Optimal Hedge Ratio Of HS300Index Futures Based On Copula Models

The stock index futures is an important risk management tool in the financialmarkets, but because of the leverage effect brought about by its margin trading, stockindex futures market bears huge financial risk. April16,2010, China’s HS300stockindex futures turned out, more and more institutional investors participate in thestock index futures trading. Along with the development of China’s stock indexfutures market, how to be able to realize the stock index futures hedging function,effectively disperse and transfer transaction risk has become a major topic of thestock index futures research for investors to generate profits.China’s stock index futures have appeared for a short time, the relative studiesof hedging is lacking. Existing empirical studies have shown that static hedgingmodel is unable to adapt to the needs of practice, time-varying model candynamically reflect the changes in the financial markets. However, most of the earlydynamic hedging model mainly based on GARCH models ignored many restrictions.For example, assuming the normal distribution to estimate the optimal hedge ratio,while the financial time series often non-normal distribution, there exists a "fat tail"phenomenon, and distribution law often appear asymmetric. How to choose a moreappropriate distribution to describe the changes of financial data, and then using thefinancial hedging model, that is extremely concerned by institutional investors.The Copula function overcomes the above analysis assumes, in recent years, thenature of the Copula theory and application get more and more attention. The key ofCopula theory and its application is the integrated application of marginaldistribution fitting model, programming techniques, and the parameter estimationmethod. Copula function modeling methods include static, dynamic and Markov conversion. Past studies have focused on static Copula. But if the financial data haschanged significantly in the sample period, the traditional method would have acertain bias, dynamic and Markov Switching Copula function can better characterizethe time-varying characteristics and state dependency structure of financial assets.Thus this article based on statistics, econometrics and finance theory, using theCopula model to analyzing the hedging problem of the HS300index futures. Takingstatic Copula model for comparison, try to explore the superiority of Copula withdynamic and Markov conversion function modeling method in hedging-relatedresearch, make up for the current research overlooking the dynamic relationship ofspot and futures.Based on the goal of this study, the structure of the paper is organized asfollows: The first chapter introduces the background and significance of the hedgingsubject. Then research at home and abroad are reviewed in Chapter II. The thirdchapter describes the forthcoming in-depth study of several models based on Copulatheory, namely the Copula static dynamic model and Markov Switching Copulamodel. Chapter IV from the empirical point of view, namely the combination ofthese three models to estimates the hedge ratio. Finally, through the calculatedhedging gains to reduce the degree of the variance to compare which model has thebest variance control effect, and then come to the most effective hedging model.Empirical research shows that: the goodness of fit from the logarithm of thelikelihood function or AIC value, dynamic and Markov conversion Copula functionmodeling methods are higher than the static modeling method. This seems that themethods considering Copula function’s dynamically characteristics and status ofdependency relationship modeling method to hedging are more suitable for the studyof China’s stock index futures hedge issue.