Understanding herding behavior in hospitality stocks

Herding investment behavior on stock markets has consequences for practitioners, theorists, and policy makers. Thus, empirical research on this topic in the last couple of years has grown exponentially. However, there exist only a few papers dealing with herding behavior that consider the Croatian stock market. This study employs the quantile regression approach of estimating several herding investor behavior models of this market for the first time in the literature. Based upon daily data for the 37 most liquid stocks in the Zagreb Stock Exchange (ZSE) for the period September 22, 2014 to May 8, 2018, several model specifications are determined using quantile regression. Because the quantile regression approach deals with specific characteristics of financial data (stylized facts) better than the OLS method, more robust results can be achieved for evaluating if herding behavior is present in the Croatian market. The results indicate very weak to almost nonexistent evidence of herding behavior in the ZSE. Moreover, market volatility does not have any effect on herding behavior. Finally, the economic and political crisis (regarding concern Agrokor) in 2017 was controlled for in the model and the crisis was found insignificant. It seems that herding behavior does not need to be taken into account when tailoring investment strategies on the ZSE.

In this study, we employ an innovative new methodology suggested by Bernhardt et al. (2006) to examine the herding (or anti-herding) behavior of German analysts in case of earnings forecasts. Our methodology avoids well-known shortcomings often encountered in related studies, such as, e.g., correlated information signals, unexpected common shocks to earnings, systematic optimism or pessimism or forecast target mismeasurement. Our findings suggest that German analysts anti-herd, i.e., they systematically issue earnings forecasts which are further away from the consensus forecast than their private information indicates. Furthermore, we analyze the association between herding behavior and different characteristics which might influence analysts' herding behavior, like the size of the brokerage, the experience of the analyst and the coverage of firms of the Neuer Markt. We mainly confirm findings for the U.S., e.g., that the anti-herding phenomenon is more severe in cases of higher competition among analysts. Contrary to anecdotal evidence, we also find anti-herding behavior when analysts issue forecasts for Neuer Markt firms during the 'new economy' bubble.

We examine the existence of herding and anti-herding (positive herding) behavior in major European benchmarking stock market indices. Following the recent events that unfolded in the Eurozone sovereign debt crisis our analysis is further expanded on two subsamples namely north and south European countries. In order to identify any time-dependent properties reflected in time-varying parameters, we employ an overlapping rolling window regression of varying window sizes. The empirical evidence confirms a herding behavior during the global financial crisis for the South countries, and anti-herding behavior for both North and South subsets before and after the shock, independent of the window size. The herding and anti-herding behavior, are explained with the use of dynamic conditional correlation via DCC-GARCH family multivariate modeling. The results indicate that the correlations have recorded a significant decrease before and after the crisis for both North and South subsamples, accounting for the anti-herding behavior, whereas correlations for the South countries during the crisis have increased, thus justifying the herding behavior. Our results entail significant implications for international portfolio diversification strategies.

The current measure method of LSV herd behavior is inadequate, which makes the coefficient of herd behavior smaller, the paper makes the improvement based on this problem. By using the sample data of fund companies' weightiness stock of WIND database from 2003 Q1 to 2009 Q2, the paper carries out the research on general, buyer and seller herd behavior of fund companies and their funds. The results show that: (1) The traditional LSV methods underestimate the funds' herd behavior, the coefficient of the general, seller and buyer herd behavior is underestimated by 5.61%, 7.55% and 4.10% respectively; (2) The coefficient of seller herd behavior is higher than the one of buyer herd behavior, that means the fund companies and their funds show a stronger herd behavior when selling stocks than buying stocks; (3) The general and seller herd behavior of funds is higher than the one of fund companies, while the buyer herd behavior of funds is lower than the one of fund companies; (4) The general, buyer and seller herd behavior of fund companies show a positive correlation with Shanghai Composite Stock Index, but this correlation is not significant; (5) The coefficient of general and buyer herd behavior of fund companies is minimum when the stock market drops by large amounts; the coefficient of general and buyer herd behavior of fund companies increases, and the coefficient of seller herd behavior decreases when the stock market drops by smaller amounts; the coefficient of the general, buyer and seller herd behavior is maximum when the stock market goes up by smaller amounts; the coefficient of the general, buyer and seller herd behavior decreases when the stock market goes up by large amounts.

Purpose This paper aims to examine not only the herding behavior in developed stock markets but also the role of the foreign market returns in explaining national herding behavior during normal and extreme market movements by extending the cross-sectional absolute deviations (CSADs) model for the period that spans from January 5, 2000, to April 22, 2022. Design/methodology/approach Extending the CSADs model. Findings The authors found that herd behavior in the Canadian market is more pronounced than in the US and French markets, but it is absent in the UK market. Moreover, simultaneity and continuity of herding behavior are detected in these markets. In normal periods, the French market is a UK herding trigger, but the US, UK and Canadian markets are anti-herding. Mainly, downturns in the US market lead Canadian investors to be more pessimistic about their future cash flows, creating a feeling of fear and uncertainty among investors and leading them to flock into herding behavior. Conversely, extreme upturn movements of the UK market explain Canadian herding behavior. These results represent a guide for investors to construct optimal portfolios, an alert for global risk managers and a way for national policymakers to improve regulations to challenge herding risk. Research limitations/implications Investors in global financial markets, global risk managers and local policymakers should put too much emphasis on herding risk in developed-like emerging markets in the era of digitalization and global interconnectedness. This study represents an addition to herding behavior literature. It offers a field for discussion of different explanations suggested by previous studies at the same time. This study also shows that the US market has varying degrees of influence on others. Investors in all markets must pay more attention to US information. Practical implications This helps investors construct optimal portfolios and diversify risk by investing in the UK market. For global risk managers, this clarifies the source of risk and hence helps them to minimize global risk. For Canadian policymakers, this study helps them to improve regulations to challenge herding behavior. This leads UK investors to pay more attention to French market information. Policymakers of the world must take into account US returns in the formulation of new national regulations. The results represent an alert for the Canadian market. Originality/value First, compared to the above-mentioned studies, this work is the first attempt to explain herding behavior across national borders. Second, examining the impact of the foreign market on the national herding behavior for major developed markets takes us away from the usual assumption that herd behavior is particularly significant in emerging markets. Hence, this can offer theoretical and practical implications. Third, this study distinguishes between the trigger and anti-herding markets. This can be a response to several questions. Hence, this offers several practical implications for investors, policymakers, risk managers and future researchers. Fourth, this issue is of great interest to global investors who allocate their assets across developed financial markets because increasing market linkages may reduce the benefits of investment diversification. Fifth, analyzing herding behavior across national borders is important for understanding the mechanisms of financial market operations and developing appropriate policies. Finally, examining whether investors herd around other markets’ consensus can answer questions about the sources of herding behavior and explain its spread to different markets and systemic risk transmission across markets.

This paper examined the factors that affect investor herd behavior. Herd behavior bias is a well- known phenomenon in financial markets in which individuals blindly follow the investing decisions of others without understanding the fundamental principles of investment. While extensive research has explored herd behavior in financial markets, there remains a significant research gap in understanding herding behavior at the level of individual investors. Previous studies have primarily focused on herding behavior within market contexts, neglecting the examination of specific factors that influence herding behavior among individual investors. Using a sample of 217 Indonesian investors this study investigates the factors that influence herding behavior. The findings showed that stock influencer credibility had a significant positive impact on herd behavior bias, suggesting that investors with high trust in stock influencers were likely to follow the herd. Financial literacy also had a significant negative impact on herd behavior bias, indicating that investors with higher financial knowledge are less likely to herd. However, financial literacy was found to have a significance towards herding behavior when mediated through risk perception. Lastly, risk perception had a significant positive impact on herd behavior bias, indicating that investors with higher risk perception are more likely to follow the herd. This study contributes to the existing literature by enhancing our understanding of herd behavior dynamics among investors, specifically at the individual level. By exploring the factors that influence herding behavior, it provides valuable insights into the mechanisms that drive this bias. The findings highlight the importance of targeted financial education programs and regulatory measures to address herding behavior bias among Indonesian investors, focusing on enhancing financial literacy and reducing risk perception.

This paper investigates the dynamic interplay between monetary and fiscal policies and their influence on herding behavior among manufacturing companies in China. Herding behavior, characterized by the tendency of firms to mimic the actions of others rather than making independent decisions, can significantly affect market stability and efficiency. The study employs a comprehensive dataset spanning a period that encompasses various monetary and fiscal policy interventions, alongside fluctuations in market conditions. Using advanced econometric techniques, including Vector Autoregression (VAR) models and Granger causality tests, we analyze the short-term and long-term effects of monetary and fiscal policies on herding behavior within the manufacturing sector. The study also examines the moderating role of firm-specific characteristics such as size, industry, and financial health on the relationship between policies and herding behavior. Preliminary findings suggest a complex and dynamic relationship between policy interventions and herding behavior. Monetary policy tools, such as interest rate adjustments and open market operations, exhibit significant short-term effects on herding behavior, influencing firms' decisions to follow prevailing market trends. Similarly, fiscal policy measures, including tax incentives and government spending, demonstrate varying degrees of impact on herding behavior, contingent upon the economic context and firms' financial positions. Furthermore, the study explores the transmission channels through which monetary and fiscal policies influence herding behavior, including their effects on market liquidity, risk perceptions, and investor sentiment. Understanding these mechanisms is crucial for policymakers and market participants to anticipate and mitigate the adverse effects of herd behavior on market stability and efficiency. In conclusion, this empirical study contributes to the existing literature by providing insights into the dynamic relationship between monetary and fiscal policies and herding behavior among manufacturing companies in China. The findings have important implications for policymakers aiming to design effective policy interventions to foster a more resilient and stable market environment, ultimately promoting sustainable economic growth and development.

Predation is a powerful selective pressure and probably a driver of why many animal species live in groups. One key explanation for the evolution of sociality is the 'selfish herd' model, which describes how individuals who stay close to others effectively put neighbours between themselves and a predator to survive incoming attacks. This model is often illustrated with reference to herds of ungulates, schools of fish or flocks of birds. Yet in nature, when a predator strikes, herds are often found fleeing cohesively in the same direction, not jostling for position in the centre of the group. This paper highlights a critical assumption of the original model, namely that prey do not move in response to position of their predator. In this model, I relax this assumption and find that individuals who adopt 'selfish herd' behaviour are often more likely to be captured, because they end up at the back of a fleeing herd. By contrast, individuals that adopt a rule of 'neighbour to neighbour alignment' are able to avoid rearmost positions in a moving herd. Alignment is more successful than selfish herding across much of the parameter space, which may explain why highly aligned fleeing behaviour is commonly observed in nature.

This paper is investigated herding and cross-herding behavior in the UAE equity markets during the period from January 1, 2008 to March 31, 2019. Herding behavior is tested in both static and regime-switching framework. The findings of the paper suggest a presence of significant herd behavior in the UAE markets. Herding asymmetries are detected with respect to market returns and volatility where herding appears more pronounced during market declines and high volatility regime. Additionally, the results suggest a significant herding effect during the global financial crisis. The findings also show strong cross-market herding during the period of market stress. Results from this study could be useful gaining an insight into the functioning of the UAE stock markets for academicians in behavioral finance also as for policymakers.

PurposeIt has been argued in the literature that structural changes in the financial markets, such as integration, have the potential to cause herding behavior or correlated behavioral patterns in traders. The purpose of this study is to investigate whether there is any financial herding behavior in the Latin American Integrated Market (MILA), a transnational stock market composed of Chile, Peru, Colombia and Mexico stock exchanges and whether there is any ARCH or GARCH effect in the herding behavior models.Design/methodology/approachThis study uses the modified return dispersion approach on daily index return data. The sample period is from January 03, 2002 to May 07, 2019. The data are obtained from the MILA database. To count time-varying volatilities in herding models, the authors run ARCH family regression with GARCH (1,1) settings. Hwang and Salmon (2004) model is used as a robustness test.FindingsThe authors found strong herding behavior under the general market conditions and moderate and partial herding behavior under some specified markets circumstances, such as bull and bear markets and high-low volatility states. Moreover, the pre-MILA period exhibits more herding behavior than the post-MILA period. The empirical results show that most of the ARCH and GARCH effects are statistically significant, implying that the past information of stock returns and market volatility significantly affect the volatility of following periods, which can also explain the formation of herding tendency among investors. Finally, the results of the robustness tests (Hwang and Salmon, 2004) confirm herding in all periods, except full sample period for Mexico and post-MILA period for Mexico and Colombia.Research limitations/implicationsThis study investigates the herding behavior in the MILA market in terms of market return, volatility and timing. A limitation of the paper is that the authors have not included other factors on the formation of herding behavior, such as macroeconomic factors, effects of regional or international markets and policy influences. The authors will explore the issue in the extension of the paper.Practical implicationsAs MILA is the first virtual integration of stock exchanges without merging, the study provides useful findings and draws good inferences of herding behavior in the MILA market in terms of market return, volatility and timing which are useful for academics, investors and policymakers in their investment and decision makings.Social implicationsThe paper provides useful findings and draws good inferences of herding behavior in the MILA market in terms of market return, volatility and timing which are not only useful in practical implications, but also in social implications.Originality/valueThis study contributes to the herding literature by examining four different hypotheses in respect of the unique case of transnational stock exchange without fusions or corporate mergers, where each market maintains its independence and regulatory autonomy. The authors also contribute to the literature by including both ARCH and GARCH effects in the herding behavioral models along the Hwang and Salmon (2004) approach.

Herding behaviour in the financial market has been popular as a theoretical concept since the 1990s. Many articles have studied and discussed herding behaviour in the capital market, but research examining the causes or factors that trigger herding behaviour is minimal. The research themes are relatively underdeveloped because the majority of empirical research still struggles to answer the question of whether herding behaviour is found in the capital market or not. It has impeded our understanding and the development of a comprehensive theoretical framework of herding behaviour. The purpose of this paper is to conduct a bibliometric analysis and systematic literature review to provide an overview of the research findings, analyse the research profile, and guide the researcher to the most influential works and results related to herding behaviour. Based on 279 articles taken from the Scopus database, we mapped the co-occurrence of research through keywords analysis. This paper's main contribution is to build a structure of knowledge for herding behaviour in the capital market, elaborate and classify empirical research into relevant dimensions that can be used as a reference for comprehensively developing herding behaviour research. Finally, this systematic literature review's results may provide insight into future research prospects about herding behaviour.

Objective—This study investigates the phenomenon of herding behavior among investors in Indonesia's Shariah banks. In this situation, market participants tend to follow prevailing market trends without engaging in comprehensive fundamental analysis. Methodology/Technique – Specifically, the research examines the influence of investors' religious understanding as a mediating variable on their decision-making processes within the Shariah financial sector. Notably, the study addresses whether investors are more inclined to mimic market movements or rely on independent analysis when investing in Sharia-compliant banks. It is commonly observed that rumors can precipitate rash trading decisions among investors, leading to the buying or selling of shares even in the absence of substantial changes in asset fundamentals (Bommel, 2003). Findings – Employing a quantitative approach, this study utilizes path analysis to explore the impact of religious understanding on herding behavior. Although prior research has extensively investigated herding behavior, the introduction of religious understanding as a mediating variable offers a new dimension to assess the correlation between religiosity and market behavior. This aspect has not been widely examined in previous segmentations. The sample comprises data from 15 Islamic Banks in Indonesia, analyzed using associative data analysis techniques with AMOS software. Findings indicate significant positive relationships between stock returns and herding behavior, trading volume and herding behavior, and the level of Islamic understanding and herding behavior in these banks. Novelty – However, these relationships do not hold when Islamic understanding is applied as a mediating variable. This suggests that the level of religious understanding acts as a direct influencer rather than a mediator in herding behavior among investors in Indonesian Islamic banks. Type of Paper: Empirical JEL Classification: G41, D81, C58. Keywords: Herding behavior, Stock returns, Trading volume, Level of Understanding of Islam Reference to this paper should be made as follows: Kamaludin; Usman, B; Susanti, W. (2024). Insights into Herding Behavior in Indonesian Islamic Banks, J. Fin. Bank. Review, 9(1), 27 – 37. https://doi.org/10.35609/jfbr.2024.9.1(1)

Predator-driven fragmentation of fiddler crab droves into selfish miniherds of biased composition

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.

(2006). An Economic Psychological Approach to Herd Behavior. Journal of Economic Issues: Vol. 40, No. 1, pp. 75-95.