The Study Of Hedging Performance Between Stock Index Futures And SSE180ETF In Our Country

The securities market is an investment market, which exists risk and return. According to the different nature of risk, securities price fluctuation risk includes systematic risk and unsystematic risk. Unsystematic risk can be eliminated through fully decentralized investment, but the systemic risk can not. Unsystematic risk can be fully eliminated through ETF, but incapable of systemic risk. The CSI300index futures provide a hedging tool of avoiding systematic risk for ETF investors. The paper contains five parts:The first part is the history and present situation introduction of stock index futures and ETF. Then it summarizes the hedging theory research home and abroad, which lays the theoretical foundation for the paper.The second part introduces the stock index futures contract features, basic transaction system, function and generated process, characteristics, functions of ETF. Then it analysises the same and different points of ETF and stock index futures comparatively and their mutual influence.The third part is the stock index futures hedging theory review.Firstly, it introduces the economics principle of hedging and the concept of long hedging, short hedging and cross hedging. Secondly, it introduces three kinds of static hedging model:OLS model, B-VAR model and ECM model. And it also introduces two kinds of dynamic hedging models:Modified ECM-GARCH model and D-BEKK model. Lastly, it derives the minimum variance optimal hedge ratio and the formula, then it introduces the hedging performance evaluation method.The fourth part is the empirical study of hedging performance between stock index futures and the SSE180ETF. Firstly, the descriptive statistics show that the volatility of future market is more than the spot, the future and spot return series are not subject to normal distribution.The stationary test result shows that the spot and future return series are1(1). EG cointegration test shows that the spot and futures return series exist cointegration relationship. Secondly, Using OLS model, ECM model, Modified ECM-GARCH model to estimate the optimal hedge ratio(OHR). The OHR of OLS model is0.906328. The OHR of ECM model is0.911552. The mean of OHR of Modified ECM-GARCH model is0.941811, the standard deviation is0.077261. lastly, it analysises hedging performance of the three models comparatively, the conclusions are as follows:(1) portfolio variance of Modified ECM-GARCH model is the smallest.(2) the investor utility level of OLS model, ECM model, Modified ECM-GARCH model and no hedging respectively is-0.0000335-λ*0.0000248203,-0.0000304-λ*0.0000248303-0.0000108-λ*0.0000242458,-0.000574-λ*0.000219129(3) In the case of not considering transaction cost from adjustment of stock index futures contract position, For any λ, the investor utility level of Modified ECM-GARCH model is the highest.(4) when λ=1, the utility level of the four kinds of model calculated by the mean variance utility function is-0.00079313,-0.00005832,-0.00005523,-0.00003505. The UI of the three hedging model respectively is0.00073481,0.0007379,0.00075808.(5) In the case of considering transaction cost, When the commission rate is less than0.00002, the investors will choose Modified ECM-GARCH model for hedging; When the rate is between0.00002and0.000023, choose ECM model for hedging; When the rate is greater than0.000023, choose OLS model or ECM model for hedging.The fifth part summarizes the empirical part and then prospects the direction of further research. The possible innovations in the paper are as follows:First, it introduces the Modified ECM-GARCH model to solve the problem of cointegration and residual heteroscedasticity. Analysising hedging effect through dynamic and static hedging methods comparatively.Second, it uses mean variance utility function to measure the utility level of different hedging model.Third, Considering the transaction cost of the dynamic hedging, it solves the hedging model selection under different commission rate.