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In the stock market, herding behavior occurs when investors mimic the actions of others in their investment decisions. As a result, the market becomes inefficient and speculative bubbles form. This study aims to investigate the relationship between information, overconfidence, market sentiment, experience and national culture, and herding behavior among Malaysian investors. A total of 400 questionnaires are distributed to bank institutions' investors. The survey design based on cross-sectional data is analyzed using the Partial Least Squares Structural Equation Model. The results indicate that information, market sentiment, experience, and national culture are positively related to herding behavior, while overconfidence has no effect. With this, the government should strengthen regulations to prevent the dissemination of misleading information. Moreover, investors are encouraged to overcome narrow thinking by expanding their understanding of different cultures when making investment decisions.

This article aims to clarify the mechanism by which herding behavior influences perceived market efficiency, investment decisions and the performance of individual investors actively trading on the Pakistan Stock Exchange (PSX).

The deductive approach was used in this study, as the research is based on the theoretical framework of behavioral finance. A questionnaire and cross-sectional design were employed to collect data from the sample of 309 investors trading on the PSX. The collected data were analyzed using SPSS and AMOS graphics software. Hypotheses were tested using structural equation modeling (SEM).

The article provides further empirical insights into the relationship between herding behavior and investment management and perceived market efficiency. The results suggest that herding behavior has a markedly negative influence on perceived market efficiency and investment performance, while positively influencing the decision-making of individual investors.

The current study is the first to focus on links between herding behavior and investment management activities and perceived market efficiency. This article enhances the understanding of the role that herding behavior plays in investment management and, more importantly, it improves understanding of behavioral aspects and their influence on investment decision-making in an emerging market. It also adds to the literature in the area of behavioral finance, specifically the role of herding behavior in investment management; this field is in its initial stage, even in developed countries, while little work has been done in developing countries.

The purpose of this paper is to analyze the interaction between the availability of financial information and individuals' cognitive profiles to explain investors' herding behavior.

The authors designed and conducted an experiment to observe the behavior of subjects in three settings, each with a different level of information.

Results confirm that a dependence relation exists between information, investors' behavioral biases and the herding phenomenon. Moreover, the experiment shows that information concerning the number of previous transactions in the market is particularly relevant to explain herding propensity among investors. The findings indicate that the cognitive profile of investors is more relevant as the availability of information increases and the number of previous transactions in the market is low.

Future research should examine further the best way to measure the individual's cognitive profile and its interaction with information limitation in financial markets. The presence of high levels of uncertainty favors herding behavior regardless of inter‐individual differences, and only when the availability of information is high and the number of transactions is low does the subjects' cognitive profile explain the investors' herding behavior. Finally, it is observed that not all public information receives the same attention by investors. The attractiveness of public information requires further attention.

The herding phenomenon is difficult to anticipate because there are factors of a very diverse nature that intervene.

The research described in this paper measures investors' cognitive profile to identify the interaction between availability of information, cognitive profile and herding.

This study explores whether herd behavior exists for equity crowdfunding investors in China and whether this herding is rational.

Based on signaling theory and social learning theory, two hypotheses were proposed. This study employed two approaches to collect data. First, this paper analyzed 3,041 investments on an equity crowdfunding platform in China using Python programming and built a panel data model. Second, based on a unique experiment design, this study conducted several relevant herd behavior simulation experiments.

We found that investors in the Chinese equity crowdfunding market exhibit herd behavior and that this herding is rational. Project attributes play a negative role in moderating the relationship between the current investment amount and cumulative investments. Experimental results further support our findings.

This study contributes to the emerging literature on herding in crowdfunding by focusing on equity crowdfunding in China. We are the first to explore whether Chinese equity crowdfunding investors exhibit rational herding behavior. The study is also original in applying social learning theory to equity crowdfunding and in using both actual crowdfunding campaigns and experimental approaches to collect data. This study has valuable implications to practice.

Based on the theoretical framework, this paper analyzes the sentiment-herding relationship in emerging stock markets (ESMs). First, it aims to examine the effect of investor sentiment on herding. Second, it seeks the direction of causality between sentiment and herding time series.

The present study applies the Exponential Generalized Auto_Regressive Conditional Heteroskedasticity (EGARCH) model to capture the volatility clustering of herding on the financial market and to investigate the role of the investor sentiment on herding behaviour. Then the vector autoregression (VAR) estimation uses the Granger causality test to determine the direction of causality between the investor sentiment and herding. This study uses a sample consisting of stocks listed on the Shanghai Composite index (SSE) (348 stocks), the Jakarta composite index (JKSE) (118 stocks), the Mexico IPC index (14 stocks), the Russian Trading System index (RTS) (12 stocks), the Warsaw stock exchange General index (WGI) (106 stocks) and the FTSE/JSE Africa all-share index (76 stocks). The sample includes 5,020 daily observations from February 1, 2002, to March 31, 2021.

The research findings show that the sentiment has a significant negative impact on the herding behaviour pointing out that the higher the investor sentiment, the lower the herding. However, the results of the present study indicate that a higher investor sentiment conducts a higher herding behaviour during market downturns. Then the outcomes suggest that during the crisis period, the direction is one-way, from the investor sentiment to the herding behaviour.

The findings may have implications for universal policies of financial regulators in EMs. We have found evidence that the Emerging investor sentiment contributes to the investor herding behaviour. Therefore, the irrational investor herding behaviour can increase the stock market volatility, and in extreme cases, it may lead to bubbles and crashes. Market regulators could implement mechanisms that can supervise the investor sentiment and predict the investor herding behaviour, so they make policies helping stabilise stock markets.

The originality of this paper lies in investigate the sentiment-herding relationship during the Surprime crisis and the Covid-19 epidemic in the EMs.

Starting in the 1980s, financial liberalization and technological developments have enabled individual investors to participate in financial markets and carry out easy transactions. With these developments, academics began to wonder how the individual investors decide to invest and what factors affect these decisions.

According to traditional finance theory, it is suggested that markets are efficient and investors show rational behaviors in their financial purchasing decisions. However, in many studies conducted in recent years, it was determined that investors included emotional elements as well as rational elements in their decision-making process and therefore exhibited irrational behaviors by believing rumors instead of real information. It is thought that many factors such as personal characteristics, psychological factors, demographic and socio-economic factors play a role in the behavior of investors in purchasing a financial product.

In this study, the importance of herd behavior, which is one of the psychological factors that play a very important role in financial markets, on financial product purchasing process is examined in the light of the behavioral finance theory. It is thought that information included in the study will be useful for researchers who want to study herd behavior and for those who are interested in the subject.

Investor sentiment (optimism or pessimism) may influence investors to follow others (herding) while taking their investment decisions. Herding may result in bubbles and crashes in the financial markets. The purpose of the study is to examine the presence of herding and the effects of investor sentiment on herding in China and Pakistan.

The investor sentiment is captured by five variables (trading volume, advance/decline ratio, weighted price-to-earnings ratio, relative strength index and interest rates) and a sentiment index developed through principal component analysis (PCA). The study uses daily prices of 2,184 firms from China and 568 firms from Pakistan for the period 2005 to 2018.

The study finds that herding prevails in China while reverse herding prevails in Pakistan. Interestingly, as investors become optimistic, herding in China and reverse herding in Pakistan decrease. This indicates that herding and reverse herding are greater during pessimistic periods. Further, the increase in herding in one market reduces herding in the other market. Moreover, optimistic sentiment in the Chinese market increases herding in the Pakistani market but the reverse is not true.

Considering the greater global financial liberalization, and better opportunities for emotion sharing, this study has important implications for regulators and investors. Market participants need to understand the prevalent irrational behavior before trading in the markets.

Since individual proxies may depict different picture of the relationship between sentiment and herding therefore the study also develops a sentiment index through PCA and incorporates this index in the analysis. Further, this study examines cross-country effects of herding and investor sentiment.

The purpose of this paper is to investigate investor herding behaviour and the effect of presidential elections on investor herding behaviour in African stock markets at the sector level.

The study segregates listed firms into financial, consumer goods, consumer services and basic materials sectors and uses the cross-sectional absolute deviation approach as a metric of detecting herding in each of the sectors. The authors extend the model to tease out the effect of presidential elections on investor herding behaviour.

The study reveals that sectoral differences are fundamental to the evolution of herding. Herding is prominent in a financial services sector dominated by banks. The phenomenon also prevails in markets with smaller consumer goods and services sectors. A post-presidential election effect on investor herding is found for the consumer goods and services sectors of Ghana and a pre-presidential election effect is documented in Nigeria's consumer services sector. The authors conclude that post-presidential election effect is as a result of political connections whilst a pre-presidential election effect is attributable to political business cycles.

The study is based on four African countries due to data constraints. Nonetheless, the study is the first in Africa to the best of the authors' knowledge, and the results are very solid and have a lot of practical and policy implications.

The study has implications for investors as it guides investment behaviour in pre- and post-presidential election periods.

Past studies on investor herding behaviour in African stock markets have largely concentrated on the aggregate market. Knowledge on sectoral differences in investor herding is almost non-existent for African stock markets. Furthermore, premised on the fact that stock markets react to presidential elections, there is no known study that have attempted to examine the effect of presidential elections on investor herding behaviour. This paper contributes to the literature by providing evidence on sectoral differences in investor herding behaviour and the effect of presidential elections on sectoral herding behaviour.

The purpose of this paper is to provide a review of theory and empirical evidence on herding behavior in financial markets.

Review and discussion of the literature.

More than two decades of empirical and theoretical research have provided a significant insight on investor herding behavior.

The discussion indicates that there are still open issues and areas with inconclusive evidence, e.g. the author knows relatively little for markets other than equity markets.

The paper may need empirical methodologies to evaluate herding that address current limitations.

The paper reviews recent empirical evidence and identifies open issues for future research.

In recent years, significant research has focused on the question of whether severe market periods are accompanied by herding behavior. As herding behavior is a considerable cause of the speculative bubble and leads to stock market deviations from their basic values it is necessary to examine the motivators which led to herding behavior among investors. The paper aims to discuss this issue.

In this study, the authors performed a two-phase analysis to address the research questions of the study. In the first phase, for text analysis NVivo software was used to identify the factors driving herding behavior among Indian stock investors. The analysis of a text was performed using word frequency analysis. While in the second phase, the Fuzzy-AHP analysis techniques were employed to examine the relative importance of all the factors determined and assign priorities to the factors extracted.

Results of the study depicted Investor Cognitive Psychology (ICP), Market Information (MI), Stock Characteristics (SC) as the top-ranked factors driving herding behavior, while Socio-Economic Factors (SEF) emerged as the least important factor driving herding behavior.

The current study was undertaken among stock investors from North India only. Moreover, numerous factors are not part of the study but might significantly influence the investors' herding behaviors.

Comprehending the influences of the different factors discussed in the study would enable stock investors to be more aware of their investment choices and not resort to herd behavior. This research enables decision-makers to understand the reasons for herd activity and helps them act accordingly to improve the stock market's performance.

The current study will provide an inclusive overview of herding behavior motivators among Indian stock investors. This study's results can be extremely useful for both academics and policymakers to gain some insight into the functioning of the Indian stock market.