Behavioral Finance Theory Research Articles

Investor behavior in crisis: a comparative study of fear-driven downtrends and confidence-led recoveries

PurposeThe purpose of this research is to investigate the differences between financial crises of fear and confidence and the differential behavior between downtrends and recovery.Design/methodology/approachFive national stock markets have been analyzed – the USA (SP500), China (Hang Seng), Spain (IBEX 35), Japan (Nikkei) and Germany (DAX) – through the evolution of three world economic crises: the mortgage bubble crisis of 2007 in the first place, with special attention to the bankruptcy of Lehman Brothers, which will be treated as an independent crisis process, and the crisis caused by COVID-19. The behavioral finance theory, with the support of the complexity theory in the field of risk management, will establish the different behavioral biases that explain the differences between the two types of crises, fear and confidence, when confronted with risk.FindingsEconomic crises resulting from a shocking event, addressed as crises of fear in this research, such as Lehman Brothers or COVID-19, are fast-moving; all the economies analyzed show a common pattern of evolution. The difference is found in the recovery periods in which the previous parallelism does not continue. Crisis events that arise from a social context, addressed as crises of trust in this research, follow similar patterns in their evolution; nonetheless, the start date presents higher variations than those originated by a shock. These crises also lack parallelism between fall and recovery.Practical implicationsUnderstanding crisis process patterns may help to prevent them and alleviate their effects when they occur.Originality/valueUnderstanding crisis process patterns may help to prevent them and alleviate their effects when they occur. This constitutes an original field of research.

Sentiment and Stock Characteristics: Comprehensive Study of Individual Investor Influence on Returns, Volatility, and Trading Volumes

Abstract Background Traditional asset pricing models face challenges from financial anomalies, prompting exploration through behavioural finance theory. This study analyses the nuanced relationship between individual investor sentiment and key stock market variables. Objectives To assess the impact of individual investor sentiment on stock returns, volatilities, and trading volumes using the American Association of Individual Investors (AAII) sentiment index. Methods/Approach Using regression models, we examine the relationship between individual investor sentiment and various stock characteristics across 480 components of the Standard & Poor's 500 index. Results We find a positive relationship between the AAII sentiment index and stock returns and a negative relationship with volatility and trading volume. Conclusions Our study contributes to understanding the intricate role of individual investor sentiment in financial markets.

FINANCIAL LITERACY, RISK TOLERANCE, RETURN, AND INTEREST IN STUDENT INVESTMENT DECISIONS

Investing in the capital market is growing rapidly in Indonesia, as evidenced by the increasing number of investors registered at PT Kustodian Sentral Efek Indonesia and most of them are young investors under 30 years old. The objective of this research is to examine how financial literacy, risk tolerance, return, and interest affect decision-making when it comes to investments. The participants involved in this study are students enrolled in the Bachelor of Accounting program at Udayana University's Faculty of Economics and Business from the graduating classes of 2020 and 2021. The sample was determined using the purposive sampling technique, a sample of 242 respondents was obtained. The data analysis technique uses multiple linear regression analysis. The results of the analysis prove that financial literacy, risk tolerance, return, and interest have a positive effect on students' decision to invest. The results of this study can provide empirical support in behavioral finance theory and theory of planned behavior which explain behaviors related to students' decisions to invest.

Fostering Future Investors: Analysing Determinants of Stock Market Participation Among Malaysian Students using PLS-SEM

Participation in the stock market is crucial for financial engagement and wealth creation. However, specific population segments, such as students from higher learning institutions, may exhibit lower stock market participation levels. Addressing this issue, this study uses the behavioral finance theory to examine how financial literacy, financial well-being, herding behavior, overconfidence bias, risk tolerance, social interaction, and investment intention influence stock market participation. Data was collected through a self-administered questionnaire distributed to 669 university students in Malaysia aged 17-30 years old. The findings reveal that financial literacy, herding behavior, risk tolerance, and social interaction positively influenced investment intention. The study also discovered that investment intention positively influences stock market participation. This study has made significant contributions to both theory and practice. Theoretically, this study contributes to the literature by confirming the positive relationship between financial literacy and investment intention. This study contributes to the development of more effective interventions and policies that not only educate students about an essential aspect of financial literacy but also prepare them for a financially secure future.

The Mediating Effect Of Market Liquidity On The Relationship Between Financial Liberalization And Stock Market Returns Among East Africa Community Member Countries

The motivation for this study stems from the critical role of financial markets in economic development and the need to understand the factors influencing stock market performance in the East African Community (EAC) member countries. Financial liberalization, market liquidity, and macroeconomic stability are pivotal in shaping stock market returns. However, empirical studies examining these relationships within the EAC context are limited, prompting this comprehensive analysis. The general objective of this study was to investigate the effect of financial liberalization, market liquidity, and macroeconomic factors on stock market returns among EAC member countries. The study was anchored on the theory of financial liberalization, neoclassical theory, efficient market hypothesis, behavioral finance theory, and the general theory of employment, interest, and money. Data were collected from secondary sources, including financial reports, stock exchange databases, and relevant economic databases, covering the period from 2002 to 2021.The study employed fixed-effects regression models, chosen based on the Hausman specification test, to control for unobserved heterogeneity across countries. Baron and Kenny’s approach was used to test for mediation and moderation effects. The analysis involved examining the direct and, mediating relationships between the key variables. The findings revealed that financial liberalization significantly and positively affects stock market returns. Conversely, market liquidity was found to mediate this relationship, enhancing the positive effects of financial liberalization. The study concludes that financial liberalization is a crucial determinant of stock market performance in the EAC region. Market liquidity plays a significant role in amplifying the benefits of financial liberalization. For policymakers, the study recommends policymakers in EAC should focus on developing infrastructure that supports efficient trading systems. This recommendation is based on the finding that higher market liquidity significantly boosts the positive effects of foreign assets and liabilities on stock market returns

Advancements in Stock Market Prediction Techniques: A Comprehensive Survey

The stock market, known for its unpredictable nature and complex workings, has been the focus of significant study. Conventional models frequently fail to fully capture the complex and diverse nature of stock market behavior. With the increasing complexity of financial markets, there is a rising demand for advanced strategies that can offer investors precise predictions and essential insight. There are several studies in this regard, from which we chose 24 modern studies from the year 2018 to the year 2023 in various ways to come out with results that are the focus of a new start in the prediction. This review collected different machine learning methods and deep learning techniques, including deep neural networks, which were then used to build powerful prediction models. Integrating behavioral finance theory with quantitative indicators and financial news provides a unique perspective on stock market dynamics. Also, The Efficient Market Hypothesis (EMH) highlights the significant impact of future information, such as news, on the valuation of stocks. Combining deep learning techniques in forecasting and examining the stock market represents an essential stage in financial research, it offers a more intricate comprehension of the intricacies of stock market dynamics. However, obstacles still need to be overcome, and it is essential to use prudence when applying reported accuracies to actual trading situations. The convergence of behavioral finance, efficient market hypothesis, and deep learning present opportunities for more investigation, offering a more comprehensive method of forecasting stock market trends

Understanding Behavioural Biases Driving Equity Investors in India: A Factor Analysis Approach

In the dynamic realm of equity investment decisions, this study challenges the traditional assumption of investor impartiality and rationality, arguing that investors’ choices are often shaped more by beliefs and psychological inclinations than by objective reasoning alone. Drawing from behavioural finance theory, which contests the adequacy of the standard finance model in capturing the nuances of decision-making, this research delves into the psychological forces influencing private investors. Recognizing the prevalent biases coloring their decisions, the study investigates common prejudices impacting investor choices. Leveraging survey data from 375 equity investors, the research employs exploratory factor analysis and regression models to disentangle the effects of cognitive biases, such as the gambler’s fallacy, overconfidence, aversion to ambiguity, lack of representativeness, aversion to loss, and anchoring. The findings challenge the assumption of investor rationality, offering valuable insights into the complexities of financial decision-making. Notably, the study underscores a robust and positive association between these biases and equity investment decisions, shedding light on the intricate interplay between psychological factors and investment behaviour.

The Failure of Silicon Valley Bank: A Test of Market Efficiency

The unexpected collapse of Silicon Valley Bank (SVB) on March 10, 2023, sent shockwaves through the tech industry. SVB, a long-standing financial institution serving tech startups for nearly four decades, suddenly shifted from solvency to insolvency within 48 hours, marking the second-largest bank failure in U.S. history. This event provides an excellent opportunity to test the Efficient Market Hypothesis (EMH), particularly its semi-strong form, which posits that rapid information absorption prevents significant stock price gains in response to new information. This research uses the standard event study methodology in the finance literature to investigate SVB’s collapse and its impact on the stock prices of 30 banks traded on the New York Stock Exchange. The study aims to discern whether stock returns exhibited reactions prior to, on, or after the public announcement of SVB’s failure, thereby assessing market efficiency. Using historical stock and S&P 500 index data, the study analyzes holding period returns, performs regression analyses for pre-event periods, and calculates average excess returns. Results indicate statistically significant negative impacts on stock prices surrounding and on the event date. Furthermore, consistent with behavioral finance theory, a decline in adjusted stock prices approximately 7 days before the event suggests anticipatory market behavior, in line with semi-strong market efficiency. SVB’s case emphasizes the role of external factors, regulatory changes, and industry concentrations in shaping market responses. This research contributes empirical evidence to the discourse on market efficiency, highlighting the need for a nuanced understanding of market behaviors during crises. Lessons from SVB’s collapse will inform regulatory and risk management strategies, impacting future discussions on market efficiency. Likewise, the study results support the semi-strong form efficient market hypothesis and suggest the possibility of trading on this information up to 7 days prior to the announcement consistent with the behavioral finance literature (Bacon & Howell 2021). This study provides valuable insights into market dynamics during unprecedented events, influencing future discussions on regulation, risk management, and market efficiency.

HERDING BEHAVIOUR MARKET INFORMATION AND INDIVIDUAL INVESTOR DECISION-MAKING AT THE NAIROBI SECURITIES EXCHANGE

This paper examined the relationship between herding behaviour and individual investor decision-making at the Nairobi Securities Exchange. In addition, the study assessed the moderating effect of market information on the relationship between herding behaviour and individual investor decision-making at the Nairobi Securities Exchange. The study was anchored on behavioural finance theory and was guided by a correlational research design. The study's target population was 2.03 million individual investors who traded at the Nairobi Securities Exchange through the 17 licensed brokerage firms in Kenya. A structured questionnaire was used to collect data and Internal consistency of the instruments was measured using Cronbach’s alpha coefficient, where a coefficient of 0.865 was obtained. The obtained data was analyzed descriptively using frequencies, means, and standard deviation and inferentially by correlation and multiple regression models. The findings revealed that herding behaviour (r = 0.235; β =0.180 p<0.05) had a positive and significant relationship with individual investor decision-making. Jointly, the study established that herding behaviour explains a 59.6% change in individual investor decision-making. In addition, the study established that market information had a positive significant moderating effect on the relationship between herding behaviour and individual investor decision-making as the moderator increased the R2 from 59.6% to 61.0%, which is an R-square change of 1.4%. The study concluded that herding behaviour had a significant relationship with individual investor decision-making at the Nairobi Securities Exchange. The study recommended that investors understand market trends, financial statements, and economic indicators and continue seeking advice from financial experts. NSE should also provide regular market analysis, ensure transparency in market operations to build investor confidence and introduce investment products that cater to different risk profiles, such as low-risk mutual funds. The findings of the study could be of significance to policymakers, financial experts, academicians, scholars, and theoretical developments.

Behavioral Biases and Decision-Making in Investment among working individuals in the education sector

This study investigates the impact of behavioral biases on investment decisions among working individuals within the education sector. Behavioral finance theory serves as the theoretical foundation, emphasizing the role of psychological factors in shaping investment choices. The study employs a mixed-methods approach, combining surveys and in-depth interviews to gain insights into the investment behavior of educators, administrators, and support staff. Our findings reveal that a range of behavioral biases, including loss aversion, overconfidence, and herding, significantly influence investment decisions. Working professionals in the education sector often exhibit a strong preference for conservative investment strategies, even when market conditions may suggest otherwise. Psychological factors, such as fear of losses and a tendency to follow trends, play a vital role in shaping investment behavior. These biases are further exacerbated by a lack of financial literacy and investment education. The implications of this research suggest a need for targeted financial education programs to mitigate behavioral biases and enhance decision-making among working individuals in the education sector. Addressing these biases can lead to more informed and diversified investment strategies, potentially improving financial security and long-term wealth accumulation for this demographic. This abstract provides a brief overview of the research focus, methodology, key findings, and the potential implications of the study. It gives readers a clear understanding of the research's scope and significance.

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.

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.

Role of Financial Literacy in Household Investment Decisions in Iraq

Purpose: The aim of the study was to assess the role of financial literacy in household investment decisions in Iraq. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The study indicated that households with higher levels of financial literacy tend to make more informed and effective investment choices, which lead to better financial outcomes. These households are more likely to participate in financial markets, diversify their investments, and utilize a broader range of financial instruments, which helps in mitigating risks and enhancing returns. Financially literate individuals are also more adept at understanding complex financial products, assessing investment risks, and planning for long-term financial goals such as retirement. Conversely, a lack of financial literacy can result in poor financial decisions, leading to lower participation in the stock market, inadequate savings, and suboptimal investment portfolios. Thus, enhancing financial literacy is essential for empowering households to make sound investment decisions, ultimately contributing to greater financial stability and wealth accumulation. Implications to Theory, Practice and Policy: Behavioral finance theory, portfolio theory and agency theory may be used to anchor future studies on assessing the role of financial literacy in household investment decisions in Iraq. In terms of practical recommendations, developing and implementing targeted financial education programs is essential. These programs should focus on improving specific aspects of financial literacy relevant to investment decisions. From a policy perspective, advocating for policies that support the integration of financial literacy education into school curricula at all levels is essential.

Effect of Interest Rate Changes on Stock Market Volatility in Congo

Purpose: The aim of the study was to assess the effect of interest rate changes on stock market volatility in Congo. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Changes in interest rates have a notable impact on stock market volatility. When central banks adjust interest rates, it influences investor sentiment and economic forecasts. Typically, an increase in interest rates makes borrowing more expensive, which can dampen corporate profits and economic growth, leading to higher market volatility as investors reassess the value of stocks. Conversely, a decrease in interest rates generally lowers borrowing costs, potentially boosting corporate earnings and economic expansion, which can initially reduce market volatility. However, the long-term effects might differ as lower rates can also lead to overvaluation concerns, eventually increasing volatility. Additionally, interest rate changes signal monetary policy shifts and broader economic conditions, further influencing investor behavior and stock market dynamics. Overall, interest rate fluctuations are a critical factor contributing to stock market volatility through their direct and indirect effects on economic activities and investor perceptions. Implications to Theory, Practice and Policy: Efficient market hypothesis, portfolio theory and behavioral finance theory may be used to anchor future studies on assessing the effect of interest rate changes on stock market volatility in Congo. For practical implications, investors and financial institutions should develop risk management strategies that account for the short-term volatility spikes following interest rate announcements. From a policy perspective, policymakers should consider the lagged effects of interest rate changes when formulating monetary policy to ensure smoother market transitions.

Unveiling the Nexus Between Crises, Investor Sentiment, and Volatility of Tourism-Related Stocks: Empirical Findings From Pakistan

This study investigates the predictive power of sentiment metrics concerning the volatility of tourism-related stocks listed on the Pakistan Stock Exchange (PSX) during recent crises. We employed univariate and multivariate GARCH-family econometric models to analyze daily data collected from March 2020 to April 2023. The data is categorized into two periods: A (COVID-19 until February 2022) and B (the vote of no-confidence motion until April 2023). The findings indicate that Market Sentiment (MS) plays a more significant role than individual sentiment in predicting stock price volatility and negatively impacts return volatility. During period A, the Fear Index (FI) and in B, economic policy uncertainty (EPU) were identified as factors contributing to increased fluctuation in tourism-related stocks. Additionally, MS exhibited a heightened level of bearishness compared to the COVID-19 era. The multivariate BEKK-GARCH analysis revealed that MS past volatility negatively spillover onto the current conditional volatility of PSX firms. This highlights the paramount importance of MS in understanding stock price fluctuations in the PSX. Interestingly, the technology sector exhibited lower sensitivity across the analysis. This study provides valuable insights for decision-makers by elucidating the principles of behavioral finance theory within the context of the PSX. They should prioritize long-term strategies to institutionalize investors, enhance their emotional intelligence, and mitigate psychological biases in the market.

Multi-feature fusion stock prediction based on knowledge graph

PurposeStock prices are subject to the influence of news and social media, and a discernible co-movement pattern exists among multiple stocks. Using a knowledge graph to represent news semantics and establish connections between stocks is deemed essential and viable.Design/methodology/approachThis study presents a knowledge-driven framework for predicting stock prices. The framework integrates relevant stocks with the semantic and emotional characteristics of textual data. The authors construct a stock knowledge graph (SKG) to extract pertinent stock information and use a knowledge graph representation model to capture both the relevant stock features and the semantic features of news articles. Additionally, the authors consider the emotional characteristics of news and investor comments, drawing insights from behavioral finance theory. The authors examined the effectiveness of these features using the combined deep learning model CNN+LSTM+Attention.FindingsExperimental results demonstrate that the knowledge-driven combined feature model exhibits significantly improved predictive accuracy compared to single-feature models.Originality/valueThe study highlights the value of the SKG in uncovering potential correlations among stocks. Moreover, the knowledge-driven multi-feature fusion stock forecasting model enhances the prediction of stock trends for well-known enterprises, providing valuable guidance for investor decision-making.

Literature Study of Stock Investment Risk Analysis for Beginner Investors

Awareness of investment has been owned by all parties, including young people who unfortunately still do not understand the risks of investment. This can certainly have a negative impact that is far from the expectations or objectives of the investment itself. This article was compiled using a literature review based on the Google Scholar database for the period 2014-2024, with one of the objectives to study the risks often experienced by novice investors. The results of the literature review show that investment decisions whose decision making is ideally rational, but often become irrational and this condition is very relevant to various theories such as the theory of Efficient Market Hypothesis (EMH), the theory of Behavioral Finance, the Theory of Planned Behavior.

Does ownership structure drive the effect of CEO overconfidence on earnings quality?

PurposeThe purpose of this paper is to examine the effect of chief executive officer (CEO) overconfidence on earnings quality and the moderating role of ownership structure as a crucial corporate governance device.Design/methodology/approachThe paper uses the generalized method of moments (GMM) estimation method to test our models on a sample of 335 French companies between 2009 and 2020, i.e. 4,020 observations.FindingsThe results show that CEO overconfidence negatively affects earnings quality. This result supports the predictions of behavioral finance theory and suggests that CEO overconfidence is a behavioral bias that affects the quality of earnings. The authors also examined the effect of different types of ownership structures on this relationship. The results show the significant role of controlling shareholders, owner-managers, families and institutional investors in mitigating the negative effect of CEO overconfidence on earnings quality.Research limitations/implicationsThis paper has some limitations. First, other types of ownership structures could have been analyzed such as state ownership. Second, we ignored the role of the board of directors as an important governance mechanism in controlling overconfident CEOs’ actions.Practical implicationsCompanies should be aware of the potential risks associated with CEO overconfidence, which can compromise the faithful representation of earnings. This highlights the importance of effective monitoring and internal controls to detect and prevent such practices, which involve the role of ownership structure.Originality/valueThis paper addresses the effect of CEO overconfidence on earnings quality and provides new evidence on the role of different ownership structure types in shaping this relationship. Additionally, this paper sheds new light on how overconfident CEOs may behave in challenging times.

The Influencing Mechanism of Managerial Myopic Behavior on Enterprise Sustainable Development Performance: Evidence Based on Listed Companies in China

Corporate sustainability is a key concern in today’s world. This research examines the relationship between managerial myopic behavior and corporate sustainability performance in Chinese A-share listed companies from 2013 to 2022. Based on behavioral finance theory and time orientation theory, our research provides novel insights into how time preference in managerial decisions significantly affects corporate sustainable development. We also investigate how myopic behavior by managers can adversely affect a company’s sustainable development performance. Using a robust dataset, we describe the mechanisms by which managers’ myopic behavior affects sustainability performance, especially in two aspects: financialization of assets and green innovation capability. The results of our research show the following: (1) managers’ myopic behavior adversely affects corporate sustainability performance; (2) asset financialization and green innovation capability play mediating roles; and (3) unlike the findings of the existing research, this study found that the linear moderating effect of media attention plays a significant “inverted U-shaped” moderating role in the relationship between the two influences.

Behavioral traits of fund managers: a systematic literature review

PurposeThe purpose of the study is to investigate, synthesize and critically evaluate empirical research findings on the behavioral traits of fund managers from 1994 to 2024. The ultimate goal is to provide a unified body of literature on three broad topics: first, fund managers' demographic and professional characteristics, such as age, gender, level of education and years of industry experience; second, fund managers' social and political connections; and third, fund managers' behavioral biases that lead to irrational investment decisions.Design/methodology/approachThe relevant papers from selected journals were discovered and manually validated using the Scopus database. From 317 retrieved documents, 57 relevant articles were chosen and analyzed after the forward and backward search of the existing articles.FindingsThis paper presents a categorized summary of behavioral factors that have gained a foothold in influencing the behavior of fund managers in fund management research, with several studies demonstrating their significance leading to improved prediction and model precision, as this review indicates. In addition, the study summarized the contributions of prior empirical studies within the aforementioned three major categories and illustrated their consequences.Originality/valueThe present study contributes to the understanding of the effects of behavioral finance theories on fund managers by providing meaningful explanations of their behavioral traits based on empirical evidence and existing trends and knowledge gaps, both of which can influence the future direction of research.