The Research Of Stock Index Future Hedge

Stock index futures has a function of hedging.It is a very important one the best tool to avoid systemic risk. China released the first stock index futures of the Shanghai and Shenzhen 300 stock index futures on April 16th, in 2010. This has an important impact on Chinese securities market. How to more effectively make good use of the financial products ,the asset managers needs to do the in-depth research of hedging strategies and determines the hedge ratio.This paper does the comprehensive research and analysis on relational literatures,based on expounding theory of stock index futures and hedging.This paper puts emphasis on four models of stock index futures hedging strategy.It includes the traditional model of stock index futures hedging(OLS), two-variable vector auto regression model(B-VAR), error correction model(ECM)and the GARCH model, and comparative analysis.The traditional model of stock index futures hedging(OLS)has the most important defect of ignoring the residuals'autocorrelation.The B-VAR model solves the problem of identification of the model assumptions,that is the sequence to eliminate residual autocorrelation problem. ECM model considers the the spot prices and futures prices'non-stationary ,long-term equilibrium relationship and short-term dynamic relationship. OLS model establishes on the base of the futures prices and spot prices'fixed variance. But the actual change of the futures prices and spot prices has the different variance characteristics generally. Therefore, the estimated result will produce systematic bias.But GARCH model makes up for this defect, which allows the sample data conditional heteroscedasticity and conditions of covariance estimation ,and solves the problem of the data estimating that heteroscedasticity caused.And it also reflects the new information on the impact of hedge ration.This article puts emphasis on the OLS method.Although OLS method is very simple in use by a wide range of applications, it must satisfy some specific assumptions in order to ensure the effective that the sequence is not related,normal distribution and the same variance. Therefore, this article analies the defects of the OLS model . This article used data from the Shanghai and Shenzhen 300 stock index as the sample data, and the sequence of autocorrelation distribution for empirical analysis. Empirical results is that OLS model has that defects in application.Therefore, the regression coefficient of the simple linear regression is not the best estimate of the minimum risk hedge ratio in the case of not meeting for the OLS assumptions.