Estimation And Comparative Research Of The CSI300Stock Index Futures Optimal Hedging Ratios

As the financial derivatives becoming more and more mature, the financial investors in Chinacare more about risk management. As the important tool of avoiding the systematic risk of stockmarket for investors, stock index futures are applied widely. Since the CSI300stork index futures wasintroduced in domestic stock market, more and more domestic scholars have performed the researchon its hedging function. Combining the actual exchanging data of the CSI300stock index futuresfrom2010to2012, this paper estimates and compares its optimal hedging ratio. The first chapterstudies the research background, research significance as well as the domestic and overseas researchstate. The concepts, characteristics and functions of stock index futures and hedging are defined andanalyzed in chapter two, the development process of the CSI300stock index futures is reviewed andarranged, and the formula of hedging ratio is able to be deduced precisely. The third chapter analyzesthe optimal hedging model, categorizes the current existing hedging models which can be divided intotraditional(static) hedging model, time varying(dynamic) hedging model as well as non-linear relativehedging model, and can precisely know the theory, characteristics and applicable conditions of eachmodel. The key point of the whole dissertation focuses on the fourth chapter, in which the close pricedata of the CSI300index series trading days and futures are collected, the data are handled by usinglogarithm, and daily return rate is gained by using difference. Furthermore, the stationary test andco-integration test are performed for the gained four indexes so that it can prove if two sets of timesequences exist co-integration relationship. Thereafter, OLS is applied to estimate the daily return ratefunction of spot and futures, the ARCH-LM test is conducted for residual error sequence to decide ifthe GARCH model will be established. Finally, the descriptive statistical analysis is performed for twosets of time sequences(the logarithm of close price), and whether or not the data exist sharp peak andheavy tail as well as asymmetric characteristics is to decide if the Copula function will be introduced.Through four models such as ECM, VECM, ECM-BGARCH(1,1)-BEKK,Copula-ECM-BGARCH(1,1), the optimal hedging ratio of the CSI300stock index futures isestimated and the effectiveness of the hedging of four models is compared. Combining thecharacteristics of financial time sequence existing the sharp peak and heavy tail as well asasymmetrical distribution, the elliptic type Copula function is introduced to calculate the time varyingnon-linear correlation coefficient of futures and spots, thus the dynamic optimal hedging ratio can beestimated. Empirical research demonstrates that the application of Copula-ECM-BGARCH(1,1)model is the breakthrough of hedging theory and its effect is prior to other hedging models.