CHAPTER 5 Regression analysis
5.2 Short-term analysis
Tables 5.2.1 and 5.2.2 explain the coefficient of regression in the short-term group. The following tables analyze the price, volume and value of the stocks.
Table 5.2.1 Short-term regression result of stock price
Variables Clsprc
Note. The values in parentheses are t- value.
*** and ** indicate significant level under one percent and five percent, respectively.
Table 5.2.1 shows the regression results of the stock price indicators under the circuit breaker mechanism in short-term trading, and we obtain four models in the short-term analysis. The biggest difference is that the treatment coefficient in model (Stp1), model (Stp2), model (Stp3), and model (Stp4) all had no significance, indicating that the
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treatment group and the control group had no relevant significance before the policy. In addition, the regression result of the time-dummy coefficient in the short-term group is shown as a negative number, and the result is the same as the long-term group. The price index in the post-period will be lower than that in the pre-period, including the opening price, the closing price, the highest price, and the low price.
In the short-term group, the interaction results of the stock price index all have significant regression results under the circuit breaker mechanism. According to the DID regression model, the different inter-coefficients of the explanatory variables represent the different effects that were produced. We can get the same results as the long-term group, when inter-coefficient is indeed significantly negative, which can confirm that the circuit breaker mechanism does cause the intraday stock price index to fall. It also means that the treatment group will decrease the price index when compared to the control group. This has significantly affected the treatment group. The log(total assets), leverage, profit, and earnings ratio are used as control variables. In the short-term, the higher total assets will make the stock price fall; the higher earnings ratio will make the stock price rise.
Summarizing this data, it becomes evident from the regression model that we can get the same results in the short-term group and long-term group after implementing the policy. It also led to a decline in the intraday share price relative to the other A shares that did not implement a circuit breaker mechanism, but the degree of decline in the short-term group was greater than that of the long-term group. In the short term, the circuit breaker mechanism has further exacerbated the instability of the stock market.
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Table 5.2.2 Short-term regression result of the daily stock market
Note. The values in parentheses are t- value.
*** and ** indicate significant level under one percent and five percent, respectively.
From Table 5.2.2, the daily circulation status is straightforward, and we have four models in the short-term analysis. In the short-term group, both the daily number and value of stocks traded have a significant effect when the circuit breaker mechanism is implemented. The treatment coefficient in model (Stv1) can be found to be significant, which means that daily value of stocks traded in the before treatment group is higher than the before control group after considering impacts from other variables.
Variables Dnshrtrd
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Subsequently, the coefficient of time-dummy is negative in the short-term group. The post-period will decrease the daily number and value of stocks traded from the pre-period.
According to the DID regression model, the different inter-coefficients of the explanatory variables represent the different effects. Furthermore, according to the regression results obtained in the data of model (Stv1) and (Stv2), the interaction coefficients are indeed significant and negative. It can be confirmed that, when controlling other factors after implementing the policy, the daily number and value of stocks traded in CSI300 is significantly reduced. Namely, the treatment group will decrease the daily number and value of stocks traded when compared to the control group after the policy.
The log (total assets), leverage, profit, and earnings ratio are used as control variables.
In the long-term, the higher leverage, earnings ratio, and rate of return will make the number of daily stocks traded and the daily trade value fall; the higher total assets will make the number of daily stocks traded and the daily trade value rise. This result indicates that the circuit breaker mechanism weakens the number of trading shares and liquidity in a trading day. Also, we obtained the same results in the short-term and long-term group—meaning that the liquidity indicator has indeed decreased, but it did not exacerbate the investors' behavior to disregard costs when selling.
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In summary, both the long-term and short-term groups achieved similar results, but the intraday stock price drop is more severe in the short-term while the trade volume decrease is more significant in the long-term. Furthermore, both the long-term group and the short-term group show that the circuit breaker mechanism does reduce the liquidity according to the regression results of the daily stock circulation status, indicating that the stock price decline is not caused by investors disregarding the stock cost when selling.