An Empirical Analysis on the Relationship between Stock Price Index and Macroeconomic Variables in China

: The relationship between the stock price index and the macroeconomic variables has always been the hot topic in the economics field. From the point of view of empirical analysis, this paper made Unit-Root Test, Co-integration Analysis, Granger Test and Impulse Response Analysis on the relationship between the stock price index and macroeconomic variables such as industrial production, money supply, interest rate, save and price index based on the monthly data from January in 2016 to March in 2021. The result shows that there exists the negative relationship between stock price index and long-term interest rate and save; while the stock price index is positive with industrial production and short-term interest rate; furthermore, there exists the positive relationship between stock price index and the initial stages of the money supply and inflation, while the stock price index is negative with the later period of the money supply and inflation.


Introduction
As an important place of direct financing, stock market not only plays the role of resource allocation, but also plays the role of economic prediction and value discovery as a barometer of national economy, the status of the stock market in the national economy has been unprecedented. But since June 2007, China's stock market has taken a nosedive, coming out of a bear market that is completely out of line with the overall trend of the national economy and is the longest in the history of the stock market. Therefore, the relationship between the stock market and the macro-economy has become one of the focuses of discussion in the theoretical and industrial circles, which is not only related to the development of our country's capital market, but also related to the formulation of a country's economic policy and the rapid development of the economy. It has strong theoretical and practical significance. [1] 2. Empirical Analysis

Selection of Indicators
From an economic perspective, this paper selects short-and long-term interest rates, money supply, savings, industrial value-added and price indices, which are closely related to the stock market, as macroeconomic variables, the Composite Stock Price Index of Shanghai and Shenzhen stock markets are used as a measure of stock price to examine the relationship between the between stock price index and macroeconomic. [2] This paper uses monthly data from January 2016 to March 2021 with the annual price level in 2015 as the base period, and converts the monthly CPI data into the regular CPI data, on this basis, the nominal value-added of industry is converted into the real value-added of industry, and at the same time, in order to avoid sharp fluctuations in the indicators, the selected short-term interest rate, long-term interest rate, money supply rate, real industrial value added, savings, price index, Shanghai Composite Index and Shenzhen Composite Index were logarithmically processed. LNRRATE, LNLRATE, LNM1, LnRip, LnSave, LNCPI, LnSZ, LnSH, respectively. [3]

Methodology
Because the macroeconomic variables interact with each other, the effects of these variables on the stock market may also cancel each other out. Therefore, this paper analyzes the stock price index and the industrial value-added, money supply, interest rate, savings and price index as a system, the unit root test, co-integration test, Granger cause test and impulse response function were used to analyze the relationship between them. [4]

The Results of Co-integration Test
DLnSZ, DLnSH, DLnCpi, DLnRip, DLnM1, DLnSave, DLnRrate, DLnLrate are all I (1). In this paper, the Vector autoregression Johansen co-integration test is applied to examine the relationship between Shanghai Composite Index and Shenzhen Composite Index and macroeconomic variables. The test results are as follows: Table 2 and Table 3:  Table 2 shows that the maximum eigenvalue corresponds to a statistic larger than the 5% significance threshold, while the second largest eigenvalue corresponds to a statistic smaller than the 5% significance threshold. Therefore, we reject the first original hypothesis and accept the second hypothesis, that is, there is only one co-integration relationship between Shanghai Stock Index and each variable, and the co-integration equation is The sequence of its residuals is Vect=LnSH-0.0477LnM1+1.645693LnSave-0.39554LnRrate+0.564803LnLrate -13.6537LnCpi--0.00813LnRip +36.15924  Table 3 shows that the trace statistics corresponding to the largest eigenvalue are larger than the critical value of 5% significance level, while the trace statistics corresponding to the second largest eigenvalue are smaller than the critical value of 5% significance level. Therefore, the first hypothesis is rejected and the second hypothesis is accepted, that is, there is only one cointegration relationship between Shenzhen index and each variable, which is expressed as: LnSZ=4.69823LnM1-8.687198LnSave+0.01211LnRrate-3.51245LnLrate+26.3387LnCpi +1.64041LnRip-75.2151 The sequence of its residuals is Vect=LnSZ-4.69823LnM1+8.687198LnSave-0.01211LnRrate+3.51245LnLrate-26.3387LnCpi ADF test is used to test the stability of the residual sequence, and it is found that the residual sequence is stable, which proves that there is a long-term equilibrium relationship between the Shenzhen and Shanghai Composite Index and the variables, that is, the Shenzhen and Shanghai Composite Index is positively correlated with money supply interest rates, short-term interest rates, price indices and real industrial value-added, and negatively correlated with long-term interest rates and savings. [6]

Granger Cause Test
Granger cause test results show that there is a long-term stable correlation between Stock Price Index and individual variables, but it is not clear whether this relationship has a statistical cause. Therefore, using group objects in eviews 5.0 to do Granger cause test to test whether there is Granger cause between variables. The test results are shown in Table 4. Cause LNSH can be rejected at significant levels of 5% and 10% , that is, changes in the savings index, the price index and long-term interest rates are Granger cause of the change in the Shanghai Composite Index, but other assumptions can not be rejected, therefore, changes in short-term interest rates, real industrial value-added and money supply are not Granger cause of the Shanghai Composite Index, which can partly reflect the economic situation. For the Shenzhen Index, you can reject the null hypothesis that the variables are not Granger cause at 1%, 5% and 10%, respectively, that is, real industrial value-added, money supply, savings, long-term interest rates, short-term interest rates and price indices are the Granger causes of the Shenzhen Index, which can provide a comprehensive picture of macroeconomic conditions. [7]

Impulse Response Function
In order to measure the effect of random disturbance on the relationship between variables and describe the trajectory of these effects, the next part of this paper is impulse response function analysis. We used the Eviews software to analyze the impulse response function, and the results are shown in figures 1 and 2 From the impulse response function chart, the Shanghai Composite Index and Shenzhen Composite Index are basically the same, the following Shanghai Composite Index as an example to illustrate the Stock Price Index response to the impact of various variables. [8] The Shanghai Composite Index (Lnsh) has a strong reaction to its standard deviation information without any lag, reaching about 0.055 in the current period, then gradually decreased, and tends to be stable to the 20th month.
For long-term interest rates, a standard new spread has a positive response in the second month, a negative response in the sixth month, and then gradually levelled off to zero. This shows that the long-term interest rate and the stock price negative correlation, the higher the long-term interest rate, the lower the stock price. This is in line with the intrinsic value of the stock, because the higher the discount rate, the lower the value of the stock, and thus the lower the price of the stock. [9] And the disturbance of a standard new spread of short-term interest rates had a negative effect in the second month. From the third month, the effect changed from negative to positive, reaching a maximum of 0.005 in the seventh month or so, and then gradually decreased, but the impact has been positive. That short-term interest rates are positively correlated with stock prices, mainly because companies increase their capital requirements while increasing their cash flows and year-end dividends, thus driving up stock prices, under the condition of interest rate marketization, the interest rate will rise, therefore, the stock price and the short-term interest rate are positively correlated, in line with the actual economic phenomenon. [10] The disturbance of savings peaked at -0.005 in the 4th month and levelled off in the 9th month, but the relationship remained negative. This suggests that savings and stock prices move in the opposite direction, because the more savings there are, the less money flowing into the stock market and thus the lower the stock price, in line with economic phenomena.
The fluctuation of a standard new interest rate spread of CPI has a positive effect in the second month, reaches a maximum of 0.003 in the fifth month, and then gradually decreases, from the 10th month to a negative effect, this suggests that inflation initially drives up share prices, but later causes them to fall, mainly because the Means of production price does not rise sharply immediately and the cost of production does not increase significantly, but the sales increase sharply with the price increase, which leads to the increase of the profit of the enterprise, which leads to the rise of the nominal income of the stock and the increase of the demand for the stock, and finally drives the corresponding rise of the stock price. But with rising production costs and inflation expectations, profits have fallen and share prices have fallen, which is in line with reality. [11] The money supply disturbance had a positive effect on the Shanghai Composite Index in the second month, reaching a maximum of about 0.003 in the fourth month, then gradually decreased, and leveled off in the eighth month, but remained a negative effect all the time. This is mainly due to the money supply increase in the cash flow of the stock market and the expansionary effect on the investment of companies, hence the rise in the stock price, but over time the increase in the money supply increases inflation expectations, it increases the incentive for households to hold money and reduces the demand for stocks; this, coupled with the reluctance of commercial banks to lend, has led to a shortage of corporate capital and hence to a fall in share prices.
For the disturbance of a standard new spread of industrial value added, the Stock Price Index had a negative reaction in the 2nd month, but turned positive from the 3rd month and reached a maximum of 0.01 in the 6th month, then gradually reduced until the 10th month began to level off, but has maintained a positive impact. The Stock Price Index of our country is positively related to the national economy, the better the economic development, the higher the stock price, thus reflecting the stock price is the "Barometer" function of the national economy. [12]

Conclusion
The empirical analysis of the relationship between stock price index and macroeconomic variables shows that stock price index has negative correlation with long-term interest rate and savings, positive correlation with short-term interest rate and industrial value added, and positive correlation with money supply rate and early stage of inflation, in the later stage, it is negative correlation, which is basically consistent with economic phenomenon. However, the Stock Price Index of our country has a weak response to other macro-economic variables except its own changes, which shows that the stock market of our country is not effective and there are certain obstacles to the processing of information, therefore, we should speed up the reform of the capital market, increase the construction of transparency and standardization, and make the transmission channel of macroeconomic variables to the stock market unblocked, thus better play the capital market resource allocation and the macroeconomic economic forecast and value discovery functions.