financial behavioral biases in investors in Indonesia. To conduct this study, a structured questionnaire was given to 230 respondents at the researcher.populix.co.id as the primary data collection page that includes questions related to gender variables, overconfidence bias, herding bias, regret aversion bias, and MBTI personality assessment. Of the 230 respondents, 182 respondents were accepted and met the analysis requirements. The findings obtained were that the gender factor that had a significant effect on this study was only on overconfidence bias while herding and regret aversion did not have a significant effect. Then the MBTI personality type significantly influenced the three financial behavior biases.
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Kamoune, Assia, and Nafii Ibenrissoul. "Behavioral biases influencing the investment decision-making process of institutional investors." African Scientific Journal Vol 3, N°18 (2023): 073. https://doi.org/10.5281/zenodo.8013227.
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<strong>Résumé :</strong> Dans la vie quotidienne, les gens doivent prendre plusieurs décisions, grandes ou petites. Peu de choix sont faciles et semblent simples, tandis que d'autres sont complexes et nécessitent un processus en plusieurs étapes pour prendre les bonnes décisions. Cette étude évalue l'impact des biais comportementaux auxquels les investisseurs institutionnels doivent faire face au moment de la prise de décision d’investissement. Le biais comportemental est défini comme un modèle de variation du jugement qui se produit dans des situations particulières, ce qui peut parfois conduire à une altération de la perception, à un jugement inexact, à une interprétation illogique ou à ce que l'on appelle généralement l'irrationalité. La prise de décision est le processus mental ou cognitif qui aboutit à la sélection d'un plan d'action parmi plusieurs situations alternatives. Chaque processus de prise de décision se termine par un choix final. L'objectif de cette étude est de préciser l’impact des biais comportementaux bien précisément ; le biais d'excès de confiance, l’effet de troupeau, le biais de représentativité, et le biais domestique sur la prise de décision d’investissement chez les investisseurs institutionnels. Tout d’abord, nous allons présenter les biais émotionnels et cognitifs, ensuite, nous allons expliquer théoriquement le processus de la prise de décision d’investissement et les stratégies d’investissement des investisseurs institutionnels, pour pouvoir finalement définir l’impact des biais comportementaux les plus dominants sur la prise de décision d’investissement des investisseurs institutionnels à partir des études antérieures. <strong>Mot clés :</strong> Biais comportementaux, Biais d'excès de confiance, Effet de troupeau, Biais de représentativité, Biais domestique, Investisseurs institutionnels, Décision d’investissement. <strong>Abstract:</strong> Nowadays people must take variety of large or small decisions. Some choices are easy and simple, while others are complex and require a multi-step approach in making the right decisions. This study evaluates the impact of behavioral biases that institutional investors must face while making investment decision. Behavioral bias is defined as a pattern of variation in judgment that occurs situations, which may sometimes lead to perceptual alteration, inaccurate judgment, illogical interpretation, or what is largely called irrationality. Decision making is the mental or the cognitive process that results in the selection of a course of action among several alternative situations. Every decision-making process comes to its end with a final choice. The aim of this study is to specify the impact of behavioral biases such as overconfidence bias, herding bias, representativeness, and home bias on investment decision making among institutional investors. First, we are going to present emotional and cognitive biases, then we will try to theoretically explain the processes of investment decision making and investment strategies of the institutional investors, and finally we will evaluate and define the impact of these behavioral biases on the investment decision making of the institutional investors following the previous studies in literature. <strong>Keywords: </strong>behavioral biases, overconfidence bias, herding bias effect, representativeness, home bias, institutional investors, investment decision.
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Rana, Bikash. "Investor Bias: A Case of Nepalese Investor Perspective." Lumbini Journal of Business and Economics 11, no. 1 (2023): 116–30. http://dx.doi.org/10.3126/ljbe.v11i1.54321.
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Behavioral finance incorporates the field of psychology into finance and studies the behavior of individual which are guided by behavioral biases. The current study aims to examine the behavioral biases which can be seen in Nepalese stock investor and studies if the behavioral biases affect the financial decisions of investor or not. The study tested the following behavioral bias: Loss Aversion, Overconfidence, Optimism, Mental Accounting, Illusion of Control, Confirmation and Status Quo Bias. The data was collected from 136 respondents. The sample size was set as minimum of 120 on the basis of rule of thumb of Roscoe (1975). Likewise, four in-depth interviews were taken in order to collect response from institutional investor. The number of interviews for institutional investor was determined on the basis of Rao soft Sample Size Calculator. The study showed that Loss aversion, overconfidence and confirmation bias were correlated with financial decision making of the investor. The correlations were significant. But the regression analysis showed that there is influence of loss aversion, overconfidence and optimism bias in the financial decisions. Confirmation bias did not have significant relationship. Also, the behavioral bias as a whole affects the financial decisions. Likewise, the study also showed that status quo bias and mental accounting bias are prevailed in the institutional investor. These biases also influenced the individual investor financial decisions. As a whole the study shows that Nepalese investor are influenced by behavioral biases.
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Schulz, Bastian. "Behavioral Finance and how its Behavioral Biases Affect German Investors." ACTA VŠFS 17, no. 1 (2023): 39–59. http://dx.doi.org/10.37355/acta-2023/1-03.
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The growing discipline of behavioral finance has identified several biases that significantly impact individual investors' actions. This paper aims to evaluate the influence of behavioral biases on investing decision-making among German investors. A questionnaire is created, and survey results from 342 investors are collected. Three behavioral biases, namely overconfidence, herding, and anchoring behavior, have been examined in this study. Moreover, it was determined if gender influences these biases among German investors. The findings indicate that male German investors are more susceptible to overconfidence and anchoring bias than female German investors. However, women are more likely than males to fall victim to the herding bias. Overall findings show that individual investors are prone to psychological mistakes.
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Hidajat, Taofik. "BEHAVIOURAL BIASES IN BITCOIN TRADING." Fokus Ekonomi : Jurnal Ilmiah Ekonomi 14, no. 2 (2019): 337–54. http://dx.doi.org/10.34152/fe.14.2.337-354.
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This paper aims to propose some behavioural biases of trading in Bitcoin. It is review literature in the areas of behavioural finance that address issues related to Bitcoin to underpin the conceptual model. A conceptual model for understanding the behavioural bias that affects investing in cryptocurrency is proposed. The biases are herding, optimism, overconfidence, confirmation bias, loss aversion, and gamblers’ fallacy. This paper ought to fill the research gap on cryptocurrency from the behavioral perspective. This paper implies that prices and Bitcoin transactions are more determined by psychological factors.
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Rosyidah, Umu, and Heri Pratikto. "The role of behavioral bias on financial decision making: a systematic literature review and future research agenda." Journal of Enterprise and Development 4, no. 1 (2022): 156–79. http://dx.doi.org/10.20414/jed.v4i1.5102.
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Purpose — This paper aims to analyze current research trends, identify theoretical perspectives, and identify research topics of behavioral bias in financial decision-making in the future.Research method — To perform bibliometric analysis, this article uses a systematic literature review, as well as content analysis. This article uses a total of 51 publications between 2018 and 2022 as the sample for the literature review, directed by PRISMA. The tool used in analyzing bibliometrics is VOSviewer. Meanwhile, content analysis is conducted to build theoretical perspectives and proposed future research agendas.Result — This systematic review explains the number of articles per year, most influential articles, leading journals, leading countries, leading authors, important keywords, and research cluster networks. Besides, this article also discovers seven behavioral biases that can be analyzed to gain a theoretical perspective on behavioral bias. The seven behavioral biases are Heuristic Bias, Self-Attribution Bias, Framing Bias, Herding Bias, Aversion Bias, Disposition Effect, and Overconfidence Bias,. In the scientific mapping analysis, important keywords are obtained, and the author's research cluster network is to discover topics that rarely researched to be offered in future research.Recommendation/significance/contribution — In contrast to previous studies of behavioral bias, which were dominated by survey-based research, this paper provides a different reference by using a systematic literature review method that provides coverage of the main research issues and theoretical arguments about behavioral bias in financial decisions. In addition, this paper offers new ideas about potential research fields by identifying studies in developing countries that are still rarely carried out compared to developed countries.
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Walker, Elaine, and Eugene Emory. "Commentary: Interpretive Bias and Behavioral Genetic Research." Child Development 56, no. 3 (1985): 775. http://dx.doi.org/10.2307/1129766.
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Gokhale, Jayendra, Carol Horton Tremblay, and Victor J. Tremblay. "Misvaluation and Behavioral Bias in Financial Markets." Journal of Behavioral Finance 16, no. 4 (2015): 344–56. http://dx.doi.org/10.1080/15427560.2015.1095756.
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Tong, Jordan, Daniel Feiler, and Richard Larrick. "A Behavioral Remedy for the Censorship Bias." Production and Operations Management 27, no. 4 (2017): 624–43. http://dx.doi.org/10.1111/poms.12823.
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Zhang, Xixuan. "The Role of Behavioral Bias in Investment Outcomes." Highlights in Business, Economics and Management 15 (June 28, 2023): 99–104. http://dx.doi.org/10.54097/hbem.v15i.9323.
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Investment decisions are made by individuals who are subject to behavioral biases. The biases could lead to a significant impact on the outcome of investments. This research paper aims to investigate the role of behavioral biases in investment decisions and outcome. The study draws on the theories of Rational Behavioral Finance, which recognizes that human behavior is influenced by both rational and irrational factors. The paper reviews several key behavioral biases that can affect investment decisions, including loss aversion, endowment bias, framing, overconfidence, and the illusion of control. The analysis of these biases is based on the context of different investment settings, including stock markets, mutual funds, and real estate. The paper introduces the significance of each bias, and how they can lead to suboptimal investment decisions. The latter part of the paper highlights how the biases can be addressed to improve the outcome of investments. Eventually, the research paper concludes that behavioral biases can significantly impact investment outcomes, but the application of Rational Behavioral Finance theories and strategies can mitigate the impact of these biases.
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Jain, Jinesh, Nidhi Walia, and Sanjay Gupta. "Evaluation of behavioral biases affecting investment decision making of individual equity investors by fuzzy analytic hierarchy process." Review of Behavioral Finance 12, no. 3 (2019): 297–314. http://dx.doi.org/10.1108/rbf-03-2019-0044.
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Purpose Research in the area of behavioral finance has demonstrated that investors exhibit irrational behavior while making investment decisions. Investor behavior usually deviates from logic and reason, and consequently, investors exhibit various behavioral biases which impact their investment decisions. The purpose of this paper is to rank the behavioral biases influencing the investment decision making of individual equity investors from the state of Punjab, India. This research would provide valuable insight into the different behavioral biases to investors and other participants of the capital market and help them in improving investment decisions. Design/methodology/approach The research is conducted on the individual equity investors of Punjab, India. Fuzzy analytic hierarchy process was applied to rank the factors influencing the decision making of individual equity investors of Punjab. The primary factors considered for the study are overconfidence bias, representative bias, anchoring bias, availability bias, regret aversion bias, loss aversion bias, mental accounting bias and herding bias. Findings The three most influential criteria were herding bias, loss aversion bias and overconfidence bias. The five most influential sub-criteria were “I readily sell shares that have increased in value (C61),” “News about the company (Newspapers, TV and magazines) affects my investment decision (C84),” “I invest each element of my investment portfolio separately (C71)” and “I usually hold loosing stock for long time, expecting trend reversal (C52).” Research limitations/implications Although sample survey conducted in the present study was based on a limited sample selected from a particular area that truly represented the total population, it is considered as the limitation of this study. Practical implications The outcome of this research provides investors with a better understanding of behavioral biases that influence their decision making. This study provides them a guideline on different behavioral biases that they should consider while making investment decisions. Originality/value The research model is based on the available literature on behavioral finance and the research results and findings would add value to the existing knowledge base.
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Morales, Santiago, Natalie V. Miller, Sonya V. Troller-Renfree, et al. "Attention bias to reward predicts behavioral problems and moderates early risk to externalizing and attention problems." Development and Psychopathology 32, no. 2 (2019): 397–409. http://dx.doi.org/10.1017/s0954579419000166.
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AbstractThe current study had three goals. First, we replicated recent evidence that suggests a concurrent relation between attention bias to reward and externalizing and attention problems at age 7. Second, we extended these findings by examining the relations between attention and behavioral measures of early exuberance (3 years), early effortful control (4 years), and concurrent effortful control (7 years), as well as later behavioral problems (9 years). Third, we evaluated the role of attention to reward in the longitudinal pathways between early exuberance and early effortful control to predict externalizing and attention problems. Results revealed that attention bias to reward was associated concurrently and longitudinally with behavioral problems. Moreover, greater reward bias was concurrently associated with lower levels of parent-reported effortful control. Finally, attention bias to reward moderated the longitudinal relations between early risk factors for behavioral problems (gender, exuberance, and effortful control) and later externalizing and attention problems, such that these early risk factors were most predictive of behavioral problems for males with a large attention bias to reward. These findings suggest that attention bias to reward may act as a moderator of early risk, aiding the identification of children at the highest risk for later behavioral problems.
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Feng, Xinhui. "Gender Differences in Behavioral Bias and Influencing Investment Decisions." Lecture Notes in Education Psychology and Public Media 81, no. 1 (2025): 218–23. https://doi.org/10.54254/2753-7048/2025.21108.
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This study explores the impact of behavioral biases in gender differences on investment decisions through a literature review and case study. The traditional theoretical assumption in finance is that investors are rational. They are able to make optimal decisions based on all available information. However, real investors are often influenced by emotions, biases, and cognitive errors that lead to irrational decisions. Therefore, researchers have introduced psychological studies into traditional finance. Psychological studies have shown that people are often influenced by cognitive biases in the decision-making process. These biases are particularly significant on investment decisions, such as overconfidence bias, overreaction bias, regret avoidance bias, self-attribution bias, framing effect bias, and reference point bias. Behavioral finance assumes that individual investment decisions are imperfectly rational. It has been found that gender differences have a significant impact in behavioral biases, thereby affecting the behavioral decisions of investors. Among these common cognitive biases, risk aversion, overconfidence, anchoring effect, and loss aversion are more significant for gender differences in investment decisions.
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Prayogi, Prayogi, Fitriaty Fitriaty, and Musnaini Musnaini. "Pengaruh Financial Literacy dan Sosiodemografi terhadap Keputusan Investasi Individu dengan Bias Perilaku Sebagai Variabel Intervening." Jurnal Ilmiah Universitas Batanghari Jambi 23, no. 2 (2023): 2493. http://dx.doi.org/10.33087/jiubj.v23i2.3968.
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This study entitled the effect of financial literacy and sociodemography on individual investment decisions with behavioral bias as an intervening variable. The purpose of this study was to analyze the direct and indirect effects of financial literacy and sociodemography on investment decisions through behavioral bias. The research method used is a quantitative descriptive analysis method with the Structural Equation Modeling (SEM-PLS) model using SmartPLS. Based on the results of the study, it shows that financial literacy has no significant effect on the individual investment decisions of Jambi High Court employees. Sociodemography has a significant effect on the individual investment decisions of Jambi High Court employees. Financial literacy has no significant effect on individual behavioral biases of Jambi High Court employees. Sociodemography has no significant effect on individual behavioral biases at the Jambi High Court. Behavioral bias has a significant effect on the individual investment decisions of Jambi High Court employees. Financial literacy does not have a significant effect on investment decisions through behavioral bias. Sociodemographics have a significant influence on investment decisions through behavioral biases.
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Ahmed, Faiza, Maria Siddiqui, Muhammad Qaveem Akhtar Khan, and Asadullah Lakho. "A Qualitative Study of Behavioral Biases Among Pakistani Investor Decisions." Bulletin of Business and Economics (BBE) 12, no. 4 (2023): 1–5. http://dx.doi.org/10.61506/01.00066.
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The basic purpose of this study is to highlight the importance of behavioural biases in individual investors' decisions that cause deviation from rationality. It also helps them to accelerate their abilities in investment decision-making. This study used semi-structured open-ended questions to explore the behavioural bias in six individual investors of the Pakistan stock market. The thematic content analysis is used to analyze the data. This study explores eight behavioural biases of the individual investor in the Pakistan stock market and process it does not seem that all the investors will suffer from all the behavioural biases simultaneously. Their decision is based not only on quantitative analysis but also influenced by cognitive, emotional, and social biases. They depend on other sources of information before investing in the stock market. This study focuses on behavioural biases of individual investors of the Pakistan stock market so their results can not be generalized to institutional investors, real estate investors, or any other geographical area due to culture differences, education level, values, and financial structure. As this study explores only individual behavioural bias it leaves many areas that are unexplained for further research like institutional investors behavioural bias, real estate investors behavioural bias with more sample size. The practical implications are it is helpful for companies, policymakers, and securities issuers can observe the investor interest and behaviour before issuing securities into the market. As far as the social implication is concerned it is good for investors to understand the several behavioral biases and make sound investment decisions that mitigate their risk. This paper explores the concept of behavioural biases in individual decision-making and adds value to the existing literature on behavioural finance.
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Afzal, Muhammad, Abdul Rasheed, and Khalil Ur Rehman. "Evaluation of Behavioral Biases and Investment Decision: An Evidence from Pakistan Stock Exchange (PSX)." Bulletin of Business and Economics (BBE) 12, no. 4 (2023): 126–34. http://dx.doi.org/10.61506/01.00094.
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Investors act irrationally while making decisions, according to research in the subject of behavioral finance. The main goal of this study is to assess the behavioral biases that influence the choices made by individual equities investors from Punjab. For investors, agents, and other market participants, this study is useful and aids in making better investment decisions. The study takes into account the private investors who buy common stocks in the Pakistani province of Punjab. The Fuzzy Analytical Hierarchy Process (F-AHP) is used to examine the behavioral biases that influence certain common stock investors' choices. The familiarity bias, optimism bias, herding bias, mental accounting bias, loss aversion bias, regret aversion bias, availability bias, anchoring bias, representative bias, and overconfidence bias are the most prevalent behavioral biases taken into account in this study. Mental accounting bias, herding bias, anchoring bias, and representational prejudice were the four factors that had the greatest impact. "I prefer to invest in the well-known companies that have wider media coverage (C101)" was one of the top six sub-criteria. The financial effects of my choices are better than I anticipated (C96). "The financial ramifications of my choices turn out to be immediate" (C95). The company's news (from newspapers, television, and magazines) influences my investment choice (C84). “My investment for purchasing new stock is totally based on information released regarding the stock (C43).” “I have particular skills and experience for decision making (C13).”
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Stone, Brian J. "Bias in Learning Disabilities Placement." Psychological Reports 72, no. 3_suppl (1993): 1243–47. http://dx.doi.org/10.2466/pr0.1993.72.3c.1243.
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A nationally representative sample of 20,614 eighth grade students was examined for bias in placement decisions for children said to have learning disabilities. Factors investigated for bias were race, sex, and socioeconomic status. Path analysis showed significant and direct paths from sex and race to placement, controlling for socioeconomic status, academic ability, and behavioral competency. Boys were overrepresented in such classes beyond what their somewhat lower academic and behavioral competencies would predict. Caucasians were similarly overrepresented controlling for other variables in the model. It appears that boys and Caucasians are overrepresented in learning disabilities placements on a national scale even when other contributing factors are controlled.
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Beatrice, Vania, Werner R. Murhadi, and Arif Herlambang. "The effect of demographic factors on behavioral biases." Jurnal Siasat Bisnis 25, no. 1 (2021): 17–29. http://dx.doi.org/10.20885/jsb.vol25.iss1.art2.
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The purpose of this study was to examine the influence of demographic factors such as gender, age, education, occupation, income, and investment experience on investor behavior bias such as overconfidence bias, disposition effects, herding bias, and mental accounting. This type of research was causal research with a quantitative approach, and the analytical method used was the analysis of SEM (structural equation modeling). This research was conducted by distributing questionnaires to investors listed on the Indonesia Stock Exchange with a minimum age of 17 years. The results showed that overconfidence bias was influenced by investment experience while disposition effect was influenced by age, income level, and investment experience. Herding bias was influenced by age and occupation while mental accounting was influenced by income level.
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Zhang, Lujia. "Research on the Heuristic Bias in Behavioral Economics." Advances in Economics, Management and Political Sciences 62, no. 1 (2023): 129–32. http://dx.doi.org/10.54254/2754-1169/62/20231333.
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Behavioral economics is a branch of economics. It studies people's decision-making patterns and behavioral principles when making decisions. Behavioral economics has penetrated into people's lives, and heuristics are everywhere. This paper shows several classifications and experimental investigations of heuristic bias in behavioral economics. It is widely believed that heuristic bias means that when people want to judge a complex, fuzzy, and uncertain event, they often take some shortcut in thinking due to the lack of effective methods, such as relying on past experience, analyzing and processing past experience, getting inspiration, and then making judgments using the inspiration. However, through literature reading and analysis, it can be found that people don't always make such choices when faced with problems, or they stay rational.
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Geng, Hao. "Exploring How Market Sentiment Affects Investor Behavioral Bias." Law and Economy 3, no. 12 (2024): 46–50. https://doi.org/10.56397/le.2024.12.07.
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The purpose of this paper is to explore how market sentiment affects investor behavioral biases. By constructing a theoretical model, the paper analyzes how changes in market sentiment can lead to different behavioral biases by affecting investors’ information processing, risk perception, and decision-making framework. The article introduces behavioral finance theories, such as prospect theory and overconfidence, to explain how market sentiment shapes investors’ decision-making process. Through case studies, including the analysis of the discount rate of closed-end funds and the implied volatility of subscription warrants in the Chinese securities market, the paper reveals the close connection between market sentiment and investor behavioral biases. The findings suggest that fluctuations in market sentiment can significantly affect investors’ behavioral biases, which in turn have an impact on asset pricing and market volatility. The research in this paper not only provides new perspectives for understanding market dynamics, but also provides valuable guidance for investors and policy makers. Finally, the paper discusses the limitations of the study and possible directions for future research.
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Afroh, Ibna Kamilia Fiel, and Achmad Hasan Hafidzi. "Sharia stock investment decisions: Sharia stock literacy and risk factors and their relations with behavioral bias." Journal of Accounting and Investment 25, no. 1 (2024): 231–48. http://dx.doi.org/10.18196/jai.v25i1.20534.
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Research aims: This study aims to analyze the influence of Sharia stock literacy and risk factors on Sharia stock investment decisions with behavioral bias as an intervening variable.Design/Methodology/Approach: The population was investors in East Java Province who invested in Sharia stock. The sample for this research was 500 respondents. The analysis employed was the Structural Equation Model.Research findings: The impact of Sharia stock literacy on both Sharia stock literacy and investor behavioral bias was positive. Sharia stock investment decisions were adversely impacted by risk factors. Additionally, risk factors had a detrimental impact on investor behavioral bias. Behavioral bias yielded a favorable impact on the decision-making process for investing in Sharia-compliant stocks. Through behavioral bias, Sharia stock literacy positively affected Sharia stock investment decisions. Meanwhile, risk factors obtained a negative effect on Sharia stock investment decisions through behavioral bias.Theoretical contribution/Originality: This research contributes to Sharia stock investment decisions and provides empirical evidence of Sharia stock investment decisions concerning Sharia stock literacy, risk factors, and behavioral biases.Practitioner/Policy implication: This research contributes to investors' ability to determine investment decisions in Sharia stock.Research limitation/Implication: The limitation of this research is that independent variables only used two components of Sharia stock investment decision, i.e., Sharia stock literacy and risk factors. Hence, the level of influence of the independent variables on the dependent was small.
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Anastasia, Njo, and Steve Kayne. "Pengaruh personality traits pada cognitive bias dalam pengambilan keputusan investasi saham." Jurnal Psikologi Sosial 22, no. 1 (2024): 18–30. http://dx.doi.org/10.7454/jps.2024.04.
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Kepribadian dan perilaku dalam diri investor menjadi pijakan dalam pengambilan keputusan investasi untuk mencapai tujuan finansial. Penelitian ini bertujuan menguji hubungan personality traits (agreeableness, extraversion, conscientiousness, neuroticism, openness) dan behavioral bias (disposition effect, herding behavior, overconfidence) pada diri investor. Pemilihan sampel menggunakan teknik purposive sampling yaitu investor di pasar saham yang telah memiliki Single Investor Identification (SID). Pengambilan data menggunakan kuesioner yang disebarkan menggunakan Google Forms secara online. Pengujian hipotesa menggunakan Structural Equation Modelling - Partial Least Square (SEM-PLS) dengan alat SmartPLS versi 3.0. Hasil pengujian membuktikan personality traits (neuroticism) berpengaruh signifikan terhadap behavioral bias (disposition effect). Personality traits (agreeableness, extraversion, neuroticism) berpengaruh signifikan terhadap behavioral bias (herding behavior) dan personality traits (conscientiousness, openness) berpengaruh signifikan terhadap behavioral bias (overconfidence). Temuan ini membuktikan setiap individu memiliki kepribadian masing-masing sehingga dalam proses pengambilan keputusan investor secara rasional akan melakukan berbagai pertimbangan namun keputusan yang ditentukan dapat dipengaruhi faktor psikologisnya sehingga menjadi bias. Proses tersebut akan berdampak pada kegiatan transaksi di bursa saham, maka investor saat berinvestasi perlu mencari informasi, mempertimbangkan risiko dan mengambil keputusan yang efisien untuk mengurangi bias.
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R, Mardiana, Yossinomita Yossinomita, M. Haris Saputra, Mandasari R, and Yulia D. Kartika. "BEHAVIORAL BIAS (AVAILABILITY, REPRESENTATIVENESS, ANCHORING, AND CONFIRMATION) TOWARD INVESTMENT DECISION-MAKING." Journal of Management : Small and Medium Enterprises (SMEs) 18, no. 1 (2025): 399–412. https://doi.org/10.35508/jom.v18i1.17769.
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When making investment decisions, retail investors tend to rely on shortcuts in thinking to process the information and data they get. This creates illogical thinking based on emotions or momentary judgments that can result in less-than-optimal investment performance and even losses. This research investigates the relationship between behavioral financial biases (like availability, representativeness, anchoring, and confirmation) and investment decision-making. This study method uses purposive sampling with certain characteristics. Data was collected from 130 retail investors for 3 months in 2024 and analyzed with SPSS Statistics. The research results show that confirmation bias and representativeness bias positively affect investment decision-making. However, anchoring bias and availability bias do not significantly affect investment decision-making. In addition, confirmation bias, representativeness bias, anchoring bias, and availability bias simultaneously positively affect investment decision-making. Financial behavioral biases that can influence investors are confirmation bias and representativeness bias, where retail investors tend to look for information according to their views and similarities based on certain stereotypes, which can reduce or cause losses in stock investments. Keywords: Anchoring Bias; Availability Bias; Confirmation Bias; Representativeness Bias; Investment Decision-Making
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Abinzano, Isabel, Luis Muga, and Rafael Santamaria. "Behavioral Biases Never Walk Alone." Journal of Sports Economics 18, no. 2 (2016): 99–125. http://dx.doi.org/10.1177/1527002514560575.
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This article presents evidence of the impact of overconfidence bias in asset prices drawn from a study based on data from tennis betting exchanges. A series of betting strategies in tournaments with a clear-cut favorite are shown to yield significant economic returns. The impact of overconfidence bias on betting odds increases with trading volume, media coverage, and levels of disagreement between overconfident and cumulative prospect theory bettors. Just as in traditional financial markets, arbitrage limits are shown to be a necessary condition for the impact of behavioral biases on prices.
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Chakraborty, Anujit. "Present Bias." Econometrica 89, no. 4 (2021): 1921–61. http://dx.doi.org/10.3982/ecta16467.
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Present bias is the inclination to prefer a smaller present reward to a larger later reward, but reversing this preference when both rewards are equally delayed. Such behavior violates stationarity of temporal choices, and hence exponential discounting. This paper provides a weakening of the stationarity axiom that can accommodate present‐biased choice reversals. We call this new behavioral postulate Weak Present Bias and characterize the general class of utility functions that is consistent with it. We show that present‐biased preferences can be represented as those of a decision maker who makes her choices according to conservative present‐equivalents, in the face of uncertainty about future tastes.
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Xu, Shurui. "The Impact of Behavioral Bias on Investment Decision-Making." Highlights in Business, Economics and Management 15 (June 28, 2023): 194–202. http://dx.doi.org/10.54097/hbem.v15i.9348.
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Behavioral finance is an emerging discipline that integrates theories from psychology with finance. Robert Shiller, a professor of economics at Yale University, is the originator of behavioral finance and was awarded the Nobel Prize in economics in 2013 for his successful prediction of the Internet bubble crisis and the subprime mortgage crisis. The major difference between behavioral finance and traditional finance is the difference in the underlying assumptions of the two. Behavioral finance attempts to explain how decision-makers make financial decisions in real life, and why their decisions may not be rational every time. This is in contrast to many traditional theories that assume that investors make rational decisions. Behavioral finance suggests that individuals may not make decisions based on rational analysis of all information. This may cause the stock prices of individual companies to deviate from a fair price and cause the stock prices of the entire market to collectively be at very high or very low levels over a period of time. Therefore, the different behaviors and differences that people generate when investing has an important impact on their investment decisions. This paper focuses on promoting a deeper understanding of behavioral finance and helping people to better analyze their investment decisions by reviewing the four more common types of behavioral finance: loss aversion, noise trading, momentum effect, and the endowment effect.
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Tobon, Juliana I., Allison J. Ouimet, and David J. A. Dozois. "Attentional Bias in Anxiety Disorders Following Cognitive Behavioral Treatment." Journal of Cognitive Psychotherapy 25, no. 2 (2011): 114–29. http://dx.doi.org/10.1891/0889-8391.25.2.114.
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A substantive literature suggests that anxious people have an attentional bias toward threatening stimuli. To date, however, no systematic review has examined the effects of cognitive behavioral therapy (CBT) for anxiety on attentional bias. A better understanding of the extant literature on CBT and its effect on attentional bias can serve to bridge the gap between experimental research on cognitive bias and the implications for clinical treatment of anxiety disorders. The present review examined studies that measured the effects of CBT on attentional bias. Of the 13 studies reviewed, 10 demonstrated that attentional bias, as assessed by dichotic listening tasks, the emotional Stroop test, or probe detection tasks, was significantly reduced from pretreatment to posttreatment for obsessive-compulsive disorder, spider phobia, social phobia, and generalized anxiety disorder. Methodological issues are considered, and implications for cognitive behavioral treatments of anxiety are discussed.