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This study examines herd behavior in the cryptocurrency market at the aggregate level and the determinants of herd behavior, such as asymmetric market returns, the coronavirus disease 2019 (COVID-19) pandemic, 2021 cryptocurrency's bear market and the network effect.

The authors applied the Google Search Volume Index (GSVI) as a proxy for the network effect. Since investors who are interested in a particular issue have a common interest, they tend to perform searches using the same keywords in Google and are on the same network. The authors also investigated the daily returns of cryptocurrencies, which are in the top 100 market capitalizations from 2017 to 2022. The authors also examine the association between return dispersion and portfolio return based on aggregate market herding model and employ interactions between herding determinants such as, market direction, market trend, COVID-19 and network effect.

The empirical results indicate that herding behavior in the cryptocurrency market is significantly captured when the market returns of cryptocurrency tend to decline and when the network effect of investors tends to expand (e.g. such as during the COVID-19 pandemic or 2021 Bitcoin crash). However, the results confirm anti-herd behavior in cryptocurrency during the COVID-19 pandemic or 2021 Bitcoin crash, regardless of the network effect.

These findings help investors in the cryptocurrency market make more rational decisions based on their determinants since cryptocurrency is an alternative investment for investors' asset allocation. As imitating trades lead to return comovement, herd behavior in the cryptocurrency has a direct impact on the effectiveness of portfolio diversification. Hence, market participants or investors should consider herd behavior and its underlying factors to fully maximize the benefits of asset allocation, especially during the period of market uncertainty.

Most previous studies have focused on herd behavior in the stock market. Although some researchers have recently begun studying herd behavior in the cryptocurrency market, the empirical results are inconclusive due to an incorrectly specified model or unclear determinants.

It 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.

This 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.

The 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.

This 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.

As 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.

The 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.

This 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.

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.

This paper aims to investigate whether the COVID-19 pandemic leads to the formation of herding behaviour among investors in Shariah-compliant stocks.

This study uses a sample of the stocks that constitute the Dow Jones Islamic Market Malaysia Titans 25 Index, over the period from 6 December 2017 to 12 March 2021.

This paper provides robust evidence on the contribution of the COVID-19 pandemic to the formation of herding behaviour in Shariah-compliant stocks. The findings also reveal that herding behaviour occurs only during falling market.

The findings provide useful implications for policymakers and portfolio managers seeking to understand the behaviour of investors in Shariah-compliant stocks during turbulent periods. The presence of herding behaviour begs the question on the market efficiency and limits its potential to offer diversification benefits to investors. The findings suggest that policymakers and investors should mitigate misvaluations that occurred during the COVID-19 outbreak because the herding behaviour can drive stock prices away from their equilibrium values. Thus, regulators should adopt appropriate policies to enable the market to reach a more efficient level by monitoring and improving the quality of information and facilitate their transmission to the market. The misevaluation opportunity enables market timers to sell overpriced stocks and purchase underpriced stocks. The findings also imply that investors should implement effective hedging strategies to mitigate the downside risk. In addition, the results suggest that investors should devise their trading strategies in falling and rising markets during the COVID-19 pandemic.

There is meagre literature on the effect of the COVID-19 outbreak on the formation of herding behaviour among investors. Studies conducted on herd behaviour are widely focused on Shariah non-compliant stocks, only a few ones deal with Shariah-compliant stocks. The novelty of this paper consists in addressing this gap in the literature through examining the presence of herding behaviour on the part of investors in Shariah-compliant stocks in Malaysia before and after the COVID-19 outbreak.

The purpose of this paper is to examine herding in four frontier markets in the Balkan region, namely, Bulgaria, Croatia, Romania and Slovenia, from October 2000 to December 2016.

The author employs Chang et al.’s (2000) cross-sectional dispersion approach to capture herding, while also testing for the global financial crisis’ effects and the European Union (EU)/Euro zone accession effects over herding. Potential asymmetric herding effects conditional on market performance, domestic volatility, German and US investor sentiment are also examined. Finally, the cross-market herding dynamics of the region are also explored.

Overall, Romania exhibits the most extensive evidence of herding across various estimations. The empirical results indicate that cross-market herding dynamics within the region generate stronger herding (compared to the herding observed within each stock market individually), suggesting that Balkan stock exchanges’ growing financial integration leads their herding to be “imported”, rather than domestically motivated.

The findings provide useful insights for regulators in frontier markets, considering the destabilising potential of herding; they are also of particular interest to the investment community for reasons of international asset allocation, diversification and hedging strategies.

This study contributes to the limited herding literature regarding frontier markets and provides novel findings regarding the herding dynamics in the Balkan region, the EU/Euro zone accession’s effect and global factors’ impact on herding estimations.

This study explores the economic impact of the COVID-19 crisis on herding behaviour in the Australian equity market by considering liquidity, government interventions and sentiment contagion.

This study utilizes a daily dataset of the top 500 stocks in the Australian market from January 2009 to December 2021. Both predictive regression and portfolio approaches are employed to consider the impact of COVID-19 on herding intention.

This study confirms that herding propensity is more pronounced at the beginning of the crisis and becomes less significant towards later phases when reverse herding is more visible. Investors herd more toward sectors with less available information on financial support from the government during the financial meltdown. Conditioning the stock liquidity, herding is only detectable during highly liquid periods and high-liquid stocks, which is more observable during the initial phases of the crisis. Further, the mood contagion from the United States (US) market to Australian market and asymmetric herding intention are evident during the pandemic.

This is the first study to shed further light on the impact of a health crisis on the trading behaviour of Australian investors, which is driven by liquidity, public information and sentiment. Notwithstanding the theoretical contributions to the prior literature, several practical implications are proposed for businesses, policymakers and investors during uncertainty periods.

This chapter examines the existence of dynamic herding behavior by Tunisian investors in the Tunisia stock market during the revolution period of 2011–2013. The sample covers all Tunindex daily returns as a proxy for the Tunisia stock exchange index over the period 2007–2018. The author modifies the cross-sectional absolute deviation model to include all market conditions (bull and bear markets) and the geopolitical crisis effect corresponding to the Tunisian Jasmine revolution during 2011–2013, and show that herding is indeed not present in the Tunisia stock market including during its turmoil periods. These findings imply that the Tunisian emerging financial market became more vulnerable to adverse herding behavior after the revolution. There is also a clear implication for capitalist firms and angel investors in Tunisia that adverse herding behavior tends to exist on days of higher uncertainty and information asymmetry.

Motivated by the ongoing debate on the existence and magnitude of herding in financial markets, the purpose of this paper is to examine Eurozone stock markets for herding behavior. In the context of the present study, the authors seek for herding behavior of stock markets as a whole as opposed to previous studies that examine herding on stock level.

To this end, the authors employ data on benchmark stock market indices for a long sample starting from 2000 through 2016. The testing procedure entails the standard Capital Asset Pricing Model-based procedure along with an advanced econometric method allowing the coefficients of the model to vary over time.

Results provide evidence in favor of negative herding behavior (anti-herding) for the Eurozone as a whole with noteworthy transitions. Further analysis reveals that stock markets of the periphery exhibit scarce evidence of herding, whereas continental countries are mainly characterized by negative herding behavior.

The present study’s main contribution is twofold. First, herding is examined not in sector or stock level as previous studies but at market level. Second, the testing methodology entails a pure time-varying regression model with stochastic volatility proposed by Nakajima (2011) that has not been previously employed in stock market herding. The results entail significant implications for investors seeking for diversification across Eurozone stock markets.

This paper aims to examine herding behaviour among investors and traders in UK-listed Real Estate Investment Trusts (REITs) within three market regimes (low, high and extreme volatility periods) from the period June 2004 to April 2016.

Observations of investors in 36 REITs that trade on the London Stock Exchange as at April 2016 were used to analyse herding behaviour among investors and traders of shares of UK REITs, using a Markov regime-switching model.

Although a static herding model rejects the existence of herding in REITs markets, estimates from the regime-switching model reveal substantial evidence of herding behaviour within the low volatility regime. Most interestingly, the authors observed a shift from anti-herding behaviour within the high volatility regime to herding behaviour within the low volatility regime, with this having been caused by the FTSE 100 Volatility Index (UK VIX).

The results have various implications for decisions regarding asset allocation, diversification and value management within UK REITs. Market participants and analysts may consider that collective movements and market sentiment/psychology are determinative factors of risk-return in UK REITs. In addition, general uncertainty in the equity market, proxied by the impact of the UK VIX, may also provide a signal for increasing herding-related risks among UK REITs.

The present study sets out to examine the empirical literature on the behavioural aspects of cryptocurrencies, showing the findings of related studies and discussing the various results. A systematic literature review of cryptocurrencies in behavioural finance seems to be timely and particularly important in terms of providing a guide for future research. Key topics include an extent review on the issue of herding behaviour amongst cryptocurrencies, momentum effects and overreaction, contagion effect, sentiment and uncertainty, along with studies related to investment decision-making, optimism bias, disposition, lottery and size effects.

Systematic literature review.

A systematic literature review of cryptocurrencies in behavioural finance seems to be timely and particularly important in terms of providing a guide for future research. Key topics include an extent review on the issue of herding behaviour amongst cryptocurrencies, momentum effects and overreaction, contagion effect, sentiment (investor's, market's) and uncertainty, along with studies related to investment decision-making, optimism bias, disposition, lottery and size effect.

The authors' survey paper complements recent papers in the area by offering a systematic account on the influence of behavioural factors on cryptocurrencies. Further, this study's purpose is not just to index the relevant literature, but rather to showcase and pinpoint several research areas that have emerged in the field of behavioural cryptocurrency research. For all these reasons, a systematic literature review of cryptocurrencies in behavioural finance seems to be timely and particularly important.