Loss Aversion Bias Research Articles

Predicting and Understanding Human Action Decisions: Insights from Large Language Models and Cognitive Instance-Based Learning

Large Language Models (LLMs) excel in tasks from translation to complex reasoning. For AI systems to help effectively, understanding and predicting human behavior and biases is essential. However, it remains an open question whether LLMs can achieve this goal. This paper addresses this gap by leveraging the reasoning and generative capabilities of LLMs to predict human behavior in two sequential decision-making tasks. These tasks involve balancing between exploratory and exploitative actions and handling delayed feedback, which is essential for simulating real-life decision processes. We compare the performance of LLMs with a cognitive instance-based learning (IBL) model, which imitates human experiential decision-making. Our findings indicate that LLMs excel at rapidly incorporating feedback to enhance prediction accuracy. In contrast, the IBL model better accounts for human exploratory behaviors and effectively captures loss aversion bias — the tendency to choose a sub-optimal goal with fewer step-cost penalties rather than exploring to find the optimal choice, even with limited experience. The results highlight the benefits of integrating LLMs with cognitive architectures, suggesting that this synergy could enhance the modeling and understanding of complex human decision-making patterns.

Influence of Overconfidence and Loss Aversion Biases on Investment Decision: The Mediating Effect of Risk Tolerance

This study aims to examine the effects of overconfidence and loss aversion on Investing behavior with the mediating role of risk tolerance. Employing a quantitative methodology, data was collected using a structured questionnaire featuring multiple choice and Likert scale questions. Convenience sampling was used to gather responses, and the data was analyzed through multiple regression techniques. The mediating effect of risk tolerance was measured using Andrew F. Hayes’ Process V4.2 Macro. The study found that risk tolerance partially mediates the relationship between overconfidence and investment decision-making behavior, with both direct and indirect effects being statistically significant. Similarly, the study found that loss aversion has a statistically insignificant direct effect on investment decisions, while its indirect effect through risk tolerance is statistically significant. The study discloses that risk tolerance partially mediates the relationship between overconfidence and investment decision behavior, while it fully mediates the relationship between loss aversion and investment decision making behavior. Risk tolerance significantly influences investment decisions, influencing both overconfidence and loss aversion, while loss aversion’s influence is partially explained by risk tolerance.

Impact of Behavioral Biases Observed on Investors’ Performance in The Nepalese Stock Market

The purpose of this research article is to clarify how behavioral biases affect the performance of investors within the framework of the Nepalese stock market. This study employs a quantitative analysis utilizing a purposive and causal research design. Data was collected between April and May of 2024 through a survey conducted with 124 respondents who actively trade in the Nepalese stock market. Secondary data was gathered from existing research papers to support the findings. The analysis reveals that emotional biases, specifically Loss Aversion Bias and Overconfidence Bias, significantly impact investor performance. In contrast, cognitive biases, such as Anchoring Bias, Availability Bias, and Representativeness Bias, showed no significant effect on investor performance. This suggests that while cognitive biases can be identified and adapted, emotional biases may have a more profound influence on trading decisions. Implications the significance of this study extends beyond individual and institutional investors. It provides insights into the importance of understanding various biases that affect investor performance in the Nepalese context. By addressing these biases, investors can improve their decision-making processes and potentially enhance their investment outcomes. This research contributes to the existing literature on behavioral finance by focusing on the specific biases affecting Nepalese investors. It highlights the need for further exploration of these biases to mitigate inconsistencies in investor performance and promote more informed trading strategies in the Nepalese stock market.

All are interesting to invest, I fear of missing out (FOMO): a comparative study among self-employed and salaried investors

Purpose This paper aims to examine how fear of missing out (FOMO) and investment intention mediate the relationship between behavioral biases and investment decisions of retail investors in the Indian stock market. Design/methodology/approach The present research comprises two cross-sectional quantitative studies, where Study A involves data from 405 self-employed and Study B involves 393 salaried investors. Data was attained through questionnaires – the partial least squares structural equation modeling was used for data analysis. Findings The outcomes show that herding, overconfidence and loss aversion bias significantly impact investment intention and FOMO on both studies. Furthermore, the outcomes also indicate that herding and loss aversion bias significantly influence investment decisions in studies (A and B); however, overconfidence bias insignificantly affects the investment decisions in Study A. Besides, the results also reveal a substantial relationship between FOMO, investment intention and investment decision. Practical implications The findings of this paper assist practitioners (financial analysts and retail investors) in considering the various ways of analyzing investment decision outcomes by considering the joint effect of several biases. Originality/value This paper is an initial attempt to propose a new theoretical framework and empirically examine the impact of behavioral biases on investment decisions by considering the FOMO and investment intention among self-employed and salaried investors. This study also contributes to the behavioral finance literature; other researchers may find it valuable to attain their goals.

The relationship between emotional biases and investment decisions: a meta-analysis

PurposeThe study attempts to investigate the relationship between emotional biases (loss aversion bias, overconfidence bias, and regret aversion bias) and investment decisions through a meta-analysis approach.Design/methodology/approachA meta-correlation analysis was done using sample size and correlation (r) data from several relevant studies that look at how emotional biases (loss aversion bias, regret aversion bias, and overconfidence bias) affect investment decisions. Additionally, beta coefficients (ß) were also converted to correlation coefficients (r) from six studies.FindingsThis study analysed 31 empirical studies and found a significant positive correlation between emotional biases and investment decisions [loss aversion bias (r = 0.492), regret aversion bias (r = 0.401), and overconfidence bias (r = 0.346)]. We set the statistical significance threshold at 0.05.Research limitations/implicationsThe review covered 31 online research publications that showed significant heterogeneity, possibly influenced by various methodological, population, or other factors. Furthermore, the use of correlational data restricts the ability to establish causation.Originality/valueThis is a novel attempt to integrate the results of various studies through meta-analysis on the relation between these emotional biases (loss aversion, overconfidence, and regret aversion) and investment decisions.

From mindset to market: unveiling the nexus of cognition, behavior and environment in igniting students’ E-entrepreneurial intentions

PurposeIndia has witnessed a significant surge in internet users in recent years, creating an ideal environment for E-entrepreneurship. With the rise of E-commerce and the growth of the digital economy, there is tremendous potential for online businesses in developing nations. Our study outlines the behavioral, cognitive, and environmental aspects shaping students' E-entrepreneurial intentions (EEI).Design/methodology/approachOur study incorporated structural equation modeling (SEM), social cognitive theory (SCT), and entrepreneurial event model (EEM) to evaluate the EEI of 460 students from India's top five engineering institutes. The direct and indirect linkages in the model were examined by employing mediation and moderation analysis.FindingsOur findings reveal that behavioral, environmental, and cognitive factors facilitate evaluating feasibility, further igniting students' EEI. The cognitive factors and E-entrepreneurial feasibility (EEF) mediate the relationship between the underlying constructs. Furthermore, financial resource availability (FRA) strengthens, and loss aversion bias(LAB) weakens the linkage between EEF and EEM.Research limitations/implicationsThe study's findings may benefit online innovation communities, potential technopreneurs, financial institutions, and policymakers in improving the entrepreneurial ecosystem.Originality/valueThe study integrates psychological and sociological perspectives to understand the key facilitators of EEF and EEI. The study combines SCT and the EEM by appending crucial constructs such as FRA and LAB to broaden the horizons of EEI.

Fast & slow decisions under risk: Intuition rather than deliberation drives advantageous choices

Would you take a gamble with a 10% chance to gain $100 and a 90% chance to lose $10? Even though this gamble has a positive expected value, most people would avoid taking it given the high chance of losing money. Popular “fast-and-slow” dual process theories of risky decision making assume that to take expected value into account and avoid a loss aversion bias, people need to deliberate. In this paper we directly test whether reasoners can also consider expected value benefit intuitively, in the absence of deliberation. To do so, we presented participants with bets and lotteries in which they could choose between a risky expected-value-based choice and a safe loss averse option. We used a two-response paradigm where participants made two choices in every trial: an initial intuitive choice under time-pressure and cognitive load and a final choice without constraints where they could freely deliberate. Results showed that in most trials participants were loss averse, both in the intuitive and deliberate stages. However, when people opted for the expected-value-based choice after deliberating, they had predominantly already arrived at this choice intuitively. Additionally, loss averse participants often showed an intuitive sensitivity to expected value (as reflected in decreased confidence). Overall, these results suggest that deliberation is not the primary route for expected-value-based responding in risky decision making. Risky decisions may be better conceptualized as an interplay between different types of “fast” intuitions rather than between two different types of “fast” and “slow” thinking per se.

A Study on Influence of Behavioural Biases on Investment Decision of Young Investors in Coimbatore City

This study investigates the influences of cognitive biases on the investment behaviour of the youth of the city of Coimbatore. The main purpose of this study will be to explore the idea that individuals who engage in stock market activities and have different types of biases such as Overconfidence, Anchoring, Loss Aversion, Confirmation and Herding perceive to have the power to affect their investment choices. The study involved 120 investors aged 18-29. The study uncovered various behavioural biases that significantly affected the investment decision-making process among young investors. Anchoring Bias was proven the most significantly influencing bias of investment decisions, followed by Overconfidence Bias and Loss Aversion Bias. The information provided suggests that the effect of Confirmation Bias and Herding Bias on decision-making is insignificant.

Implications Of Loss Aversion And Investment Decisions

As a behavioral bias known as "Loss Aversion," it states that people are more negatively affected by the prospect of losing money than they are by the prospect of gaining it. Concerning its effect on investors, the findings of the many research conducted on loss aversion have been contradictory. Individuals who engage in the Indian stock markets via brokerage companies are the target of this research, which seeks to answer the question, "Is loss aversion real?" and how does it influence investing decisions. This research also looks at the potential effects of gender, income, investing history, and risk perception on loss aversion. The research relied on primary data gathered via a structured questionnaire and analyzed using statistical procedures such as linear regression, independent t-test, and analysis of variance. According to the study's findings, loss aversion bias influences investors' investing choices and is significantly impacted by the respondents' gender.

Role of behavioral biases in the investment decisions of Pakistan Stock Exchange investors: Moderating role of investment experience

Despite many revolutionary asset pricing models developed over the past decades, traditional finance does not explain investor behavior very well. The purpose of this study is to examine the influence of behavioral biases on the investment decisions of investors of Pakistan Stock Exchange. In addition, the moderating influence of investment experience investigated in this study. The findings were reported using a sample of 230 individual investors, who make their own investments, typically through a mutual fund, bank, or internet broker. They make investments to achieve their unique investment objectives, such as saving for retirement, a child’s education, or increasing their overall wealth. The influence of behavioral biases on investment decisions was calculated using regression analysis. Regression results show that beta and t-values are significant and have a significant impact on investment decisions. Regression findings show that Confirmation Bias, Gamblers Fallacy Bias, Negativity Bias, Bandwagon Effect Bias, Loss Aversion Bias, and Overconfidence Bias all have a substantial impact on Investment Decisions. Status quo prejudice and endowment bias have a favorable but minor influence on Investment Decisions. Investment Experience is regarded as an essential component that contributes to successful decision making under risk and uncertainty, however the results of this study show that moderating variables have a minor influence. According to the findings, the moderating variable had no effect on the connection between behavioral biases and investment decisions. And the reason for this is that behavioral biases persist regardless of investing experience.

Behavioral Biases Influencing Individual Investors Decision Making in Bearish Trend at Nepse

The discipline of financial economics has seen a paradigm shift over the past 25 years, moving from traditional finance to a new area of the study known as behavioral finance. Due to a multitude of behavioral biases and emotional attachments, professional investors make bad financial decisions that hinder their investing performance. Due to the increase in individual investors over the past several years, which is predicted to continue in the years to come, the problem of behavioral biases may become more and more important. Overconfidence bias, representativeness bias, disposition bias, loss aversion bias, herding bias and market factors are the independent variables, whereas investment decision making is the dependent variable. Questionnaires were used to collect primary data. 200investors were sampled using the convenience sampling technique, and data obtained was subjected to regression analysis. The SPSS was used to analyze data collected in order to generate descriptive statistics for the study. The extent to which the dependent variables could be explained by the independent variable was described using regression analysis. The study thus suggests that individual investors be educated how to avoid poor investment outcomes caused on by behavioral biases. Furthermore, individual investors should seek the advice of stock brokers/fund managers to guide them accordingly in terms of performance of a specific security in which an investor would wish to invest in.

Biases in Capital Market Instrument Investing Decisions: A Study from India

This study examines the influence of different behavioral biases on the investment choices made by individual investors in the Indian capital market. The study utilizes a cross-sectional design, which entails gathering a substantial amount of data at a specific point in time. The study employed a survey methodology to collect data from a sample of 497 individual investors using purposive and snowball sampling. The data was collected using structural equation modeling (SEM), utilizing SPSS version 25 and AMOS version 26 as statistical software. This study characterizes individual investors as displaying irrational conduct. The study reveals a significant and positive association between representativeness, anchoring, and loss aversion biases and the investment decision-making process of individual investors in India. This study will enhance the current corpus of literature by examining the field of behavioral finance, which is gaining acknowledgment. Furthermore, few researchers have specifically examined these biases in developing countries, such as India.

Herding Behavior, Loss Aversion Bias, Financial Literacy, and Investment Decisions (a Study on Millennial Generation in Indonesia in the Digital Era)

In the last few years in Indonesia, many investment applications have emerged where these applications make it easy for investors to be able to invest. The emergence of investment applications also raises many problems such as fraud under the guise of investment and people in Indonesia, especially young people who are easily tempted by investment offers that provide high returns so that they often carry out investment activities but are irrational and tend not to look at financial conditions in making investments. The purpose of this study is to see how the internal and external factors of an investor, especially the millennial generation, in making investment decisions, namely the factors of Herding Behavior, Loss Aversion Bias and Financial Literacy. This research method uses descriptive and verification methods with a sample size of 400 respondents and data analysis techniques using Multiple Logistic Regression Analysis. The results showed that the the Herding Behaviour variable has a positive effect on Investment Decisions of the Millennial Generation in Indonesia in the Digital Age, Loss Aversion Bias has a negative effect on Investment Decisions of the Millennial Generation in Indonesia in the Digital Age, while the Financial Literacy variable has no effect on Investment Decisions of the Millennial Generation in Indonesia in the Digital Age.

Evaluation of Behavioral Biases and Investment Decision: An Evidence from Pakistan Stock Exchange (PSX)

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).”

Investment Decision-Making Behavior in the Era of Covid-19: An Analysis on the Basis of Mental Accounting, Loss Aversion Bias, and Risk Tolerance

Abstract The era of Covid-19 is a condition that illustrates the uncertainty of national and world economic conditions, which encourages individuals to be able to manage their economy and finances. Therefore, this research aims to explain whether mental accounting, loss aversion bias, as well as risk tolerance can affect investment decision-making in the Covid-19 situation from the point of view of behavioral finance theory. The results of research using SEM PLS analysis show that Mental Accounting, Loss Aversion Bias, as well as Risk Tolerance, have an effect on investment decision-making. Based on behavioral finance theory, the results of the study illustrate that in the Covid 19 pandemic situation, individuals will generally respond to information received as a basis for making decisions by paying attention to the level of risk and optimizing the rate of return from the investment made.

Effect of Behavioural Biases on the Financial Decisions of Rural Women Micro-entrepreneurs: A Scale Development Approach

The basic purpose of this article is to understand the impact of behavioural biases on the financial decisions of the rural women micro-entrepreneurs. The indicators were selected based on the literature review and exploratory interview, and in consultation with the experts of the funding agencies (mainly banks) to cover behavioural biases of the rural women micro-entrepreneurs. In order to design the scale, SEM AMOS 26 software along with SPSS 26 was used for data analysis. Reliability score and exploratory factor analysis were conducted with the help of SPSS 26 software. Overconfidence of the rural women micro-entrepreneurs negatively influenced their financial decisions. Rural women micro-entrepreneurs were found to be better financial decision-makers as past loss from their financial decisions did not deter them from taking risk. The loss aversion bias did not influence the financial decisions of the rural women micro-entrepreneur. However, the regret aversion bias and the anchoring bias positively influence their financial decisions, depicting the impact of behavioural biases on their financial decisions. The present study can be further extended to identify the impact of moderating and mediation variables. The impact of other emotional and cognitive behavioural biases on the financial decisions of the rural women micro-entrepreneurs can also be considered. The understanding of impact and the effect of behavioural biases on financial decisions of rural women micro-entrepreneurs will help to identify the rationale behind financial decision-making of the rural women micro-entrepreneurs. Most of rural women micro-entrepreneur has to deal with decisions related to finance. The confidence with which they handle their money is a reflection on how confidently they can handle their business. The present study attempts to design and validate a comprehensive behavioural bias scale influencing financial decisions of the rural women micro-entrepreneurs. To the best of the knowledge of the author, almost no studies have focused adequately to explore the influence of behavioural biases on the financial decisions of women micro-entrepreneurs. Thus, the aim of this research is to understand the influence of behavioural biases on the financial decisions of rural women micro-entrepreneurs and design a robust and comprehensive scale.

A Review of the Relationship Between Loss Aversion Bias and Investment Decision-making Process

The decision-making process determines that investors tend to be not rational to make substantial investment decisions when it possesses the possibility of great loss. This phenomenon can be explained by the loss aversion bias, which indicated that people have stronger feelings and biases when they are taking losses than gaining profits. However, it is also pointed out by other scholars that many other factors could influence the result of the bias, and rationality cannot be easily predicted. Therefore, by conducting survey analysis, it is then concluded in this paper that the loss aversion bias is significant in investors, and multiple factors could affect the degree of loss aversion for individual investors, they are age, gender, and the ability to take the risks.

The Impact of Financial Literacy, Overconfidence Bias, Herding Bias and Loss Aversion Bias on Investment Decision

Investment decisions, aimed at securing long-term gains, are shaped by rational and irrational attitudes in capital allocation. Financial literacy gauges the rational stance, while behavioral finance dissects irrational inclinations. Behvioral finance includes overcondience bias, herding bia and loss aversion bias. This study scrutinizes how financial literacy, overconfidence bias, herding bias, and loss aversion bias sway investment choices for young Java Island investors. Simple random sampling is used, analyzed via Partial Least Square. Results indicate financial literacy lacks significant impact. Overconfidence boosts decisions, while high herding bias hampers them. Loss aversion bias, however, holds no sway on Java Island investors' decisions.

Decoding Investor Decision-Making: Unraveling Psychological Factors and Educational Moderation in Financial Markets

This study delves into the influence of psychological factors on investors' decision-making, with a focus on the moderating role of education. The target population comprises 883 domestic individual investors registered in the Pakistan Stock Exchange. Employing a structured questionnaire, opinions were gathered from a sample of 275 financial domestic individual investors. The findings reveal a positive and significant association between risk propensity, risk perception, and investment decisions. Conversely, herding behaviour exhibits a negative and significant impact, indicating that heightened herding behaviour reduces investors' decision to invest. Further analysis underscores the combined effect (moderating effect) of risk propensity financial literacy, revealing a significant yet negative impact on investors' decisions, while risk perception financial literacy demonstrates a positive and significant effect. The concluding table highlights the positively significant presence of loss aversion bias.

The Media's Role in Fostering Knowledge of Financial Management: A Case of Pakistan

This study investigates how behavioural biases affect how individual investors make investing decisions. Drawing upon the discipline of behavioral finance, which integrates psychological insights into financial decision-making, we investigate the presence and effects of various biases on investment behavior. The study aims to contribute to understand the factors thoroughly that shape individuals' investment choices and their subsequent financial outcomes. Using a mixed-methods approach, including surveys and interviews, we explore the prevalence and magnitude of biases for instance loss aversion, overconfidence, and framing effects among individual investors. By analyzing real-world investment decisions, we assess the influence of these biases on portfolio composition, trading frequency, and performance outcomes. According to the preliminary findings, behavioral biases play a significant role in shaping investment decisions. Overconfident investors prefer to trade more often, leading to higher transaction costs and lower returns. Loss aversion biases lead to suboptimal portfolio allocation, as investors disproportionately allocate funds to low-risk assets. Additionally, framing effects impact decision-making by altering risk perceptions and preferences. The study underscores the importance of recognizing and mitigating behavioral biases in investment decision-making. By raising awareness and providing insights into the specific biases influencing individual investors, this research offers valuable implications for financial education, regulatory policies, and investment advisory services. Ultimately, understanding the role of behavioral biases can contribute to more informed and rational investment decision-making, leading to improved financial outcomes for individual investors.