秦溶苑

【Abstract】This study investigates the risk management of investing Shanghai Composite Index employing IF300 during April， 16 2010 to July 31， 2015. Accordingly， we calculate hedge ratios （HR） and hedge effectiveness （HE） of IF300 on the SCI. For this objective， we use OLS， VECM and GARCH （1， 1） models. The hedge performance analysis was performed not only by in-sample but by out-of-sample with 175 estimates. And the following conclusions have been drawn： First， the existence of unit roots has been found both in SCI and IF300. Second， there is at least one co-integration between them. Third， no significantly differ exists in HRs and HE calculated by several models. IF300 contracts provide a reasonably high level of HE.

【Key words】SCI； IF300； hedge ratio

I. Introduction & Theory

Risk management has become increasingly important in the future as investors recognize their exposure to a greater degree of uncertainty in stock markets. The hedging of basic risk is grounded in the mean-variance framework of Markowitz （1952）， and after that， was originally applied to futures hedging. Over the years， several measures have been employed for the hedge ratio computation. The vast majority of these studies have employed OLS [eg. Ederington （1979） and Figlewski （1984）]， VECM [eg. Ghosh （1993a； 1993b） and Kroner and Sultan （1993）] and GARCH model [eg. Hsu， Tseng and Wang （2008） and Lypny and Powalla （1998）].

So far， there are very few studies done in the region of risk management in China stock market. Therefore， this paper provides empirical evidence on the HE to reduce the risk of listed stock investment in Shanghai Stock Exchange. To achieve this， we examine hedge between Shanghai and Shenzhen 300 futures （IF300） and Shanghai Composite Index （SCI） for risk management.

The remainder of the paper is organized as follows. Section II describes the data and characteristics. The methodology is presented in Section III， while the empirical results are discussed in Section IV. And Section V shows the conclusion.

II. Data and Descriptive Statistics

In the paper， the sample period presented lasted from April， 16 2010 to July 31， 2015 with 1275 sample observations. Daily SCI and IF300 returns were calculated as the difference in the natural logarithms of daily closing prices.

To analyze the descriptive statistics， we estimate that the series are leptokurtic forms according to the skewness values （-0.714386， -0.168036） and the kurtosis values （7.781868， 9.025988） of differentiated series. Based on the Jarque-Bera test， the differentiated series are statistically significant， suggesting that the returns are not normally distributed. Moreover， the high correlation values （0.99） show that there is a strong relationship between SCI and IF300.

In

， the results of Augmented Dickey-Fuller and Phillips-Perron tests demonstrate the level variables of SCI and IF300 are non-stationary but their returns are stationary. Then， based on results of the Johansen co-integration test shown in ， there is a co-integration relationship between the level variables.

V.Conclusions

In this study， we examine the interdependence of SCI and IF300 for 1275 trading days. The SCI and IF300 HRs have been calculated with daily returns by using unit root tests， co-integration test and the hedge models. In order to analyze the hedge performance， the hedge ratio should be estimated by using minimum variance hedge model with out-of-sample （175observations）.

Accordingly， the following conclusions can be addressed in this study：

First， the existence of unit roots has been found both in the SCI an IF300. Second， there is at least one co-integration between them. Third， no significantly differ exists in hedging ratios and performance calculated by several models respectively. IF300 contracts provide a reasonably high level of HE （75%～86%） and it can be said that IF300 contracts provide useful risk management tool for hedging and for portfolio diversification in investing listed stock of Shanghai Stock Exchange .

References：

[1]Degiannakis，S.and C.Floros（2010），“Hedge Ratios in South African Stock Index Futures，” Journal of Emerging Market Finance，9，285-304.

[2]Figlewski，S.（1984），“Hedging Performance and Basis Risk in Stock Index Futures，” Journal of Finance，39，657-669.

[3]Hsu，C.C.，C.P.Tseng and Y.H.Wang（2008），“Dynamic Hedging with Futures：A Copulabased GARCH Model，” Journal of Futures Markets，28（11），1095–116.

[4]Markowitz，H.M.（1959），“Portfolio Selection：Efficient Diversification of Investments，”John Wiley and Sons，Inc.，New York.

[5]Pradhan，K.C.（2011），“The Hedging Effectiveness of Stock Index Futures：Evidence for the S&P CNX Nifty Index Traded in India，”South East European Journal of Economics and Business，10，111-123.