Research For Hedge Ratio Of Gold Futures On Six Basic Models

Gold,which is rare and precious, has excellent physical and chemical prop-erties. Before the collapse of the Bretton Woods system.Gold has long been regarded as equivalent currency,and is widely used in social work and life. Al-though it now has been out of circulation,it is still a good tool for investment. Moreover, with the rapid development of new technology and world-wide gol-balization, gold is widely recognized as one of the most important financial assets,with an ever-increasing demand.Those who operate,trade and consume gold, are inevitably influenced by the frequent fluctuations of its price during the transaction. How to lock the risk of its price fluctuations and avoid unnecessary loss during trading process has become a headache problem for them..On January9th,2008,Gold futures was finally listed on the Shanghai Futures Exchange, providing gold produc-ers and operators a good way to lock the price risk-hedging. A hedge is a position established in one market in an attempt to offset exposure to price changes or fluctuations in some opposite position with the goal of minimiz-ing one’s exposure to unwanted risk. The core index of hedging, namely the determination factor,is hedging ratio,which is particularly importantThere are a variety of ways to estimate hedging ratio.the earliest method could be dated back to1960,named risk minimization method which is pro-posed by Johnson.Later, some scholars proposed utility maximization method. Then how to accurately estimate the optimal hedging ratio has become a hot subject.Lots of scholars launched a wide-range and in-depth studies.they have put forward OLS model, ECM model, GARCH model, ECM-GARCH mod-el.EGARCH model and so on,in order to find the most appropriate method to estimate optimal hedging ratios. Each complex models was an effective supplement of the previous model, in order to make the previous one closer to the actual economic situation.Because of the difference of time and peri-od,the opinion of those scholars differ from each other as to which model can best estimate hedging ratio.Peng Hongfeng (2009), using the data of Chinese soybean futures to conduct a comparative study with five statistical models,such as OLS, B-ECM, VAR, B-GARCH, ECM-BGARCH, found out that the estimated hedging effect of OLS is optimal, yet the most complex model-BGARCH is the worst. Because it is difficult to determine the coefficient of investor’s risk appetite, which is vital when utility maximization method is to be used to estimate optimal hedging ratio. So considering this,this paper is trying to determine the current optimal hedge ratio of gold futures using risk minimization methodThis paper is divided into five chapters. The first chapter, details back-ground, purpose and meaning of the gold futures hedging research and sum-marise in the timeline the research findings of both foreign scholars and do-mestic scholars, and on this basis put forward the study thought and content of this paper.The second chapter introduces the history and development of futures,and the contracts and trading rules of gold futures.besides,this chapter gives a de-tailed discussion of the development of three important hedging theories.and then introduce a very important concept of hedging research-basis,and how to use it.finally we discuss two methods of the hedging ratio-risk minimiza-tion method and utility maximization method. The Calculation of risk min-imization method is H=Cov(Rs,Rf)/Var(Rf)=ρσs/σf,While the Calculation of utility maximization method is H*=E(△Ft)+2λCou(Rs,Rf)/2λVar(Rf)The third chapter mainly describes the commonly used hedging models and the applicable conditions as well as the theory of each model and its theoretical introduction.It mainly includes OLS model (ordinary least squares model), ECM model (ECM), ECM-GARCH model, GARCH model, EGARCH model and B-GARCH model.The fourth chapter is the empirical analysis.We choose the closing price of gold futures Shanghai Futures Exchange,and the closing price of gold spot of Shanghai Gold Exchange as our study sample,which period is from February1st,2012to February,1st,2013. Firstly we use OLS model to estimate the hedg-ing ratio, discovering the existence of autoregressive conditional heteroskedas-ticity. Based on this, stationary test and cointegration test is used to revise the data to make sure it meets the requirements.the data is modified in order to establish the ECM (Error Correction Model), GARCH, ECM-GARCH, E-GARCH model, and derived estimated hedging ratio under each model. Then we use the sequence of first-order differential gold futures and spot prices to establish GARCH models, using the formula H=ρσs/σf to simulate dynamic Hedging ratio sequence of gold futures.Finally we make a comparative study of these six basic models on the hedging effect.The fifth chapter, hedging performance measurement and conclusions of this article. This chapter adopts Ederington’s method(1979) to mea-sure hedging performance, the core is to calculate compared to no hedg-ing, the degree of risk reduction after hedging.We use He to describe it.(He=Var(Ut)-Var(Wt)/Var(Wt)).The results show that, after hedging, six basic model can effectively reduce the risk of the portfolio. And the lowest cost of hedg-ing is OLS model, while its efficiency is the highest, but considering the assumptions (residuals with variance, subject to normal and no serial correla-tion), futures and spot prices for gold sequence in general is difficult to achieve such strict rules of OLS models. And the GARCH model considers both the autocorrelation and lieteroscedasticity of time series, and the hedging costs of EGARCH model is just a little higher than OLS model.Therefore, this paper concludes, for China’s gold futures, the effect of EGARCH model is the best.