본 연구는 2001년 1월 2일부터 2006년 6월 30일까지 중국 동현물과 동선물의 수익률 자료를 사용하여 동선물의 헤지성과에 대해 분석하였다. 단위근 검정결과, 동현물과 동선물의 가격은 단위근을 가지고 있어 불안정적 시계열이었다. 1차 차분한 변수들은 안정적인 시계열이었다. 그런데 동 현·선물가격은 공적분되어 있어 두 시계열의 장기적 관계가 안정적이었다. OLS 모형, VECM 및 이변량 GARCH(1,1) 모형으로부터 얻은 헤지포트폴리오 수익률 분산과 헤지성과를 비교하였다. 내표본의 경우, 헤지포트폴리오 수익률 분산이 OLS 모형에서 가장 작았고, 단순헤지 모형에서 가장 높았다. 그리고 단순헤지포트폴리오와 여타 헤지포트폴리오 간에 수익률 분산의 차이는 유의적이었다. 외표본의 경우, 헤지성과가 이변량GARCH(1,1) 모형에서 가장 높았고 단순헤지 모형에서 가장 낮았다. 그리고 헤지포트폴리오 간에 수익률 분산의 차이는 유의적이지 않았다. 위안화 대비 원화 환율에 따른 환차손익이 존재할 때, 내표본에서는 헤지포트폴리오 수익률 분산이 VECM에서 가장 작았고, 단순헤지포트폴리오와 여타 헤지포트폴리오 간에 수익률 분산의 차이는 유의적이었다. 외표본에서는 이변량 GARCH(1,1) 모형의 헤지성과가 가장 높았다. 그리고 시간불변 분산을 가정한 모형과 시간가변 분산을 가정한 모형 간에 헤지포트폴리오 수익률 분산의 차이가 유의적이었다. 흥미롭게도 환차손익을 감안하면 내표본에서 헤지포트폴리오 수익률 분산은 더 커지지만, 외표본에서 헤지성과는 더 높아졌다. 결론적으로, 중국 동선물시장에서 헤지를 할 경우 현물과 선물을 단순히 1대1로 헤지하는 것이 복잡한 모형을 사용하는 것과 모형에 따른 비용을 감안해서 비교해 보면 한계적 효율성을 보이고 있지만, 한국의 기업이 환차손익을 반영해야할 경우 시간가변 분산을 가정한 모형을 사용하는 것이 유리하다고 하겠다.
Copper futures has the second largest trading volume in the world after aluminum futures in the futures markets of nonferrous metals. China is the world`s largest consumer of copper and the trading volume of Chinese copper futures of SHFE (Shanghai Futures Exchange) was 22% of that of LME (London Metal Exchange) in 2004. The economy of China is the second largest in the world after the US. China has been the fastest growing major nation for the past quarter of a century with an average annual GDP growth rate above 10%. Consumption of copper in China has increased rapidly. Chinese copper demand will remain strong in future because copper is used mainly for electric generation systems. Accordingly, hedging with Chinese copper futures is becoming a more significant subject to researchers as well as companies that consume copper directly. Many of the participants in futures markets aim to reduce or eliminate a particular risk that they face. Since risk is usually measured as the volatility of portfolio returns, the hedgers may be interested in the hedge ratio that minimizes the variance of the returns. The purpose of this paper is to find a compatible hedging model on the hedging with the Chinese copper futures. We investigate the hedging performance of the Chinese copper futures. We establish the conventional OLS (ordinary least square), VECM (vector error correction model) and bivariate GARCH (generalized autoregressive conditional heteroscedasticity) model as hedging models and analyze their hedging performances. The sample period covers from January 2, 2001 to June 30, 2006. The optimal ratio is calculated as a ratio of the conditional covariance between spot and futures to the conditional variance of futures. The hedge ratios are estimated by a time-varying hedging model (bivariate GARCH) as well as naive or time-invariant (OLS, VECM) models. To compare the performances in each type of hedge, we divide the sample period into in-sample and out-of-sample and measure hedging performances for each period. In-sample period is from January 2, 2001 to June 30, 2005, and out-of-sample period is from July 1, 2005 to June 30, 2006. Our main results are summarized as follows. First, in ADF (augmented Dickey-Fuller) test and PP (Phillips-Perron) test, both the spot and futures prices series are non-stationary, while two return series are stationary. In Engle and Granger cointegration test, there is a cointegration relationship between the two prices series. Second, the conditional variances and covariances vary over time. In case of in-sample, the variance of portfolio returns in the OLS model is smallest. The variance of returns in the naive model is higher than those in the other hedging models. And the F test shows that the differences between the variance of returns in the naive model and in other hedging models are significant. Third, it turns out that the bivariate GARCH model performs better than other models in case of out-of-sample. Our results indicate that investors in the Chinese copper futures markets are encouraged to use the bivariate GARCH model to hedge the volatility of copper price. But the variance of portfolio returns in the bivariate GARCH model is not lower significantly than those in other hedging models. Forth, if investors take into account profits and losses due to the changes of the exchange rate between yuan and won, the in-sample variance of portfolio returns in the VECM is smallest and the bivariate GARCH model performs better than other models in case of out-of-sample. The out-of-sample variance of portfolio returns in the bivariate GARCH model is lower significantly than those in other hedging models. In sum, our results indicate that the naive hedging model is not a poor choice for hedging the risk with the Chinese copper futures compared to much more complex models. However, time-varying hedging models as GARCH perform better for the Korean firms which are exposed to the exchange rate risk. This study will be a guiding help to the firms to hedge the risk with the Chinese copper futures in SHFE. A comparative study on hedging effectiveness of copper futures in SHFE, together with LME or COMEX (Commodity Exchange of New York) will be an interesting future research.