Herding behavior in Chinese stock markets: An examination of A and B shares

By Lin Tan, T. C. Chiang, Joseph R. Mason, Edward F. Nelling. 2008

685 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/51cc18b924b1d493770f9011bab0ee20101e33ec

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Citations in the corpus

A cross-country analysis of herd behavior in Europe (2014, methodology): “While investigating the information asymmetry in stock markets, researchers (Tan et al., 2008; Chiang and Zheng 2010; and Economou et al., 2011) have predicted that investors in financial markets are more likely to exhibit herd behavior.”
Cross-country effects in herding behaviour: Evidence from four south European markets (2011, neutral): “Along the same lines, Tan et al. (2008) examined this issue in dual-listed Chinese A-shares and B-shares from 1996 to 2003.”
Investor mood, herding and the Ramadan effect (2016, background): “14 The effect of volume over herding has been denoted by several studies, including Tan et al. (2008) and Economou et al. (2011).”
An empirical analysis of herd behavior in global stock markets (2010, methodology): “Yet, in a recent study of Chinese stock markets, Tan et al. (2008) report that herding occurs under both rising and falling market conditions and is especially present in A-share investors.4 Thus, the evidence from the studies cited above shows mixed results and that most herding behavior is…”
Herding behaviour in energy stock markets during the Global Financial Crisis, SARS, and ongoing COVID-19* (2020, neutral): “However, the disadvantage of CSSD is that it can easily be affected by outliers empirically, so it is difficult to find any evidence of herding behaviour in normal conditions ([16] Tan et al.”
Institutions and Information Environment of Chinese Listed Firms (2012, background): “feedback strategies; such trading behavior is consistent with institutional investors discounting their private information about fundamental valuations when making their portfolio allocation decisions, and instead trading on the basis of market sentiment, information contained in past trades and ge”