Empirical Research For Optimal Hedging Ratio And Portfolio Of Stock Index Futures

After the global financial crisis in2008, The Characteristics of stock market in Shanghai and Shenzhen are system risk is increasing. Stock market investors are urgent to need a new financial tool to avoid system risk, On April16,2010, the HS300stock index futures contracts are listed in financial futures exchange in Shanghai. Fill with the blank of China’s stock index futures, at the same time, Shanghai and Shenzhen stock market investors have a new effective tool to aversion risk. The risk aversion function of stock index futures through hedging strategy, investors often make use of stock index futures hedging for spot stock portfolio, avoid the stock market system risk or reduce investment loss. However, hedging with futures contracts, the core stage is lies in how to choose the optimal hedging ratio, so goal of this article is how to choose the optimal hedging ratio, this is also the significant of article.In this article we select the weight of the HS300index of stocks ranked in the top50stocks as alternative sampled stocks, which stocks returns with the HS300stock index futures returns correlation coefficient greater than0.5for the rule of choosing the stock as spot portfolio. Based on the exist stock of spot portfolios. We are study the optimal hedging ratio from static and dynamic angles respectively. Research on the static optimal hedging ratio, we used the method of OLS model, B-VAR model and VECM model; While the research on the dynamic optimal hedging ratio, we used the method of VECH-GARCH model and BEKK-MGARCH model, CCC-MGARCH model, DCC-MGARCH model.In actual study process, different method estimate the hedge ratio is often not consistent, so we need to compare and evaluate the hedging ratio of hedging performance, and select the optimal hedging ratio. So this article will from the perspective of aversion risk and perspective of utility maximization to evaluate the hedging performance respectively. The evaluation index of risk reduction measure is HE, and the evaluation index of utility maximization is Sharp ratio. But in compare to the dynamic hedging performance, we add the dynamic adjustment costs change how to effecting the hedging performance in Sharp ratio. Comparison results show that the dynamic model estimate the hedge Ratio of hedging performance is superior to static hedging estimated model, and add dynamic adjustment cost factors Sharp ratio is more in line with the actual situation, also have more significance to guiding the hedgers.