Behavioral Finance Research Articles

Behavioral finance in a hundred keywords

We analyze leading journals in behavioral finance to identify the most-used keywords in the area and how they have evolved. Using keyword analysis of data between 2000 and 2020 as well as data mapping and visualization tools, a dynamic map of the discipline was constructed. This study assesses the state-of-the-art of the field, main topics of discussion, relationships that arise between the concepts discussed, and emerging issues of interest. The sample comprises 3876 pieces, including 15859 keywords from journals responsible for the growth of the discipline, namely the Journal of Behavioral and Experimental Economics, Journal of Behavioral and Experimental Finance, Journal of Economic Psychology, Journal of Behavioral Finance, and Review of Behavioral Finance. During the period analyzed, our results depict a lively area and highlight the prominent role that experiments play in the field. Two related but different streams of behavioral finance research are revealed.

A Study on Accelerating Digital Financial Inclusion for positioning India through AI-enabled Banking Services

This research paper examines the role of AI-enabled banking services in accelerating digital financial inclusion in India, with a focus on positioning the country for the future. Financial inclusion, granting access to financial products and services, is crucial for India's economic growth and development. Despite progress, challenges like the digital divide and limitations of traditional banking models hinder inclusion, particularly in rural areas. The study proposes that AI-enabled banking services can be a game changer. AI can personalize financial products, improve creditworthiness assessments for under-served populations, and enhance security. By leveraging AI, India can empower its citizens, promote financial literacy, and solidify its position as a global financial leader. The study also explores the potential benefits and challenges associated with implementing AI in the Indian banking sector, considering factors such as regulatory frameworks, infrastructure requirements, and user adoption. The research explores how AI can address existing hurdles and proposes strategies for leveraging AI responsibly and ethically for inclusive financial growth. The paper aims to contribute to the ongoing dialogue on utilizing AI to empower all Indians and achieve sustainable economic development. This study used review of literature and survey as primary data to assess the impact of AI on digital financial inclusion. The present study discovered that AI has a strong influence on digital financial inclusion in areas related to behavioral finance, customer satisfaction and service efficiency.

An Analysis of Luckin Coffee's New Marketing Model from the Perspective of Behavioral Finance

With the development of Internet technology, Luckin Coffee has transformed the traditional value creation model, driven by customer value as the goal, and established its brand effect in a short period of time through financing. However, the excessive and rapid expansion led to financial crisis, which caused it to fall into the negative vortex of financial fraud, and finally returned to the consumer market at the cost of delisting and restructuring in the United States. After returning to the market, Luckin Coffee changed its business operation model, and the reform of the new marketing model focusing on products and customers made its financial turnaround and rebuilt its brand value. How does Luckin Coffee take advantage of consumers' psychology and guide their consumption preferences? Based on the perspective of behavioral finance, this paper analyzes how the operation management team of Luckin Coffee reconstructs its marketing methods and paths by utilizing the anchoring effect of consumers, limited attention transactions and herd effect. The research conclusion shows that the new marketing model with consumer demand caused by consumer psychology as the core can effectively and rapidly increase the number of new customers and improve customer retention. Luckin Coffee has also quickly passed the crisis after delisting and restructuring, and its business performance and corporate value have also gradually increased. The brand value has returned to the vision of consumers, and the future is promising.

Impact of Monetary Policy on Stock Market Volatility

Purpose: The general objective of the study was to analyze the impact of monetary policy on stock market volatility. Methodology: The study adopted a desktop research methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library. Findings: The findings reveal that there exists a contextual and methodological gap relating to the impact of monetary policy on stock market volatility. Preliminary empirical review revealed that monetary policy exerts significant influence on stock market volatility through various channels such as interest rate adjustments, quantitative easing, and forward guidance. It highlighted that the timing and clarity of policy announcements play a crucial role in shaping market reactions, with unexpected shifts often leading to heightened volatility. Global interconnectedness amplified these effects, underscoring the need for coordinated policy responses. Behavioral factors also contributed, as investor sentiment and market psychology could magnify volatility independently of economic fundamentals. Understanding these dynamics is crucial for effective policy design and market stability amidst evolving financial landscapes. Unique Contribution to Theory, Practice and Policy: Efficient Market Hypothesis (EMH, Rational Expectations Theory and Keynesian Economics may be used to anchor future studies on monetary policy on stock market volatility. Recommendations from the study included integrating behavioral finance models into economic frameworks to enhance predictive accuracy. It advocated for clearer and more consistent central bank communications to align market expectations with policy actions, reducing uncertainty-driven volatility. Collaborative efforts among central banks were emphasized to manage international spillovers and enhance global financial stability. Adaptive policy frameworks were proposed to respond flexibly to changing market conditions while promoting regulatory measures to safeguard against excessive risk-taking. These recommendations aimed to foster a stable financial environment supportive of sustainable economic growth and market confidence.

MANAGERIAL ENTRENCHMENT: SCALE VALIDATION

Objective: This work focused on the influence of managerial entrenchment on investment decisions. The objective was to understand the main characteristics of this variable in order to develop an instrument that could measure it.. Theoretical Framework: The decision-making process in finance is influenced by several factors related to the decision maker, such as their psychological and cognitive biases, their risk tolerance, and even their intentions to entrench themselves in the management of a company. Behavioral finance began to address the complexity of the decision-making process, starting from the complexity of the individual themself, displacing the idea of the pragmatic decision of Homo economicus that traditional theory represented Method: A questionnaire was developed and applied to a sample of 154 managers. Then, the instrument was subjected to an exploratory factor analysis and a reliability test. Results and Discussion: The findings of this research pointed to three components for measuring managerial entrenchment. These components were called “Managers’ Decision Autonomy”, “Power Hierarchies” and “Freedom of action” in the use of the organization’s financial resources. As a result, the instrument was validated, which was found to be capable of measuring entrenchment with consistent reliability. Research Implications: The practical and theoretical implications of this research are discussed, providing insights into how the results can be applied or measured management entrenchment practices in investment decision-making. Originality/Value: Thus, this qualitative study contributes both to the finance literature by summarizing the main characteristics of managerial entrenchment and to behavioral finance studies by providing a validation instrument for one of its main subjects of study.

The influence of emotional intelligence and behavioural biases on mutual fund churning frequency: Evidence from India

Behavioural finance invalidates the rationalistic assumptions of the efficient market hypothesis by proposing a realistic explanation for overreaction and underreaction. These phenomena are caused by investors making financial decisions based on their emotions without realizing them. This study attempts to establish the effect of investors' emotional intelligence on behavioural biases, namely, herding, overconfidence bias, and disposition effects, and its consequences for the churning frequency of mutual fund portfolios. This quantitative cross-sectional study was undertaken to collect data from 499 mutual fund investors using a self-administered questionnaire. We found that the disposition effect has a negative impact and that overconfidence bias positively affects the churning frequency of mutual fund portfolios. Furthermore, emotional intelligence, particularly its subconstructs, affects herding bias and overconfidence bias, ultimately impacting the churning frequency of investors. An investor with a higher level of self-motivation is likely to have a disposition effect and herding bias. Investors with disposition impact may be encouraged to reorganize their portfolio if there are any schemes that have been providing negative returns for more than two years or that are not projected to offer significant returns in the future. By understanding how they stack up on each emotional intelligence metric, investors and financial advisors may focus on avoiding the biases that could jeopardize long-term portfolio returns.

The Impact of Investor Expectation on the Financial Decision-Making

Unlike traditional finance, behavioral finance challenges the traditional financial theory of investor rationality, emphasizing that investors are not absolutely rational in real life. This perspective provides new insights for understanding and predicting financial markets. This study examines core concepts in behavioral finance, such as loss aversion, market anomalies, momentum effects, reversal effects, endowment effects, and framing effects, and analyzes how they influence investors' financial decisions. These concepts highlight the significant role of human psychology and behavior in shaping financial decisions, thus aiding investors in making more rational choices in complex financial markets. Loss aversion, for instance, suggests that investors are more sensitive to losses than to gains, leading to suboptimal decision-making. Market anomalies, such as price bubbles and crashes, indicate that markets are not always efficient. Momentum effects suggest that past stock performance can predict future trends, while reversal effects point to the tendency of extreme stock performances to revert to the mean. The endowment effect reveals that individuals value their own possessions more highly than similar items they do not own. Lastly, framing effects demonstrate how the presentation of information can influence decision-making. Future research can delve deeper into how the framing effect can be harnessed to improve the design and marketing strategies of financial products, thereby enhancing the efficiency and effectiveness of investment decisions. This exploration could lead to more sophisticated financial products and better-informed investors, ultimately contributing to a more stable and efficient financial market.

A Study on ATM Services and Customer Satisfaction of Commercial Bank in Itahari, Sunsari Nepal

The analysis of the changing behavior of customers is crucial, and more significant to understanding behavioral finance. The objective of the study was to assess the satisfaction status of customers using ATM services. The study followed an analytical research design using a quantitative research approach. Among the ATM subscribers in Itahari, Sunsari, 140 respondents were chosen conveniently. A structured questionnaire with a five-point Likert scale was designed to collect primary data. Mean and standard deviations were used to assess the status of customer satisfaction with ATM Services, while correlation and linear regression were used to examine their associations. The results revealed that the customers are moderately satisfied with the use of ATM services. In addition, this study suggested that ATM services have a significant effect on customer satisfaction. Among the factors, the transaction fee is found a key factor influencing customer satisfaction, followed by customer support and transaction speed. This study supports the bank managers to top-up customers’ satisfaction by implementing the findings.

Impact of Herding Behavior on Investment Decisions in the Nepalese Stock Market with Mediation and Moderation Effects

This research examines the influence of herding behavior on investment decisions made in Nepal, with the moderating role of financial literacy and overconfidence as a mediating factor. Traditional financial theories suggest that rational investors make decisions based on available information to maximize their capital. In contrast, behavioral finance argues that psychological factors significantly impact financial decisions. Data were collected from 384 investors trading on the Nepal Stock Exchange using a structured survey. The findings indicate that herding behavior significantly enhances both overconfidence and investment decisions. Overconfidence has a positive impact on investment decisions. Financial literacy acts as a positive moderator, while overconfidence serves as a positive mediator between herding behavior and investment decisions. SMART-PLS was employed for data analysis.

China’s Stock Market under COVID-19: From the Perspective of Behavioral Finance

China’s Stock Market under COVID-19: From the Perspective of Behavioral Finance

Behavioral Finance: Investor Psychology and Market Outcomes

Purpose: The general objective of the study was to explore how psychological factors and cognitive biases influence investor decisions and market dynamics. Methodology: The study adopted a desktop research methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library. Findings: The findings reveal that there exists a contextual and methodological gap relating to investor psychology and market outcomes. Preliminary empirical review revealed that psychological factors such as cognitive biases and investor sentiment significantly impacted financial decision-making and market dynamics, leading to anomalies like market bubbles and volatility. It highlighted the need for integrating behavioral insights into financial models to better predict and understand market behavior, emphasizing the importance of financial literacy in mitigating adverse effects of these biases. Unique Contribution to Theory, Practice and Policy: The Prospect Theory, Herding Theory and Efficient Market Hypothesis (EMH) may be used to anchor future studies on behavioural finance. The study recommended further development of behavioral finance models to incorporate psychological factors, and for financial institutions to integrate behavioral insights into their services to guide better investment decisions. It also advised policymakers to design regulations enhancing market transparency and protecting investors from biases, while promoting financial literacy and implementing measures to monitor and mitigate systemic risks from irrational behavior.

Wisdom of crowds or awkward squad? Social interaction and the information efficiency of the Chinese capital market

Existing studies on the impact of social media on the information efficiency of capital markets have opposing views. One often-overlooked aspect in these studies is the role of investor interaction, a core feature of social media. To address this gap, we employ social network analysis (SNA) to investigate how investor interactions on Eastmoney, China's largest online stock forum, influence capital market efficiency. Our findings indicate that online investor communication can effectively disseminate firm-specific information through social networks when investor interactions are at a moderate level. However, beyond a certain threshold, heightened interactions contribute to market noise, thereby distorting the stock price discovery process. Our mechanistic analysis reveals that increased investor interactions stimulate irrational emotions at both market and stock levels, ultimately impairing capital market efficiency. This study contributes to social network analysis and behavioral finance by illuminating the impact of online social interactions among retail investors on capital market information efficiency.

Cryptocurrency and Its Role in Portfolio Diversification

Purpose: This study sought to explore cryptocurrency and its role in portfolio diversification. Methodology: The study adopted a desktop research methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library. Findings: The findings reveal that there exists a contextual and methodological gap relating to cryptocurrency and its role in portfolio diversification. Preliminary empirical review revealed that incorporating cryptocurrencies into investment portfolios offered promising diversification benefits due to their low correlation with traditional assets, despite their high volatility and regulatory uncertainties. It highlighted the significant risk management challenges posed by cryptocurrencies' extreme price fluctuations and the evolving regulatory landscape. The study emphasized the importance of careful, limited allocation to cryptocurrencies, robust risk management practices, and continuous market monitoring. Ultimately, it suggested that cryptocurrencies could enhance portfolio performance when strategically used alongside traditional diversification methods. Unique Contribution to Theory, Practice and Policy: The Modern Portfolio Theory, Efficient Market Hypothesis and Behavioural Finance Theory may be used to anchor future studies on portfolio diversification. The study recommended a cautious yet strategic inclusion of cryptocurrencies in investment portfolios to enhance diversification, emphasizing the importance of ongoing research, robust risk management, and proactive monitoring due to their high volatility and regulatory uncertainties. It called for clear and consistent regulatory frameworks to protect investors while fostering market growth, and highlighted the need for collaboration between academia, industry, and regulatory bodies to improve financial literacy and market stability. These recommendations aimed to contribute to theoretical, practical, and policy aspects of cryptocurrency investments.

NAVIGATING FINANCIAL DECISIONS: A COMPREHENSIVE REVIEW OF THEORIES, BEHAVIOURS, AND INNOVATIONS

This literature review synthesizes seminal and contemporary research on financial decision-making, emphasizing theoretical frameworks and empirical findings. Fama's (1970) Efficient Market Hypothesis sets the foundation for understanding market behavior, while Kahneman and Tversky's (1979) Prospect Theory introduces psychological influences, highlighting biases such as loss aversion (Tversky & Kahneman, 1991). Jensen and Meckling (1976) provide insights into agency theory, exploring the implications of managerial behavior on firm performance. The influence of gender on investment strategies is examined by Barber and Odean (2001), illustrating the role of overconfidence. Additionally, the impact of social interactions on financial choices is explored by Bursztyn et al. (2014). Financial literacy, addressed by Lusardi and Mitchell (2014), underscores the importance of informed decision-making in personal finance. The review also highlights the integration of behavioral insights in corporate finance, particularly in capital structure decisions (Myers, 1984) and risk management practices (Hull, 2012). Overall, the collected works illustrate a rich tapestry of factors influencing financial decisions, blending economic theory with behavioral insights, and emphasizing the necessity for ongoing research in this dynamic field. KEYWORDS: Financial Decision-Making, Behavioral Finance, Prospect Theory, Market Efficiency, Agency Theory, Overconfidence, Financial Literacy, Risk Management, Capital Structure and Social Interactions.

Analysis of Behavioral Biases Affecting Investment Decisions of Individual Investors using Analytical Hierarchy Process

Individual investors exhibiting irrational behaviors may encounter a difficult situation in financial markets. Investor trends, also known as behavioral trends, have been introduced under different headlines in different studies. Overconfidence, representation, anchoring, regret aversion, and herding were included in the research study. In this study, it was aimed to determine the order of importance of investor biases of individual investors trading in Borsa Istanbul. For this purpose, a survey questionnaire was applied to individual investors trading in BIST. Analytical Hierarchy Process was utilized in testing the research model. A total of 411 participants contributed to the study. As a result of the study, regret aversion bias and overconfidence bias were the leading biases to which individual investors attached importance. However, the criterion (C41) “I feel sorrow for the long-losing stocks I hold.” was found to rank highest among all sub-criteria. This sub-criterion is part of regret aversion bias. Regret aversion bias was also the main criterion ranking highest among all criteria. Upon considering the other sub-criteria of regret aversion bias; C42, C43, and C44 sub-criteria were found to rank second, fourth, and eleventh, respectively. C12 criterion, which ranked third, was seen to belong to overconfidence bias, and this bias ranked second among the main criteria. This research would contribute to a better comprehension of the behavioral biases that affect the decision-making of individual investors trading in BIST. The obtained results of the study are thought to contribute to the behavioral finance literature.

Accounting for bubbles: A discussion of Arif and Sul (2024)

A signal that identifies asset pricing bubbles would be valuable so investors could reposition their portfolios to weather the bubble, yet ex ante bubble identification has proven illusory. Arif and Sul (2024) study whether industry-level investment in net operating asset (NOA) accruals is an ex ante accounting-based signal that predicts bubbles. Using industry-level price run-ups across 49 countries, they find that NOA accruals predict a higher likelihood of a future crash, lower future returns, and larger analyst forecast errors, especially following run-up periods. The authors attribute these patterns to sentiment-driven overinvestment. My discussion summarizes the contributions of Arif and Sul's findings to the asset pricing bubbles, behavioral finance, and aggregate accruals literatures. I also outline empirical challenges faced by studies investigating bubbles and recommend approaches to further strengthen inferences. Finally, I propose opportunities for future research to integrate deeper accounting knowledge into bubble research.

The impact of behavioral biases on investment decisions: a serial mediation analysis

PurposeThe purpose of this study is to investigate the impact of behavioral biases on investment decisions through a serial mediation of overconfidence and disposition effects.Design/methodology/approachThe authors assess the behavioral biases affecting the investment decisions of life insurance policyholders through the serial mediation of overconfidence and disposition effects using a structured questionnaire. The study included 501 life insurance policyholders who were selected using a snowball sampling technique.FindingsThe results of this study revealed that behavioral biases influence the investment decisions of life insurance policyholders. The results also support the serial mediation model, where behavioral biases influence the investment decisions of life insurance policyholders via overconfidence and disposition effects.Research limitations/implicationsThis study makes a theoretical contribution to the field of behavioral finance by exploring the influences of behavioral biases on investment decisions. It also introduces overconfidence and disposition effects as serial mediators between behavioral biases and investment decisions. The study will be helpful for researchers, academicians and policymakers in the development of a more comprehensive model in the area of behavioral finance and in raising awareness regarding those biases among policyholders in order to improve their investment strategy.Originality/valueThis study has extended the ongoing simple mediation model by integrating overconfidence and disposition effects in a serial mediation model between behavioral biases and investment decisions. The study will contribute to the area of behavioral finance, as it is the first time this particular study has been conducted according to the authors’ knowledge.

How do market volatility and risk aversion sentiment inter-influence over time? Evidence from Chinese SSE 50 ETF options

We propose to implement the TVP-VAR-SV model and the spillover index approach to investigate the dynamics of mutual influences between market volatility and risk aversion sentiment (represented by variance risk premium), from aspects of realized variance (RV) and implied variance (IV). We innovatively study the evolution of volatility information transmission mechanisms by analyzing time-varying impulse response and dynamic connectedness in the Chinese market. Upon inspecting shock effects from investor sentiment to RV and IV, we discover that investor sentiment can cause sudden shocks on realized volatility but produce expansive shocks on expected volatility. As we compare spillover effects in call and put options, we find that (i) sentiments in put option contain more volatility information and can affect market volatility, while sentiments in call option primarily perceive volatility spillovers from market volatility, and (ii) investor sentiments in call (put) option become to present more volatility information in a bullish (bearish) market. Our study provides valuable insights on behavioral finance theory and portfolio risk management.

A rational finance explanation of the stock predictability puzzle

AbstractWe address the stock predictability puzzle, a challenge in the stock market often discussed in behavioral finance. Our approach formulates a statistical model within rational finance, avoiding reliance on behavioral finance assumptions, and integrates stock return predictability into the Black–Scholes option pricing framework. Empirical analysis focuses on the predictability of stock prices by option and spot traders, introducing a forward‐looking measure we term “implied excess predictability.” Results show that option traders' predictability of stock returns positively correlates with moneyness, whereas for spot traders, this relationship is inverse. These findings suggest a potential asymmetry in stock price predictability between spot and option traders. Additionally, we demonstrate the importance of incorporating stock return predictability into option pricing formulas, particularly for options with strike prices significantly different from the stock price. Conversely, when moneyness is close to unity, predictability is not integrated into option pricing, indicating equal information among spot and option traders. Comparison of volatility measures reveals the difference between implied and realized variances or variance risk premia as potential predictors of stock returns.

Exploring Financial Behavior: A Qualitative Investigation into Psychological Factors Influencing Risk Preferences and Investment Decisions

This qualitative study investigates the psychological determinants influencing risk preferences and investment decisions. Grounded in phenomenology and interpretivism, the research aims to explore subjective experiences related to financial behavior. Employing purposive sampling, participants were selected based on diverse criteria. Data collection involved semi-structured interviews, participant observation, and document analysis. Thematic analysis revealed intricate interplays between personal experiences, cognitive biases, emotions, social influences, and financial literacy, shaping individuals' risk perceptions and decision-making processes. Findings underscore the multifaceted nature of financial behavior, highlighting the significance of personality traits, cognitive styles, and decision-making biases. Risk-averse individuals prioritized capital preservation, while sensation seekers pursued high-risk, high-reward investments. Moreover, individuals' self-efficacy influenced their investment strategies. Cognitive biases, such as overconfidence and loss aversion, further impacted investment decisions. The study emphasizes the importance of considering psychological factors in designing personalized financial interventions and educational programs. Future research directions include longitudinal studies, cross-cultural comparisons, and interdisciplinary approaches integrating insights from psychology, economics, and finance. This research contributes to the advancement of knowledge in behavioral finance and informs practical implications for financial advisors and policymakers, aiming to enhance individuals' financial well-being and decision-making competence.