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Shareholder Disputes and Commonality in Liquidity: Evidence from the Equity Markets in China

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Abstract

This paper examines liquidity commonality is caused by correlation in institutional herding and shareholder disputes due to irrational investors over the period from 2007 to 2017 in China. Consistent with the fund liquidity hypothesis, we find that shareholders dispute is negatively associated with liquidity commonality and that this negative relationship is more pronounced in firms with more excess control rights and desirability of liquidity for governance. We conclude that it is important to consider not only control-ownership divergence, which has been shown to be a supply-side factors as institutional herding from foreign investors, but also liquidity commonality in information environment. The block holders can cause the liquidity when shareholder disputes are governed by block holders to intervene and sell their stake to exit by threaten, or disagreement trade against the mispricing. This work contributes to the growing literature by analyzing the impacts of controlled ownership divergency on commonality in liquidity as well as the impact of investor sentiment related to the information environment.

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Notes

  1. Domestic investors in China cannot invest in foreign financial assets and foreign investors cannot invest in the Chinese A-share market. The Qualified Foreign Institutional Investors (QFII) program is a securities investment mechanism that was implemented prior to the complete opening-up of the Chinese capital market to foreign investments. Foreign investors may remit a certain amount of foreign currency and convert it into local currency with the approval of relevant authorities. China launched the QFII program to allow licensed investors in local securities to make investments through special purpose accounts and vice versa.

  2. As shown in Chordia et al. (2011).

  3. The equation for \(\Lambda\) can be decomposed into two parts as follows:

    $$\begin{aligned} & \Lambda_{t} = \left[ {\frac{1}{{\left( {k - 1} \right)\sigma \left( {B_{k,t} } \right)\sigma \left( {B_{k,t - 1} } \right)}}} \right]\sum\limits_{k = 1}^{k} {\left[ {\sum\limits_{i = 1}^{{I_{k,t} }} {\left[ {\frac{{\left( {D_{i,k.t} - E\left( {B_{t} } \right)\left( {D_{i,k,t - 1} - E\left( {B_{t - 1} } \right)} \right)} \right)}}{{I_{k,t} I_{k,t - 1} }}} \right]} } \right]} \\ & \quad + \left[ {\frac{1}{{\left( {k - 1} \right)\sigma \left( {B_{k,t} } \right)\sigma \left( {B_{k,t - 1} } \right)}}} \right]\sum\limits_{k = 1}^{k} {\left[ {\sum\limits_{i = 1}^{{I_{k,t} }} {\sum\limits_{j = 1,j \ne i}^{{I_{k,t - 1} }} {\frac{{\left( {D_{i,k,t} - E\left( {B_{t} } \right)\left( {D_{i,k,t - 1} - E\left( {B_{t - 1} } \right)} \right)} \right)}}{{I_{k,t} I_{k,t - 1} }}} } } \right]} \\ \end{aligned}$$

    INHD denotes the time-series average of the correlation coefficients and the first-term on the right-hand side of this equation represents the magnitude of the proportion of non-herding (NH) as adjusted to their own portfolio through trading or selling or buying for institutional investors; \({\text{I}}_{k,t}\) is the number of institutional investors trading industry k on the trading day t; Di, k, t is a dummy variable that is equal to one if investor i is a buyer in this industry on trading day t and zero if investor is a seller. Dj, k, t-1 is a dummy variable that is equal to one if investor j is a buyer in industry k on trading day t-1 and zero if investor \(i \ne j\) is a seller of industry k on trading day t.

  4. Using the Shapley value measure, each shareholder will have 1/3 the Shapley value, for example, the major shareholders hold 49%, 49%, or 2% of voting rights (total 100%), meaning that each shareholder is equally important in deciding firm policy, because to reach a majority requires at least two of them to vote together.

  5. To mitigate the impact of the split share structure reform implemented in April 2005, the sample period used in our primary analysis commences in 2005.

  6. The liquidity investor will halt decisions to trade when the liquidity is sufficiently low and the transaction costs sufficiently high. However, liquidity traders may trade regardless of transaction costs and as a consequence returns may be nonzero. The LOT model is rooted in the adverse selection framework (Glosten & Milgrom, 1985; Kyle, 1985) and treats zero returns as evidence that the transaction cost threshold has not been exceeded by the liquidity traders. \({\text{LOT}}_{i,t} = \frac{{\sum\nolimits_{j = 1}^{t} {R\_ZERO_{i,j} } }}{{N_{t} }}\).

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Acknowledgements

The author is grateful to anonymous referee, Douglas Cumming, Gary Tian, Xuan Tian, Geoffrey Wood, Cynthia Clark, Luigi Zingales, Anthony Saunders, L. Hung, Yu-Jane Liu, and seminar participants in numerous institutions and conferences for helpful comments and suggestions. Some data for this study were collected while G. Lin was a professor of the Chengchi University for financial statement studies, and additional data were assembled during a visit to the National Taiwan University who is excellent acknowledged. We also thank the econometric analysis from those fellows of Taiwan Econometric Society. Any remaining errors are the author’s own.

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    Mu-Shun Wang

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Wang, MS. Shareholder Disputes and Commonality in Liquidity: Evidence from the Equity Markets in China. Asia-Pac Financ Markets 29, 291–325 (2022). https://doi.org/10.1007/s10690-021-09350-8

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