CHAPTER 4 Data & Methodology
4.1 Data
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立 政 治 大 學
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N a tio na
l C h engchi U ni ve rs it y
CHAPTER 4 Data and Methodology
Chapter 4 integrates and analyzes the data group. Also, it introduces the details of the DID model architecture and the regression formula. Through the analysis, it provides a better understanding of the regression results in Chapter 5.
4.1 Data
Tables 4.1.1, 4.1.2, and 4.1.3 explain the terms of regression data. This paper examines the key indicators of the circuit breaker mechanism as changes in stock prices and volume. Therefore, the intraday stock price index, the transaction amount, and the trading volume are selected. They were used to measure the effectiveness of the circuit breaker mechanism on the stock market, to encourage a more accurate and comprehensive analysis of the circuit breaker mechanism.
Table 4.1.1 The control variables used in regression
Referring to the empirical method of the past literature, the following control variables were selected: total assets, leverage, profits, and earnings ratio.
Table 4.1.2 The price variables used in regression
Variable Meaning Definition
log_tas Total assets Log(Total assets)
lev Leverage Total debt /Total assets
prof Profit Net profit/Total assets
Gain Earnings ratio Stock price/EPS
Variable Meaning Definition
Clsprc Close price Daily close price
Opnprc Open price Daily open price
Loprc Lowest price Daily lowest price
Hiprc Highest price Daily highest price
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To determine the mechanism’s effect on stock price, the close price, open price, lowest price, and highest price are selected as the outcome variables. The changes in the long-term analysis and short-long-term analysis are observed before and after implementing the circuit breaker mechanism.
Table 4.1.3 The volume and value variables used in regression
In addition to the outcome variables of price, we also wanted to obtain the difference between the values for the long-term analysis and the short-term analysis of the daily volume and value of stock traded, we also selected daily trading volume and daily trading value as outcome variables.
Because the circuit breaker mechanism is based on the CSI300 Index, the constituent of the CSI300 Index is selected as the treatment group. Due to this treatment group selection, it is necessary to select the data of the approximate treatment group as the control group. We choose the relatively large capital in the Shanghai and Shenzhen stock market to be the control group. The control group will be selected from the top 300 listed companies in the Shanghai and Shenzhen stock market by eliminating the stocks in the treatment group.
Table 4.1.4 The time period of the long-term and short-term groups
Variable Meaning Definition
Dnshrtrd Daily trading volume Dnvaltrd Daily trading value
Long-term data Short-term data
Pre June 2015–December, 2015 November 20, 2015–December 3, 2015 Post January 2016–March, 2016 January 4, 2016–January 7, 2016
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立 政 治 大 學
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N a tio na
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When analyzing the stock price index in the session, we use long-term analysis and short-term analysis to measure the indicator across the two sets of data. The long-term analysis group selected the time range from June 1, 2015, to March 31, 2016, which is mainly due to the stock market disaster in China's A-share market since June 2015. At that time, the Shanghai Composite Index fell from 5,178 points to 2,850 points in only two months. Subsequently, the Chinese government announced in September 2015 that it intends to follow the foreign -recommended circuit breaker mechanism to stabilize the stock market. In January 2016, the follow-up resolution officially implemented the fuse mechanism. Therefore, the time period in the long-term group will not consider the time before the stock market crash in June 2015, but it will consider the long-term research scope for the three months after the stock market crash and the fuse mechanism.
The short-term data come from the 10 trading days before the China Financial Futures Exchange issued the “Related Regulations on Index Circuit Breaker” because it is speculated that its release psychologically affects the market. Therefore, as a sample for data analysis, the possible bias must be eliminated. The time point before December 4, 2015, was selected as the pre-period of the short-term analysis. Furthermore, the four trading days after implementing the mechanism were selected as the short-term observation group. Because the circuit breaker mechanism was removed four days after it was implemented, the amount of reference data is insufficient. Therefore, for the short-term group, we chose to use the data period that included the week before the mechanism as the control group.
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Table 4.1.5 Long-term statistics
Table 4.1.5 illustrates the statistics of outcome variables in the long-term analysis. The
“time-dummy zero” value means the period before implementing the circuit breaker mechanism, while “time-dummy one” means the period after implementing mechanism.
Also, the “treatment zero” indicates the control group, which does not implement the circuit breaker mechanism, and “treatment one” indicates the treatment group, which is implements the mechanism. When the circuit breaker was implemented, the daily trading volume of the components or non-components of CSI300 stocks fell by 50%
and 40%, respectively. The stock prices also generally fell after implementing the circuit breaker mechanism. This showed that both the components and non-components of the CSI300 stocks were affected by the circuit breaker. The standard deviation in the post period is generally larger than in the per period, indicating that the fluctuations between the shares after the policy is relatively large after the policy.
Variable Mean Std. Dev
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Table 4.1.6 Short-term statistics
The statistics of the outcome variables in the short-term analysis are listed in table 4.1.6.
Both the statistic in the long-term and short-term analysis achieved similar results. After implementing the circuit breaker mechanism, the mean of the stock prices and trading volume fell, and the mean of the stock price and trading volume in the experimental analysis were also higher than those of the control group. Further regression analysis is included in Chapter5.