Herding Behavior Research Articles

Financial stability at risk: evidence from market overreaction and herding behaviour in developed and emerging markets

PurposeThis study examines the relationships between herding behaviour, market overreaction and financial stability in developed and Brazil, Russia, India and China (BRICS) markets from 1 January 2017 to 31 December 2023. It identifies the significant differences in these phenomena across different market types and their implications for financial stability.Design/methodology/approachThis study employs panel data regression, quantile regression, Granger causality tests and the Baron and Kenny mediation model to analyse the data. These methods are used to explore the extent to which herding behaviour exacerbates market overreaction and affects financial stability.FindingsThe results reveal that herding behaviour exacerbates short-term market overreaction, leading to increased financial instability, particularly in BRICS markets. In contrast, herding behaviour does not significantly impact intermediate-term overreactions in developed markets. The study also finds that market overreaction significantly mediates the relationship between herding behaviour and financial stability.Practical implicationsThese findings have practical implications for policymakers. Understanding how herding behaviour and market overreaction impact financial stability can help formulate strategies to enhance market stability and mitigate systemic risks, particularly in more volatile BRICS markets.Social implicationsEnhanced financial stability has broad social implications, including improved investor confidence and economic growth. Policymakers can use these insights to create more stable financial environments, which can lead to more robust economic development and reduced vulnerability to financial crises.Originality/valueThis study provides new insights into the differential impact of herding behaviour and market overreaction on financial stability in developed and BRICS markets. By confirming the mediating role of market overreaction, this study enhances our understanding of financial market anomalies and contributes to the literature on financial stability.

Psychological explanations for analysts' herding behavior: A study on the impact of information cascades and reputational concerns

This study investigates the influence of information cascades and reputational concerns on analysts' herding behavior in financial markets. Using a mixed-methods approach combining archival data analysis and surveys of 5,237 financial analysts covering S&P 500 companies from 2014 to 2023, we examine the interplay between these psychological factors. Our findings reveal that both information cascades and reputational concerns significantly impact herding behavior, with a notable synergistic effect when combined. Structural equation modeling demonstrates that information cascade strength positively correlates with herding behavior (β = 0.43, p < .001), partially mediated by perceived market consensus. Reputational concerns also show a strong positive association with herding (β = 0.51, p < .001), moderated by career stage. Importantly, the interaction between information cascades and reputational concerns (β = 0.24, p < .001) suggests that their combined effect is greater than the sum of their individual impacts. This effect varies across analyst characteristics and market conditions, with stronger influences observed in small-cap stocks and high-volatility periods. Time-series analysis reveals dynamic fluctuations in these effects over time, responding to significant market events. These results contribute to the theoretical understanding of financial market behavior by integrating social influence and career concern perspectives, offering insights for both scholars and practitioners in an increasingly complex market landscape.

Twitter Economic Uncertainty and Herding Behavior in ESG Markets

Twitter Economic Uncertainty and Herding Behavior in ESG Markets

Empowering Investors: Reducing Herd Bias through Financial Literacy and Self-reflective Thinking

Herd behavior, where investors mimic the trades of others rather than relying on their own information or analysis, is a widespread phenomenon that can lead to suboptimal investment decisions and market inefficiencies. Hence, understanding how to reduce this behavior is crucial for improving individual investment outcomes and sustainable market performance. Though the literature suggests that self-reflection and financial literacy have potential to mitigate herd bias, it is unclear as to how these two perspectives interact to minimize this irrational behavior. By drawing on insights from the adaptive market hypothesis, transformative learning theory, concept of bounded rationality and dual process theory, this study attempts to enhance the understanding of this phenomenon by introducing a conditional mediation model that promotes self-directed learning. It predicts that investors can reduce their herd bias through self-reflection on their past stock trading experiences, which they can practice by engaging intuitive logical thinking and strengthen further through their financial literacy. Since herding is generally predicted to be more prevalent in frontier stock markets, the study was conducted in a frontier market - the Colombo Stock Exchange. The data was obtained through a self-administered questionnaire from 253 active individual investors, and analyzed by applying the PROCESS procedure. The findings reveal the significance of self-reflection as a mediating variable across its antecedents, which provides strong evidence for its central role in reducing herd bias. Notably, the findings indicate that self-reflection has a stronger effect on reducing herd bias of investors with lower level of financial literacy. It implies that investors with low financial literacy are more susceptible to herd bias, and self-reflection facilitates them to recognize and minimize their herd bias. Accordingly, the study concludes that promoting self-reflection can empower individual investors to become more financially literate and thereby mitigate their herd bias.

Is the Taiwan Stock Market (Swarm) Intelligent?

It is well-believed that most trading activities tend to herd. Herding is an important topic in finance. It implies a violation of efficient markets and hence, suggests possibly predictable trading profits. However, it is hard to test such a hypothesis using aggregated data (as in the literature). In this paper, we obtain a proprietary data set that contains detailed trading information, and as a result, for the first time it allows us to validate this hypothesis. The data set contains all trades transacted in 2019 by all the brokers/dealers across all locations in Taiwan of all the equities (stocks, warrants, and ETFs). Given such data, in this paper, we use swarm intelligence to identify such herding behavior. In particular, we use two versions of swarm intelligence—Boids and PSO (particle swarm optimization)—to study the herding behavior. Our results indicate weak swarm among brokers/dealers.

Did the Covid-19 Pandemic Trigger Herding Behavior?

This study aims to examine the influence of the COVID-19 pandemic on mutual fund herding in Indonesia. The research population comprises open-end mutual funds in Indonesia. By adopting the purposive sampling method, we selected the stock mutual funds registered from 2017 to 2022 as our research sample. We define the 2017-2019 period as before COVID-19 and 2020-2022 as during COVID-19. This study employs CSAD and CSSD as proxies for return dispersion by considering two types of indices as benchmarks, namely LQ45 and IDX Composite. Our study found that COVID-19 did trigger mutual fund herding. However, we failed to find herding behavior when there is a large market movement. Instead, we found reverse herding.

Impact of behavioral finance on financial decision making

This paper highlights the disproportionate effect of behavioral finance on investor’s investing decisions. While making any financial decisions, one easily gets influenced by psychological and emotional factors. Past individual experiences, tendency or opportunity for herd behavior, personal judgment, overconfidence in one's abilities, aversion to feelings of regret, reliance on advice from experts, and last but not least, something known as the disposition effect—by which investors tend to hold on to losing investments and professionally sell profitable ones too early. The impact of these factors on the investment decision-making process varies; on the one hand, they may enhance the quality of the decision-making process by aligning investments with risk tolerance and financial goals. However, on the other hand, behavioral factors can be a cause of inefficiency if investment decisions are based more on emotions than objective analysis. In our recent research, we questioned 187 investors, using a questionnaire from whom we acquired crucial information regarding the impact of behavioral finance on financial decisions. The primary objective of the questioning was to determine the effect of behavioral finance on financial decision-making. The secondary objective was to suggest some methods for making one aware of the repercussions of impulsive or emotional decision-making and making prudent investments.

The Effects of FOMO on Investment Behavior in the Stock Market

This study explores the impact of Fear of Missing Out (FOMO) on stock market investment behavior, focusing on how psychological and emotional factors influence investors' decision-making processes. The primary objective of the research is to investigate the relationship between FOMO and key behavioral trends, such as overtrading, speculative investing, and the formation of asset bubbles. A qualitative research approach was employed, utilizing a literature review of existing studies on behavioral finance, FOMO, and stock market dynamics. The findings indicate that FOMO significantly affects investors by amplifying emotional reactions to market trends, leading to irrational decisions that prioritize short-term gains over long-term financial stability. Social media and technology play a critical role in amplifying FOMO, creating herd behavior that contributes to market volatility and speculative bubbles, as seen in phenomena like "meme stocks." The study also reveals that younger investors are more susceptible to FOMO, largely due to their reliance on social media for investment advice. The results suggest that enhancing financial literacy and promoting disciplined, long-term investment strategies are essential for mitigating the negative effects of FOMO. Regulatory interventions targeting misinformation on digital platforms may also help reduce the prevalence of FOMO-driven investment behavior. Future research should further investigate the psychological mechanisms behind FOMO and explore the long-term sustainability of FOMO-driven market practices.

Herd behavior influence on decision-making during evacuation process: an empirical analysis from building evacuation experiments

Herd behavior influence on decision-making during evacuation process: an empirical analysis from building evacuation experiments

Exploring market-wide herding behavior in the major stock markets of Latin America

PurposeThis paper investigates market-wide herding behavior among investors in the stock markets of Brazil, Chile, Colombia and Mexico from January 2013 to December 2022.Design/methodology/approachWe analyze a survivor-bias-free dataset of daily stock returns, employing a measure reflecting the cross-sectional deviation of stock returns relative to market consensus.FindingsSignificant anti-herding is observed in Brazil and Mexico, while Chile and Colombia show results consistent with rational asset pricing models. The COVID-19 pandemic generally intensifies anti-herding trends. Additionally, significant asymmetries in herding/anti-herding effects are noted during different market trends and volatility levels. Furthermore, we identify the drivers of this phenomenon, revealing that extreme crude oil price movements are associated with more pronounced anti-herding, and herding/anti-herding effects appear synchronized across all four markets.Practical implicationsOur findings regarding synchronization in herding dynamics suggest challenges in realizing the desired benefits of international diversification in the region.Social implicationsThe significant cross-country effects indicate that herding dynamics may play a crucial role in precipitating regional financial crises.Originality/valueFor the first time, we examine various features of herding behavior in the sample markets, including the impact of the COVID-19 pandemic, psychological and economic drivers of the phenomenon and synchronization in herding dynamics among the four markets.

Worldwide Recessions and Herding Behaviour: A Comparative Analysis of Three Countries

The general suggestion that behavioral science plays a part in creating abnormalities within the financial sector has been studied and proposed many times in the past. This study aims to prove the existence of behavioral sciences, specifically herding behavior, in three countries with different market conditions: Indonesia (Emerging), Vietnam (Frontier), and the United States (Developed). We developed our methodology using quantile regression to study the existence of herding behavior, and our findings were as follows: (1) As expected, the US didn’t have any indication of a statistically significant herding presence; they do, however, indicate an insignificant presence of herding behavior in the post-covid period under bearish conditions (2) Vietnam does not indicate significant herding tendencies, (3) Surprisingly, Indonesia did not exhibit statistically significant herding presence, but both Indonesia and Vietnam exhibited the slight presence of herding behavior but still relatively insignificant.

The effects of extreme market conditions on investors’ herding behavior in the Malaysian stock market

The presence of herding behaviour could cause abnormality and extremely volatile markets, especially in emerging markets. This behaviour has been studied extensively but with inconclusive results. This paper investigates the effects of extreme market conditions on investors’ herding behaviour in the Malaysian stock market. Two common measures for herding behaviour were employed: cross-sectional standard deviation (CSSD) and cross-sectional absolute deviation (CSAD). Data were extracted from the daily closing prices of 346 companies listed on Bursa Malaysia. The study spans from year 2000 to 2019, consisting of pre-crisis, during-crisis and post-crisis, during up- and down-market conditions. The results from CSSD revealed the presence of herding behaviour during the pre-crisis in both extreme up and down-market conditions. In the post-crisis, herding behaviour was observed in extreme up-market conditions. Using CSAD, herding behaviour was prevalent in extreme up-market conditions and post-crisis in extreme down-market conditions. These findings offer additional evidence supporting the existence of herding behaviour during extreme market conditions. Mitigating herding behaviour through enhanced information disclosure and increased investor awareness can improve market quality and reduce volatility.

Investigating the Determinants of Herd Behavior: an Application of the Hwang–Salmon Method to the Turkish Banking Sector

Efficient financial markets are important for pricing assets at fair value. In an efficient market, investors are rational in the face of fast and accurate information flow, evaluate the information correctly, and reflect it in their pricing decisions. However, particularly in times of crisis and uncertainty, it is observed that some market participants hesitate in their decision-making processes, imitate the behavior of other individuals whom they consider reputable because they cannot rely on their own knowledge and experience, and try to follow the trend. This tendency, which is called herd behavior, destroys market efficiency and prevents correct price formation. Therefore, it is important to identify its determinants. The purpose of the study is analyzing the precense and determinants of herding behavior in the Turkish banking sector during the period 17.10.2017–10.11.2023. Herd behavior is identified using the Hwang–Salmon method, and logistic regression analysis and the Kruskal–Wallis test are applied to identify its determinants. The findings reveal that herding behavior is associated with the rise in risks and returns as well as the fall in interest rates and exchange rates.

Keputusan Investasi Keuangan dan Fear of Missing Out Sebagai Variabel Mediasi pada Mahasiswa UPN Veteran Jawa Timur

Over the past five years, the percentage growth of investors in Surabaya has experienced extreme fluctuations due to rapid advancements in information development. Easy access to information through social media and the surrounding environment has a significant potential to influence an individual's investment decisions. According to behavioral finance theory, psychological factors influence investment decisions, where information from the environment can lead to herding behavior, while information from social media can drive impulsive investment decisions. This research was conducted on students of UPN Veteran Jawa Timur with a total of 100 respondents. Data analysis used the SEM PLS method. The analysis results show that herding factors and social media contribute to impact on investment decisions. Additionally, the fear of missing out (FoMO) proves to be an influential mediator between social media and investment decisions. These findings underscore the importance of understanding psychological factors in investment decision-making in the digital era.

The effects of herding and dispersal behaviour on the evolution of cooperation on complete networks

Evolutionary graph theory has considerably advanced the process of modelling the evolution of structured populations, which models the interactions between individuals as pairwise contests. In recent years, these classical evolution models have been extended to incorporate more realistic features, e.g. multiplayer games. A recent series of papers have developed a new evolutionary framework including structure, multiplayer interactions, evolutionary dynamics, and movement. However, so far, the developed models have mainly considered independent movement without coordinated behaviour. Although the theory underlying the framework has been developed and explored in various directions, several movement mechanisms have been produced which characterise coordinated movement, for example, herding. By embedding these newly constructed movement distributions, within the evolutionary setting of the framework, we demonstrate that certain levels of aggregation and dispersal benefit specific types of individuals. Moreover, by extending existing parameters within the framework, we are not only able to develop a general process of embedding any of the considered movement distributions into the evolutionary setting on complete graphs but also analytically produce the probability of fixation of a mutant on a complete N-sized network, for the multiplayer Public Goods and Hawk–Dove games. Also, by applying weak selection methods, we extended existing previous analyses on the pairwise Hawk–Dove Game to encompass the multiplayer version considered in this paper. By producing neutrality and equilibrium conditions, we show that hawks generally do worse in our models due to the multiplayer nature of the interactions.

Herd behavior in public goods games

Herd behavior in public goods games

Impact of Behavioural Finance on Investors’ Attitudes Towards Investment in Secondary Market

This research explores some of the unanswered important questions about stock markets that can be examined and investigated by an emerging field, behavioural finance. It also explains the factors responsible for the unusual movements in the stock markets, which could not be fully explained by the theories of traditional finance. This study shall examine three important attitudes displayed by the investors. They are: ‘Expectations’ those investors have about the future performance of the stock market in India; ‘Confidence’ that investors have regarding their investments; and ‘Herd Instincts’ so investors tend to herd together. Present study shall also analyze the Investors’ preference towards traditional trading and online trading.

Herd behavior identification based on coevolution in human–machine collaborative multi-stage large group decision-making

As the scale of multi-stage large group decision-making (LGDM) continues to expand, the possibility of low-contribution individuals exhibiting herd behavior also increases, potentially leading to the phenomenon of “fishing in troubled waters.” This may obstruct the speed of consensus reaching while generating no valuable opinions, which is a topic worthy of exploration. Considering that humans are easily influenced by interests, the employment of machine intelligence to objectively identify herd behavior is more appropriate. In this context, a herd behavior identification method based on behavioral characteristics clustering from the perspective of human–machine collaboration is herein proposed. First, from the human side, an opinion–social network coevolution model is constructed to simulate the consensus reaching process (CRP) of the expert group. Then, the group is clustered into three subgroups in consideration of behavior that encompasses both opinion changes and trust relationship changes. Based on this, the low-contribution cluster with a herd behavior pattern can be optimized from the machine side. Through simulation experiments, it is verified that herd behavior management significantly accelerates the consensus-reaching speed under the premise of having minimal impact on the decision-making results. In general terms, this study is the first to propose the concept of herd behavior and provides a solution to manage it from a new perspective, which is suitable for application in multi-stage LGDM scenarios.

Navigating Market Movements: The Role of Herd Behaviour in Indian Stocks

When an individual elects to allocate their financial resources towards the stock market for the initial occasion or on a consistent basis, yet possesses insufficient knowledge pertaining to market analysis and investment strategies, the primary issue or inquiry that emerges is the appropriate allocation of capital. In more straightforward terms, this involves determining whether to invest in equity shares, preference shares, debentures, or to allocate resources to mutual funds, and if so, in which specific equity/preference shares, debentures, or mutual funds the investment should be made. Individuals may either engage the services of a stock broker to manage their investments on their behalf or choose to undertake the investment process independently. In both scenarios, their decision-making processes are likely to be influenced, either wholly or partially, by herd behaviour, commonly referred to as the bandwagon effect. Individuals tend to adhere to prevailing trends. When a substantial cohort of individuals engages in investment in a particular stock, there exists a propensity among others to similarly invest in that stock, often without conducting thorough independent analysis. They possess a belief that a significant collective cannot err. The bandwagon effect is an inherent phenomenon that is relatively innocuous to a certain degree; however, it can occasionally be strategically manipulated to influence market movements in a preferred direction, an action that may constitute unfair trade practices and is frequently observed within the stock market. While herd behaviour in everyday situations may be benign, it can prove detrimental when related to investment decisions.

Exploring Herding Instincts Through the Lens of Adaptive Market Hypothesis: Insights from a Frontier Market

Exploring Herding Instincts Through the Lens of Adaptive Market Hypothesis: Insights from a Frontier Market