Loss Aversion Research Articles

Behavioral Finance: Investor Psychology in Volatile Markets

Behavioral finance offers critical insights into how psychological biases shape investor decision-making, particularly during periods of market volatility. Traditional finance theories assume rational behavior, but behavioral finance highlights how emotions and cognitive biases like overconfidence, herding, loss aversion, and anchoring significantly impact market dynamics. In volatile markets, these biases become more pronounced, often resulting in irrational actions that deviate from rational expectations. This paper explores the role of investor psychology in influencing market outcomes, examining biases and emotional factors that drive investor actions. Practical implications of this understanding suggest strategies to mitigate risk and stabilize markets, such as behavioral nudges and AI-driven advisory tools. The paper also identifies research gaps, especially in understanding the influence of digital platforms and social media on investor behavior, indicating areas for further study to deepen our grasp of investor psychology in an increasingly digital world.

Understanding the determinants of consumer grocery stockpiling behavior

AbstractGrocery stockpiling is a common behavioral response to the emergence of disasters or heightened uncertainty. Nonetheless, the phenomenon and methods for mitigating it are not well understood. Using a model of household shopping and inventory management, we conceptualize stockpiling as a result of an increase in the fixed cost of making grocery shopping trips, or the opportunity cost of time associated with shopping. In a laboratory experiment, we find that stockpiling increases (decreases) by 78 and 41% (22%) with an increase in fixed costs and price reductions (imposition of purchase limits), respectively. We also find that stockpiling leads to fewer (more) grocery trips by 33 and 22% (36%) under the same three conditions, respectively. Our experiment and subsequent cluster analysis suggest that loss aversion suppresses stockpiling. Our experiment shows that imposing purchase limits, a common retail response to stock‐outs, can trigger stockpiling during shopping trips without purchase limits. Although we do not claim external validity, our study suggests that store managers and policymakers should be careful about solutions during a stockpiling event, such that they do not exacerbate stockpiling, which may disproportionately affect vulnerable groups and disrupt supply chains.

To disclose or to conceal? Comparison of different disclosure policies in queues with loss-averse customers

In many service industries, information disclosure about the product can alleviate customers’ loss aversion induced by uncertain product valuation. In this paper, we consider a single-server queueing system in which the manager who privately learns the valuation information discloses the valuation information strategically to loss-averse customers. We investigate the impact of the customers’ loss aversion on the system’s equilibrium arrival rate and the manager’s optimal disclosure policy. We find that loss aversion restrains customers from joining the queue. Surprisingly, we find that there is no one disclosure policy that always prevails over other disclosure policies. Specifically, the full disclosure policy is optimal only when the valuation is large and the degree of loss aversion is moderate. The full non-disclosure policy is optimal when the degree of loss aversion is too large or too small, or the valuation is small. The threshold disclosure policy is optimal when the valuation and the degree of loss aversion are moderate. Furthermore, under the threshold disclosure policy, the increasing degree of loss aversion makes managers be more reluctant to disclose the valuation.

IMPACT OF BEHAVIOURAL FINANCE ON RISK PERCEPTION, PSYCHOLOGICAL BEHAVIOUR, AND FINANCIAL DECISIONS OF MOROCCAN INVESTORS

The paper deals with behavioural finance as a stream of finance challenging the principles of classical finance by adding psychology to the reasons that could explain observed anomalies within financial markets and which, at the same time, are caused by real human behaviour. The aim of this paper is to explore investors' behavioural, biases and their disturbances of rationality, focusing mostly on the factors of loss aversion, cultural influences, and overconfidence, and how these elements influence investment decisions.It is based on empirical data and behavioural experiments, which help to show how such biases deviate from efficient market theories; this work also tests some methods that can mitigate these negative effects, therefore providing insights on how to integrate the teaching of behavioural finance more effectively into the decision-making process of investors and experts within finance. Precisely, this work is aimed at attempting to provide a model of psychological behaviour for Moroccan investors, based on an investigation carried out in the field among 93 regular investors in the Casablanca Stock Exchange.The main findings of the study underline how behavioural biases deviate from predictions by efficient market theories. This paper has only focused on the specific context of Moroccan investors, yet giving insight into how psychological factors impact investment decisions through new insights into life where these financial behaviours take place.There is, hence, uniqueness to the research through the theoretical and practical approaches integrated therein, with the use of empirical data and behavioural experiments that sustain the discussion on behavioural finance. Presenting the case of Moroccan investors adds a significant contribution to proposing a context-specific model, which may bring important implications for financial decision-making within the region.

A Critical Review of Overconfidence in Investment Decisions: A Bibliometric Analysis

The precedence of behavior bias-based studies with respect to investment is quite prevalent. Hence, a bibliometric analysis of available literature may lead to fresh topics in association with overconfidence bias. The literature ranging between 1970 and 2024 were scanned using terms related to overconfidence in finance as keywords to reach the related publications. After screening, 1327 publications related to overconfidence, 728 documents were identified. Martin Weber emerged as the most cited author. SSRN electronic journal, qualitative research in financial matters and review of behavioral finance have published most cited papers in the field of overconfidence and investment decision. The United States have published highest number of papers and citations, while Germany, India and China have also emerged as nations with highest citations. The United States of America has published highest number of papers with citations. Germany, India and China have also emerged as nations with highly citated papers. Considering year on year growth in the publications, more work may be expected from the arena of overconfidence, and authors of the present study have taken the liberty to suggest a few possibilities that can be explored. Studies with risk tolerance, after pandemic impact, experience and financial/tax literacy, loss aversion and availability bias-based studies may be considered by researchers in accordance to overconfidence.

The Microeconomics of Agricultural Development: Risk, Institutions, and Agricultural Policy

Assertions of pervasive inefficiency in the behavior and organization of developing agriculture are found to be based on unsound methodologies. Models apparently based on expected utility theory are theoretically flawed and use highly restrictive assumptions that make them largely irrelevant for explaining actual decisions. When a more appropriate model is applied to the case of the green revolution in the Philippines, the hypothesis that loss aversion impedes adoption of new technology is rejected. Common assertions about the inefficiency of agricultural institutions are also found wanting. The risk-bearing theory of share-tenancy, which is thought to imply inefficiency, cannot explain observed tenant shares. Once the disadvantages of fixed-lease contracts are recognized, sharing is plausibly second-best efficient. The purported inefficiency implied by the inverse relationship between farm size and yield per hectare also dissipates once the endogeneity of farm size is accounted for.

Behavioral Economics and Stock Market Decision-Making: Investor Biases and Investment Strategies

This study examines the application of behavioral economics to stock market decision-making, focusing on common cognitive biases of investors and their impact on investment decisions. Unlike the complete rationality assumed in traditional economics, behavioral economics reveals the irrational behaviors that investors exhibit when facing risks and uncertainties, such as overconfidence, loss aversion, and herd effect. By examining classical theories such as prospect theory, loss aversion, and the anchoring effect, as well as specific case studies such as the 2008 global financial crisis, this study aims to reveal how these psychological biases affect investors’ decision-making process. Further, this study examines how behavioral economics theories can be used to improve investment strategies by recommending methods such as low volatility investment strategies to help investors make more rational and effective investment choices in a complex market environment. Through in-depth analysis of the core theories and cases of behavioral economics, investors are better able to identify biases in the decision-making process, thereby optimizing their investment decisions and improving long-term investment returns.

Study on Impact of Neuroeconomics Tactics used by Streaming Services Companies (Eg. Netflix, Spotify) on Genz's Purchase Intentions in Ahmedabad City

This paper reflects on how the neuroeconomics strategies employed by streaming companies, like Netflix and Spotify, affect Generation Z's purchasing intentions in Ahmedabad City. Neuroeconomics endeavors to be an integrative science that explains how neuroscience and psychology will intervene in or complement economics to develop knowledge about understanding consumer decision-making processes and those factors that influence buying behavior. Having established such neuroeconomic theories, streaming service companies then hunt them under the guise of optimized user experience with visual and auditory stimuli and tailored recommendations to keep the user interested and waiting for another subscription or purchase. The effects of such strategies are pretty important to understand for the Gen Z audience - a bunch of kids known for their tech-savvy nature and instant gratification. This paper investigates how streaming applications make use of cognitive biases arising from loss aversion to dopamine-driven reward systems and social proof influencing the buying behavior of young consumers. A mixed method approach was used on a representative sample of Gen Z youths by surveys and interviews in Ahmedabad to collect the data. Overall, the findings from this study are expected to be very informative on how neuroeconomic strategies will or will not impact the consumption behavior of Gen Z in the streaming industry. This would be followed by actionable recommendations for companies about how they can maximize their marketing efforts to resonate more effectively with this emergent market going forward. As neuroeconomics and consumer behavior begin to intermix, streaming services stand to increase users' engagement, amplify sales, and cultivate long-term customer loyalty with Gen Z among urban India.

Risk attitude toward on-demand insurance: an experimental study

AbstractOn-demand insurance products cover risks for short periods of time via a smartphone or other electronic device. Such insurance contracts give policyholders the freedom to choose when to be insured in a flexible way. On-demand contracts may change the way risk is perceived. Therefore, we conduct an experiment and show that individuals can become exceptionally risk-averse when offered short-term insurance. We show two main reasons for this result: first, the underlying risk is often overestimated by the subjects due to a miscalculation of the loss probabilities. Second, the shorter valuation horizon of on-demand insurance contracts leads to myopic loss aversion.

Drivers of digital currency adoption and their configurational impact assessment in tourism and hospitality: loss aversion under prospect theory

ABSTRACT With accelerated digitalisation in all business sectors, digital currencies (DC) are increasingly popular. This study aimed to identify the effects of central bank digital currency (CBDC) innovation characteristics and perceived risks on CBDC adoption intention in the tourism and hospitality field. This study devised a research model incorporating research hypotheses addressing CBDC customers’ perceptions of CBDC's innovative technology and risks. To test the hypotheses, data were obtained from the USA, Korea, and China. CBDC's innovation characteristics and perceived risks affected the adoption of CBDC for transactions during travel. The results have academic and practical value because they aid understanding of customers’ reactions to the new transaction system and establish proactive marketing strategies such as promotional message development to reduce perceived risks in lieu of strengthening innovative characteristics.

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.

Implication of Financial Services Marketing: A Study with reference to Behavioral Economics

Abstract Purpose – It has been argued that the insights provided by behavioral economics have profound Implications for the study and practice of marketing. The purpose of this paper is to provide a detailed analysis of how such insights help enhance understanding of aspects of marketing and consumer behavior in financial services markets. Design/methodology/approach – This paper looks at various facets of behavioral economics Which it is felt provide particularly important and salient insights in the context of financial services. In particular, it studies loss aversion and prospect theory, status quo bias and defaults, framing and anchoring effects, hyperbolic discounting, availability effect and salience and over-confidence. In doing so, it provides a number of examples from the financial services context which provide insightful and informative insights for both commercial practitioners and policymakers. In each case, relevant phenomena are introduced and explained before providing a number of applications and examples from the financial services domain. Findings – The authors find that the insights afforded by behavioral economics are useful in helping to explain various aspects of consumer behavior in financial services markets. It is shown that an understanding of the implications of behavioral economics may help in fashioning a choice architecture that is more likely to bring the desired consumer response, from either a commercial or policymaking perspective. Practical implications – This analysis provides important insights for those responsible for the Marketing of financial services, policymakers in the financial services domain, third sector agencies seeking to foster greater engagement with financial services and other interested parties. Originality/value – The paper adds value by drawing together various aspects of behavioral Economics, providing an analysis of their relevance to financial services marketing and offering Numerous examples and applications. Keywords-: Financial services, Behavioral economics, Consumer behavior in financial services, Marketing Paper type-: Conceptual paper

Do stress hormones influence choice? A systematic review of pharmacological interventions on the HPA axis and/or SAM system.

The hypothalamus-pituitary-adrenal axis (HPA axis) and the sympathetic-adrenal-medullary system (SAM system), two neuroendocrine systems associated with the stress response, have often been implicated to modulate decision-making in various domains. This systematic review summarizes the scientific evidence on the effects of pharmacological HPA axis and SAM system modulation on decision-making. We found 6375 references, of which 17 studies fulfilled our inclusion criteria. We quantified the risk of bias in our results with respect to missing outcome data, measurements, and selection of the reported results. The included studies administered hydrocortisone, fludrocortisone (HPA axis stimulants), yohimbine, reboxetine (SAM system stimulants), and/or propranolol (SAM system inhibitor). Integrating the evidence, we found that SAM system stimulation had no impact on risk aversion, loss aversion or intertemporal choice, while SAM system inhibition showed a tentative reduction in sensitivity to losses. HPA axis stimulation had no effect on loss aversion or reward anticipation but likely a time-dependent effect on decision under risk. Lastly, combined stimulation of both systems exhibited inconsistent results that could be explained by dose differences (loss aversion) and sex differences (risk aversion). Future research should address time-, dose-, and sex-dependencies of pharmacological effects on decision-making.

The role of loss aversion in social conformity: psychological and neural representations.

The impact of others' choices on decision-making is influenced by individual preferences. However, the specific roles of individual preferences in social decision-making remain unclear. In this study, we examine the contributions of risk and loss preferences as well as social influence in decision-making under uncertainty using a gambling task. Our findings indicate that while both individual preferences and social influence affect decision-making in social contexts, loss aversion plays a dominant role, especially in individuals with high loss aversion. This phenomenon is accompanied by increased functional connectivity between the anterior insular cortex and the temporoparietal junction. These results highlight the critical involvement of loss aversion and the anterior insular cortex-temporoparietal junction neural pathway in social decision-making under uncertainty. Our findings provide a computational account of how individual preferences and social information collectively shape our social decision-making behaviors.

Save for a rainy day? How regional household savings constrain entrepreneurship after a natural disaster

AbstractWhy do some entrepreneurial ecosystems successfully adjust amid adversity while others languish? By integrating prospect theory into the entrepreneurial ecosystem literature and using a quasi-natural experimental design with a difference-in-difference-in-differences model, our theory and findings reveal that earthquakes reduce entrepreneurship in regions with high household savings, but increase entrepreneurship in regions with low savings, and these between-area differences increase over time. Reconceptualizing the meaning of savings from a resource into a key driver of loss aversion, we thus identify the surprising constraining influence of financial capital in times of adversity, yielding important implications for entrepreneurship research and policymakers.

Psilocybin increases optimistic engagement over time: computational modelling of behaviour in rats.

Psilocybin has shown promise as a novel pharmacological intervention for treatment of depression, where post-acute effects of psilocybin treatment have been associated with increased positive mood and decreased pessimism. Although psilocybin is proving to be effective in clinical trials for treatment of psychiatric disorders, the information processing mechanisms affected by psilocybin are not well understood. Here, we fit active inference and reinforcement learning computational models to a novel two-armed bandit reversal learning task capable of capturing engagement behaviour in rats. The model revealed that after receiving psilocybin, rats achieve more rewards through increased task engagement, mediated by modification of forgetting rates and reduced loss aversion. These findings suggest that psilocybin may afford an optimism bias that arises through altered belief updating, with translational potential for clinical populations characterised by lack of optimism.

Individual and contextual effects of attention in risky choice

AbstractWe investigate the role of visual attention in risky choice in a rich experimental dataset that includes eye-tracking data. We first show that attention is not reducible to individual and contextual variables, which explain only 20% of attentional variation. We then decompose attentional variation into individual average attention and trial-wise deviations of attention to capture different cognitive processes. Individual average attention varies by individual, and can proxy for individual preferences or goals (as in models of “rational inattention” or goal-directed attention). Trial-wise deviations of attention vary within subjects and depend on contextual factors (as in models of “salience” or stimulus-driven attention). We find that both types of attention predict behavior: average individual attention patterns are correlated with individual levels of loss aversion and capture part of this individual heterogeneity. Adding trial-wise deviations of attention further improves model fit. Our results show that a decomposition of attention into individual average attention and trial-wise deviations of attention can capture separable cognitive components of decision making and provides a useful tool for economists and researchers from related fields interested in decision-making and attention.

Investor Sentiment and Corporate Governance: The Role of Behavioral Biases in Stock Price Volatility and Managerial Decisions

Behavioural biases influence investor sentiment and behaviour, which in turn influence stock returns, stock price volatility and corporate governance structures. This paper focuses on the role of three common behavioural biases (overconfidence, herding and loss aversion) on investor behaviour, and how these biases drive inefficiencies in financial markets. Using worldwide market data from 1970 to 2019 and focusing on key events such as the 2008 financial crisis and the dot-com bubble, we investigate how these behavioural biases cause market volatility. This analysis further reinforces the importance of strong corporate governance structures such as independent boards, executive pay structures and risk management protocols that help reduce the impact of investor sentiment. The role of speculative bubbles, market overreaction and volatility clustering is also examined further, and corporate governance mechanisms are proposed to help mitigate the effects of behavioural biases on stock prices. The findings demonstrate the importance of adopting long-term corporate goals, transparency and strategies to help better manage market sentiment and safeguard shareholder value.

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.