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The results showed in Table 10 are similar with Table 9, several governance variables like management stockholdings, and blockholders’ stockholdings take opposite influence between individual and institutional investors. In addition, to judge whether the variable of information disclosure be took account of investment behaviors, we find that the grade of information disclosure only affect foreign institutional investors’ stockholdings, it shows a positive relation in Table 10.
The variable MGTPARTCEO is negative related to individual investors’ shares holding, illustrating that inside dominance of CEO may reduce the effect of management stockholdings to dependent variables, and vice versa. Finally, we discover individual investors always prefer to invest in small firms, and larger firms do institutional investors so far.
D. Trading Volumes and Trading Volatilities
In this part, we examine Hypothesis 2 by measuring trading volume proxies with OLS Regression Model, separating data as yearly frequency of 15 years, monthly frequency of 15 years, and monthly frequency of 5 years to discuss how the impact on trading volume or volatility caused by governance variables, then comparing the difference between 15 and 5 years’ data. We refer trading volume to trading value (in million) and turnover rate in individual stocks, besides, trading returns (in percentage) is fitted into the analysis as well.
We aim at discussing whether the trading volatilities varied follows by degrees of corporate governance in yearly frequency data of 15 years, therefore we build the model (2-1) to examine, which is showed below:
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(2-1)
Where Yi,t: Trading volumes and trading volatilities ; (1) LnValue: Ln of Trading Value,
(2) LnSDValue: Ln of Standard Deviation of Trading Value, (3) Ratio: Turnover Ratio,
(4) SDRatio: Standard Deviation of Turnover Ratio, (5) Rtn: Returns,
(6) SDRtn: Standard Deviation of Returns
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Table 11. Regression Results for the Trading Volume and Trading Stability – 15 years, yearly frequency
Variable (1) (2) (3) (4) (5) (6)
LnValue LnSDValue Ratio SDRatio Rtn SDRtn
MGT 0.120*** 0.0958*** 16.90*** -0.196* 1.651 -0.420***
t - statistics in parentheses * p<0.1, ** p<0.05, *** p<0.01
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The results of model (2-3) shown in Table 11 included six dependent variables, we discuss the effect of corporate governance factors to trading volume related variables first. After checking the ownership structured factors, we find that management stockholdings, blockholders’ stockholding, and board size are significantly affecting trading value and turnover ratio, where larger management stockholdings (although in a non-linear relation) would lead to larger trading value and turnover ratio, but larger blockholders’ stockholdings and board size would make them down; in general, we always deem the trading turnover ratio as a proxy of trading liquidity, so we can see from Table 11 that management stockholdings is maybe an only factor to promote the liquidity of trading. It display the trading value is changed by outside independent directors, inside dominance of chairman and CEO, firm size, and leverage ratio in Table 11, however, only more outside directors, one of the ultimate controllers serves as chairman of the board, and larger firm size can raise the trading value.
We choose the standard deviation of trading value and turnover ratio as the proxies of trading stability, the standard deviation is computed by the monthly data of trading value and turnover ratio, and we anticipate that better corporate governance mechanism will lead the trading activities tending to be more stable, that is to say the coefficients of them are expected to be negative.
Both the increases of management stockholdings and CEO duality lead the turnover ratio more stable, yet fluctuate the trading value. Nevertheless, there are three factors show completely help with stabilities of trading value and turnover rate – blockholders’ stockholdings, board sizes, and the inside dominance of CEO, which are indicating more part of shares kept by blockholders, larger board size, or one of the ultimate controllers acting as CEO would be ways to lower the trading volatilities.
Next, we examine the changes of trading volume resulted by degrees of corporate
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governance in monthly frequency data of 15 years, the model (2-2) built to examine the effect is showed below:
(2-2)
Where Yi,t : Factors of trading volume;
(1) LnValue: Ln of Trading Value, (2) Ratio: Turnover Ratio,
(3) Rtn: Returns
Table 12 shows the impacts on trading values, turnover ratios, and trading returns with model (2-2), by illustrated in table, we notice almost all the governance variables are significant to the trading volume proxies except the duality of CEO, meaning that corporate governance variable do affect the trading volume of firms, in addition, the past returns either one period or two periods are positive related to trading value and turnover ratio, exhibiting past returns would make trading activities vigorous.
We make a rough estimate of whether the governance factors generate impacts on stock returns also, however we find only blockholders’ stockholding is positive related to the returns, meaning that if block shareholders expand their stockholdings then the stock returns would increase.
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Table 12. Regression Results for the Trading Volume and Trading Stability – 15 years, monthly frequency BOARD2 -0.000791** -0.000792** -0.0162*** -0.0162*** -0.00115 -0.000916
(-2.36) (-2.33) (-3.21) (-3.12) (-0.34) (-0.27)
t- statistics in parentheses * p<0.1, ** p<0.05, *** p<0.01
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In order to compare with results of model (2-2), we examine the changes of trading volume resulted by degrees of corporate governance in monthly frequency data of 5 years and build the model (2-3) by adding the factor of information disclosure, the model (2-3) is presented below and results are showed in Table 13:
(2-3)
Where Yi,t : Factors of trading volume (1) LnValue: Ln of Trading Value (2) Ratio: Turnover Ratio
(3) Rtn: Returns
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Table 13. Regression Results for the Trading Volume and Trading Stability – 5 years, monthly frequency
INV 0.000420 0.000503 -0.000104 0.00119 0.00355 0.00363
(0.84) (0.97) (-0.02) (0.18) (0.66) (0.68)
t- statistics in parentheses * p<0.1, ** p<0.05, *** p<0.01
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In Table 13, It is evident to observe that few of governance factors make negative impact on trading value such as block shareholders’ stockholdings and part management of ultimate controllers, representing these factors are unfavorable to the traders. There are some factors negative related to turnover ratio too, block shareholders’ stockholdings and board sizes is going to be causes to make the turnover ratio decreasing. In addition to the original factors we consider, the information transparency and disclosure ranking is positively significant to trading value and turnover ratio, indicating the better ranking make traders be more confident to the firms and push ahead the accomplishment of the trading.
It is alike to the common sense that the firm size is positive related to trading value but negative related to turnover ratio, larger firms in a way represent a more guaranteed image than smaller firms do; the results of leverage ratio are also quite regular, it is negative related to trading value yet positive related to turnover ratio.
Comparing the influence caused by governance factors between long-run and short-run periods, we notice the results of five years periods are not looked as strong as the long-run, this may because the trading market and mechanism tend to be mature as time goes on, so that more elements in market could grasp traders’ attentions to affect they making decisions on their trades.