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The paper studies the effects of the stock index futures on the spot market volatility of China, through GARCH model, using HS300 stock index futures and the HS300 index as the research object. The empirical results show that the HS300 stock index futures has weakened the spot market volatility in spite of its very small; In addition, the introduction of HS300 stock index futures accelerate the transmission of the spot market information, showing that stock index future develop the function of price discovery. Introduction The first stock index futures contract officially listed on exchanges in the United States, Kansas, on February 24, 1982, then it has become an important tool to avoid the risks and promote the stability development of the spot market. China financial futures exchange (CFFE) issued the HS300 index futures simulation transaction price index On October 30, 2006, then officially launched the HS300 index futures On April 16, 2010. The introduction of stock index futures not only improves the structure of China's securities market, but also has a profound impact on promoting the healthy development of China's securities market. Since then, the relation between the introduction of stock index futures market and the spot market volatility has become a controversy topic, which is the study in this paper. Literature review A variety of Scholars at home and abroad study the effects different stock index futures on the volatility of different the spot market. Bologna (2002) analyze the volatility of the Indian stock market based on the GARCH model, and the results show that the launch of stock index futures decreases the volatility of stock cash market; Li Zhuo (2007) carried on the empirical analysis in our country Taiwan area about the impact of stock index futures on the spot, which is showing that the introduction of stock index futures reduce the volatility of the spot market in Taiwan; Huang Wei, Liu Zaihua (2007) by studying the stock index futures influenced the volatility of NIFTY in Indian stock market concluded that: the introduction of NIFTY index futures effectively reduced the volatility of the Indian stock market. Model specification and data processing Model specification GARCH (p, q) model is as follows: International Conference on Economic Management and Trade Cooperation (EMTC 2014) © 2014. The authors Published by Atlantis Press 249 σ 2 t=ɑ0+ɑ1μ 2 t-1++ɑiμ 2 t-i++ɑq μ 2 t-q+β1σ 2 t-1++βjσ 2 t-j++βpσ 2 t-p. (1) Wherein p, q is a positive integer; ɑ0>0, ɑi≥0,vi=1,2,,q; βj≥0, j=1,2,,p; GARCH model uses four parameters to describe its volatility, which ɑ0 represents uncertainty in the original system, ɑi says the impact of new information on market volatility, and βj characterizes the impact of old information on the market volatility. In this model, the greater the value of ɑi, the better the speed and quality of information transmission, and the greater the value of βj, suggesting the influence of volatility interference factor more durable and the poorer the speed and quality of information transmission. In addition, when the articles on total sample modeling, the GARCH model is introduced a virtual variable D, which set D=0 before HS300 index futures issued and set D=1 after HS300 index futures issued. So the conditional variance equation of GARCH model, adding the virtual variables, can be written as: σ 2 t=ɑ0+ɑ1μ 2 t-1++ɑiμ 2 t-i++ɑq μ 2 t-q+β1σ 2 t-1++βjσ 2 t-j++βpσ 2 t-p+φD. (2) If φ >0, the introduction of stock index futures increases the volatility of the stock market; If φ < 0, it reduces the volatility of the stock market, and if φ = 0, the stock index futures has no effect on the volatility of the stock market. Data selection and statistical description Data selection The paper selects daily closing price of HS300 index as data, and the reason of choosing it is that it reflects most of the market behavior and more persuasive. All data come from the netease finance. In order to compare the influence on the spot market volatility before and after the stock index futures introduced, data is divided into two subintervals,which are the HS300 index of daily closing price (It)before the HS300 index futures introduced ( April 10, 2007 April 15, 2010) and after the HS300 index futures introduced (April 16, 2010-March 15,2013) . And the total of the data are 1474. In paper, R, R1, R2 are respectively used to present the return of the total samples, before the introduction of HS300 index futures, and after the introduction of HS300 index futures. In addition, the paper uses the log-return first order difference as day returns, so the calculation formula is: Rt = Ln (It) -Ln (It-1) (3) Figure 1 the HS300 index day return line chart

An Empirical Analysis of the Effects of the Stock Index Futures on the Spot Market Volatility of China