“Unraveling behavioral biases in decision making: A study of Nepalese investors”

The Nepalese stock market has experienced substantial transformations in recent years. Research on investors’ herding behavior is of paramount importance since it explores the influence of collective choices made by investors, which could result in intensified market price fluctuations. This study examined the influence of behavioral biases on investment decisions among Nepalese investors – general individuals who actively participate in the country’s stock market, considering overconfidence, representative, anchoring, regret aversion, and herding biases as explanatory variables, with investment decisions as the response variable. The study employed a linear regression model, establishing relationships using a structured questionnaire with 379 observations. The study revealed the significant influence of overconfidence, anchoring, and regret aversion biases on investment decisions among Nepalese investors. Conversely, the influence of representative bias had a little impact on investment choices, and herding behavior showed no significant relationship with investment decisions. Hence, it suggests that behavioral biases have a greater impact on individual investment choices in the Nepalese financial market. It is essential for investors, advisers, and policymakers to be aware of and address these biases to make well-informed decisions, maintain financial stability, and foster market development.


INTRODUCTION
Nepal's stock market has a very short history compared to other countries.Established in 1993, the Nepal Stock Exchange (NEPSE) serves as the sole stock market in the country.On January 13, 1994, the openoutcry trading system introduced a total of 37 listed companies.The NEPSE has recently experienced a significant transformation, marked by an influx of participants, increasing trade volumes, a strong adoption of digitization, and increase in the number of listed companies to over 300.Notably, the Security Board of Nepal (2023) reported a remarkable surge of 41% in DEMAT accountholders and a 27% expansion in the active investor base in 2022 compared to the preceding year, indicating a growing interest and participation in equity investments.This stands as evidence of an emerging market in the South Asian region.
In the context of the Nepalese stock market, where economic fundamentals and company strength play a significant role, it is important to acknowledge the presence of a compelling phenomenon that often impacts its trajectory: herding behavior.Investors may occasionally base their judgments on the behavior of others rather than their research or evaluation of economic issues, leading to collective market movements.Collective behavior is not limited to worldwide markets; it is also evident in the country's stock market, providing compelling evidence of market inefficiency and irrationality.As a result, many investors in Nepal rely on paper and digital media and seek guidance from their interpersonal circles, professionals, and family members when making investment decisions.The prevalent tendency among investors for mass purchases and selective selling, for instance, has led to abnormally large gains, as seen by the multiple ups and downs in stock prices.In August 2021, the market index temporarily hit its highest level ever recorded at 3,198.6 and has been consistently declining since then as a result of the prevailing negative sentiment among investors.Moreover, this occurrence is taking place in the primary market, where several companies with poor ratings have seen oversubscription.The observed trend suggests that herding behavior may have substantially impacted the various price fluctuations in Nepal's stock market.

LITERATURE REVIEW AND HYPOTHESES
In modern finance theory, seminal contributions from scholars such as Markowitz (1952) have paved the way for understanding investment strategies.Markowitz's groundbreaking Modern Portfolio Theory (MPT) advocated for diversification of assets to achieve optimal risk-return balance.This foundational concept, coupled with subsequent developments like the Capital Asset Pricing Model (CAPM) introduced by Sharpe (1964), revolutionized the evolution of assets with market movements.Further advancements came with the introduction of multifactor models, such as the Fama-French three-factor model, which incorporated additional risk factors like company size and value, providing a more nuanced understanding of stock returns (Fama & French, 1992).These multifactor models expanded the traditional framework, acknowledging the diverse interplay of various factors influencing asset pricing.However, the influence of behavioral biases on investors' decisions has become a focal point in contemporary finance research, adding complexity to these models and challenging their assumptions.For instance, Heuristic Theory explores how individuals rely on mental shortcuts and rules of thumb to simplify complex decisions, often leading to systematic biases.On the other hand, Prospect Theory focuses on how people assess potential outcomes, emphasizing loss aversion and framing effects.Behavioral biases introduce psychological dimensions to investment decisions, shaping risk perceptions and altering decision-making processes, thus necessitating a comprehensive integration of behavioral insights within the evolving context of asset pricing theories.
Behavioral finance recognizes that investors can exhibit irrational behavior due to cognitive biases, emotions, and heuristics.This leads them to make decisions that deviate from purely rational choices assumed by traditional finance theories, where the decisions are based on all available information and aim to maximize their utility.Kumar (2018) explored the phenomenon of anchoring bias, revealing that newcomer investors were mainly prone to making irrational decisions compared to their experienced counterparts.Anchoring, a cognitive heuristic, explains how people rely heavily on initial reference points when making decisions, often leading to distorted judgments, a factor significantly influencing investment choices.Kahneman and Tversky (1979) explored the influence of emotional biases, such as overconfidence, loss aversion, and herding behavior, on individuals' decision-making processes within the framework of prospect theory.This psychological theory elucidates how individuals assess potential losses and gains, offering a comprehensive understanding of how emotions and cognitive biases influence financial choices.It claims that people evaluate their perceptions of loss and gain as unbalanced, and they tend to prioritize potential losses more than equivalent profits, a phenomenon known as loss aversion.These frameworks provide a valuable understanding of how individuals manoeuvre complex choices, shedding light on the underlying factors influencing their decisions under uncertain circumstances.
Besides heuristics and prospect theories, which serve as foundational concepts shedding light on human decision-making, the terrain of behavioral biases extends far beyond these frameworks.For instance, overconfidence bias, where individuals tend to overestimate their abilities, has been extensively studied in behavioral economics (Dahal, 2022;Lichtenstein et al., 1982).Anchoring bias, a phenomenon where people rely heavily on initial information when making decisions, has been researched and documented in various studies (Tversky & Kahneman, 1974).Mental accounting, the practice of organizing finances into separate categories, has been discussed in behavioral finance literature (Dahal, 2021;Thaler, 1999).
Regret aversion has been a significant topic in decision-making research, explaining the reluctance to take action to avoid future regret (Zeelenberg, 1999).Herding behaviors, where individuals follow the crowd, have been widely explored in behavioral finance (Bikhchandani et al., 1992).The endowment effect, which involves valuing one's possessions more, has been studied in behavioral economics experiments (Kahneman et al., 1990;Karki et al., 2023).
Moreover, framing effects, revealing how the presentation of information can alter perceptions, have been extensively researched in psychology and decision-making literature (Ghimire et al., 2023;Tversky & Kahneman, 1981).Amidst these complexities, investors face limits due to bounded rationality, as emphasized in the realm of behavioral finance (Simon, 1955).This body of research stresses the inherent perceptive limitations that impact investors' choices.Understanding these interconnections, as explored in various studies, provides a holistic view of behavioral biases, enriching the understanding of investors' decisionmaking process.
The major objective of this study is to investigate the impact of behavioral biases on investor decision making, filling a critical void within the everchanging world of financial markets.

METHODOLOGY
The ( ) Substituting the values, where Z (1.96) represents the area under the acceptance region in a normal distribution for a 95 % confidence level, and e signifies the desired precision or margin of error (5%), the estimated proportion (p) of the attribute in the population was set at 0.5, with (1−p).
( ) 1.96 0.5 1 0.5 364.16 365.0.05 According to the recommendation, a minimum sample size of approximately 365 was suggested; thus, the study employed 379 observations.It was based on the primary source of information; the structured questionnaire, incorporating a fivepoint Likert scale, has been developed and administered to collect data to meet the study's objectives.The survey questionnaire was split into two parts, comprising 34 items.The first section included four questions focusing on respondents' demographic and general information.The final part requested literature-based unraveling of behavioral biases in decision-making measures, including 30 queries, and a series of close-ended questions were composed to get the required information from the respondents.All the survey items in the final part of the questionnaire were assessed on a five-point Likert-type scale with 1 = strong disagreement to 5 = strong agreement.The study employed a field survey approaching 1,000 potential investors from diverse groups to collect the required data during 120 days of May to August 2023.Three hundred seventy-nine correctly filled questionnaires were obtained, representing a 37.90 % response rate, and their responses were utilized in the study.
The internal consistency of the study variable questionnaire items has been evaluated with Cronbach's alpha (α = 0.818) and with an interitem coefficient (r = 0.131) from 30 unraveling behavioral biases in decision-making measures, ensuring the reliability of the measurement.Educationally, the respondents exhibit a majority (63.5 %) of Bachelor's degrees, followed by Master's degrees or higher qualifications, emphasizing the expertise within the surveyed group and the presence of individuals with undergraduate educational backgrounds.According to the occupation, respondents exhibit a diverse array of occupations, highlighting the multidisciplinary nature of the surveyed group.A large portion of the respondents' occupations include academicians, representing the educational sector's active participation.The category 'Others' includes a variety of professionals, adding the second richness to the dataset, followed by the stock market investors.The stock market analysts and security market businesspeople include third and fourth categories of occupation of respondents, but there are no significant numbers.

Correlation statistics
Table 3 presents correlation coefficients, indicating the strength and direction of relationships between dependent and independent variables.A strong positive correlation of 0.512 reveals that overconfidence significantly corresponds to increased investment decisions.Investors demonstrating overconfidence tend to make more investment choices, potentially driven by their excessive self-assurance in their judgment.The representative bias has revealed a positive correlation of 0.536, which signifies that increasing this bias intensifies investors' investment decisions.This suggests that when investors perceive new opportunities as mirroring past successes, they are inclined to make substantial investment choices.
The anchoring bias has revealed a positive correlation of 0.478; thus, an increase in this variable leads to a moderate rise in the investment decision.Therefore, investors influenced by anchoring biases tend to base their decisions on initial information, impacting their investment choices significantly.Regarding the correlation of regret aversion bias, a moderate negative relationship implies that for an increase in regret aversion bias, there is a decrease in investment decisions.Investors prone to regret aversion tend to be cautious, avoiding actions that might lead to future regrets, which moderately impacts their investment choices by reducing their willingness to make investment decisions.However, the herding bias exhibited a weak positive correlation of 0.269, indicating a subtle tendency for investment decisions to rise when herding bias increases.While not highly influential, individuals influenced by herding behaviors demonstrate a mild inclination to follow the crowd in their investment choices.

Regression insights
Table 4 presents the outcomes of a linear regression analysis to assess the influence of critical psychological decision-making biases, namely overconfidence bias, representative bias, anchoring bias, regret aversion bias, and herding bias, on the investment choices undertaken by individuals within the Nepalese financial market.This analysis seeks to offer an in-depth understanding of the underlying forces that drive financial decisions through key statistical measures such as F-statistics, adjusted R-squared value, p-value, and collinearity statistics.
The obtained F-statistic of 94.519, coupled with a p-value of 0.000, strongly suggests a meaningful linkage between the presumed causes and effects.This statistical significance indicates that the association observed in the data is highly improbable to have occurred by random chance alone.A substantial and noteworthy connection exists between the specified behavioral biases and investors' decisions.An adjusted R-squared value of 0.553 indicates that approximately 55 percent of the variability in the investors' decisions can be described by the independent variables included in the regression model; that is, more than half of the changes observed in investors' decisions can be attributed to the behavioral biases under consideration, and thus suggests a moderately explanatory solid power to explain the outcome.The collinearity statistics reveal tolerance values ranging from 0.564 to 0.757 (>0.1) and Variance Inflation Factor (VIF) values between 1.320 and 1.774 (<10).
These results indicate acceptable levels of multicollinearity among the independent variables in the model and thus ensure the reliability of the regression outcomes.
The reported coefficient for overconfidence bias in this regression analysis is 0.389, with a p-value of 0.000.This indicates a positive and significant relationship between overconfidence bias and investment decisions among individuals.Specifically, for every unit increase in overconfidence bias, there is a corresponding increase of 0.389 units in the investment decisions made by individuals.The relationship is statistically significant, as reflected by the low p-value of 0.000, suggesting that the impact of overconfidence bias on investment decisions is not due to random chance.There is a positive relationship between the representative bias and investment decisions, with a beta coefficient of 0.110; however, due to the p-value being 0.022, slightly above the commonly used threshold of 0.05 for statistical significance, the strength of this relationship might not be robust enough to draw reliable conclusions.While the beta coefficient for anchoring bias is 0.214 (p = 0.000) in the context of investment decisions, it indicates a statistically significant relationship between anchoring bias and investment decision-making.
Regarding the strength and direction of the relationship of regret aversion with investment decisions, the study revealed a beta coefficient of 0.278.The corresponding p-value of 0.000 satisfies the relationship's statistical significance.In contrast, a beta coefficient of -0.038 indicates a negative association with the investors' investment decisions in herd behavior.However, the corresponding pvalue of 0.300 suggests that this association lacks statistical significance at the chosen confidence threshold, highlighting a distinct nature of investor behavior.

Hypotheses testing results
Table 5 provides a summary of the hypothesistesting outcomes.It reports each of the coefficients of the hypothesis and its corresponding p-values, along with the decisions chosen using the predefined level of significance of 5 percent.

CONCLUSION
The primary purpose of this study was to examine the impact of behavioral biases on investment decisions in the Nepalese stock market, with a specific focus on overconfidence, representativeness, anchoring, regret aversion, and herding biases as key explanatory variables.This study revealed the critical relationship between behavioral biases and their profound influence on individual investment decisions within the Nepalese financial market.The statistical significance indicated by the obtained F-statistic and corresponding low p-value evidenced the profound impact of behavioral biases on investors' decisions.However, the F-statistics value of 94.519 indicates that only 5.481 percent of the variability in decisions to play remains unexplained.This implies that factors such as market conditions and other biases also play a role in influencing individual investors' decision processes in the context of Nepal.The regression results revealed a substantial influence of fundamental behavioral biases -overconfidence bias, representative bias, anchoring bias, regret aversion bias, and herding bias -on investors' investment choices.
The study demonstrated that overconfidence bias exerts a notable influence, leading individuals to make decisions based on an inflated sense of confidence, which, although enhancing investment choices, introduces significant risks.Representative bias, although present, did not exhibit a substantial impact on investment decisions, suggesting the presence of other influential factors.Anchoring bias emerged as a critical factor, emphasizing the tendency of investors to anchor onto initial information, shaping subsequent financial choices.This bias necessitates investor awareness and proactive measures to counter its effects, ensuring informed decision making and averting potential financial losses.Additionally, regret aversion bias exhibited a significant influence, leading to conservative decision making.While herding bias negatively impacts individual investment decisions, its lack of statistical significance highlights the complexity of investor behavior, indicating that investors rely on diverse information sources in their decision-making process.
These research findings, aligning with global studies on how people's biases influence investment choices, emphasize the crucial importance for investors, financial advisors, and policymakers in Nepal to recognize and address these biases.In essence, this study enriches the understanding of behavioral biases and investment decisions among investors in Nepal, providing a robust foundation for future research and targeted interventions to address and mitigate the issues.As the financial environment evolves amidst these complexities, cultivating awareness and actively managing these biases becomes paramount, empowering individuals to make rational and informed investment choices and contributing to the financial market's overall growth and stability.In addition to the direct behavioral biases studied, this study acknowledges the indirect influence of socio-economic and cultural factors on investors' decision-making processes.While these aspects have not been the primary focus of this study, their potential impact on investment choices forms an unexplored avenue for future research.Therefore, the study lays the groundwork for future investigations, enriching the originality of this research by paving the way for a broader exploration of the dynamics that influence investors' investment decisions in recognizing the significance of these factors in shaping investor behavior.

Table 2 .
Demographic profile of respondents

Table 4 .
Regression insights of behavioral biases on investor decisions