Do Investors Herd in Global Stock Markets?

Chen, Tao

doi:10.1080/15427560.2013.819804

Cited by 92 publications

(45 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Interestingly, the parameters of return dispersion (β 1 ; β 2 ) are still significant and positive, providing strong evidence of the absence of herding behaviour in American stock markets. Scholars (Yao et al, 2014;Chen, 2013) supported Christie and Huang's (1995) assumption that cross-sectional dispersion should be negatively correlated with trading volume when herding occurs. However, in our case, trading volume does not improve herding behaviour in the US markets.…”

Section: Modified Regression Of Herding Measurementioning

confidence: 90%

“…However, empirical results on how trading volume affects herding are confused. On the one hand, Fu and Lin (2010) advanced that low trading volume may influence herding behaviour among Chinese equity market; they argue that low trading volume responds more slowly to information and lack of information is the main trigger of herding behaviour (Chen, 2013). On the other hand, Tan et al (2008) found that herding tends to be stronger in bull market, high trading volume and high volatility.…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Volume-herding interaction in the American market

BenSaïda

Jlassi

Litimi

2015

AJFA

View full text Add to dashboard Cite

This paper examines the existence of herding in the US market. We study the turnover effect on herding movement by modifying the CrossSectional Standard Deviation (CSSD) model and the Cross-Sectional Absolute Deviation (CSAD) model. Results are inconclusive about the presence of herding in the US financial market. However, we find that trading volume can trigger herding. By applying VAR and Granger causality tests, we find a strong link between herding and trading volume in both directions. More particularly, we find that trading volume can enhance herding behaviour and vice versa, i.e. herding intensifies trading. Moreover, we examine the herding behaviour during the subprime crisis, and find that herding is inhibited during this period.

show abstract

Section: Modified Regression Of Herding Measurementioning

confidence: 90%

Section: Literature Reviewmentioning

confidence: 99%

Volume-herding interaction in the American market

BenSaïda

Jlassi

Litimi

2015

AJFA

View full text Add to dashboard Cite

show abstract

“…For more on this, see Holmes et al (2013). 24 Chen (2013), Philippas et al (2013) and Mobarek et al (2014) reported significant herding during market slumps. found significant herding in both up-and down-markets for Chinese A-shares; conversely, herding was significant only in downside markets for B-shares.…”

mentioning

confidence: 99%

Herding dynamics in exchange groups: Evidence from Euronext

Economou

Gavriilidis

Goyal

et al. 2015

Journal of International Financial Markets, Institutions and Mo

View full text Add to dashboard Cite

 We examine whether joining an exchange group confers an effect over herding in the group's member-markets and if this effect persists when accounting for various domestic and international market states, the dynamics of the group's member-markets and the outbreak of financial crises  We test for the above in the context of the Euronext, which contains four equity markets (Belgium, France, the Netherlands and Portugal)  Herding is significant post-merger in all four markets; herding in Portugal is significant (yet less strong) pre-merger as well. These results are robust when controlling for various domestic/international market states and the dynamics of the group's markets  Herding following the outbreak of the euro-zone crisis is significant in Belgium, the Netherlands and Portugal, and is motivated by the dynamics of the group's two largest markets (France and the Netherlands). *Highlights (for review)Page 2 of 33 A c c e p t e d M a n u s c r i p t Herding Dynamics in Exchange Groups: Evidence from Euronext AbstractThis study investigates in the context of the Euronext, whether joining an exchange group affects herding in the group"s member-markets and if this effect persists when accounting for various domestic and international market states, the dynamics of the group"s member-markets and the outbreak of financial crises. We find that herding is significant post-merger in all four constituent equity markets (Belgium, France, the Netherlands and Portugal) of the Euronext, with herding in Portugal being significant (yet less strong) pre-merger as well. These results are robust when controlling for various domestic and international market states, as well as the dynamics of the group"s markets. The period following the outbreak of the euro-zone sovereign debt crisis produces significant herding in Belgium, the Netherlands and Portugal, with this herding being motivated by the dynamics of the group"s two largest markets (France and the Netherlands).JEL classification: G12, G15, G31

show abstract

“…Herding has now become a common phenomenon in equity markets, and a number of scholars have observed herd behaviour in equity markets around the world (See, e.g., Peiyuan and Donghui, 2002;Demirer and Kutan, 2006;Tan et al, 2008;Chiang and Zheng, 2010;Demirer et al, 2010;Balcilar et al, 2013;Chen, 2013).…”

Section: Literature Reviewmentioning

confidence: 99%

Herd behaviour in the cryptocurrency market: Fundamental vs. spurious herding

Senarathne¹,

Jiang²

2020

EurJ Appl Econ

View full text Add to dashboard Cite

This paper sets out to explore whether the investor herding in the cryptocurrency market induces correlations in cryptocurrency returns using the methodology of Chang et al. (2000) and Galariotis et al. (2015) from a daily data sampling period of 3/30/2015 to 5/24/2019. The initial regression results show that the cross-sectional absolute deviation of return can only be explained by GSCI oil and gold index return, but no relationship exists between cross-sectional absolute deviation of return and other regression variables, such as return on CCi30, US equity risk premium and US/Euro exchange rate return. The herding regression results under normal market condition show that a strong tendency exists to herd on non-fundamental information that explains cross-sectional absolute deviation of returns. As such, cryptocurrency returns cannot be predicted on the basis of fundamental economic information (e.g., major macroeconomic announcements). Herding on non-fundamental information is found to be more pronounced during an upward-trending period of the market and other than upward-trending period. No signs of herding on fundamental information could be observed under other market conditions. Although the theory suggests that herding on non-fundamental information results in more efficient outcomes, the above findings do not encourage the diversification of traditional assets with cryptocurrency on the basis of low correlation. Since cryptocurrency lacks intrinsic value, the exchange is shown to provide a pseudo-efficient trading platform for speculative investors. Implications for future research are discussed.

show abstract

Do Investors Herd in Global Stock Markets?

Cited by 92 publications

References 16 publications

Volume-herding interaction in the American market

Volume-herding interaction in the American market

Herding dynamics in exchange groups: Evidence from Euronext

Herd behaviour in the cryptocurrency market: Fundamental vs. spurious herding

Contact Info

Product

Resources

About