實證結果指出：股價指數與大豆油期貨之報酬，兩者存在波動叢聚之特性（即 拒絕同質變異之假設），此亦說明採用 GARCH 模型的適切性。由於農產品現貨 具有中長期之生長週期特性，因此透過雙變量 GARCH 及 GJR-GARCH 模型捕捉 此特性，避險績效在中長期的避險期間表現較佳，隨著避險期間的延展，避險績 效有更顯著的提升。最後，農產品現貨價格受供需狀況影響較深，價格波動亦容 易受到天候因素影響，因此相較於週避險，日避險策略更能有效地使投資組合變 異數下降。 This study primarily examines the cross-hedging performance with the most actively traded contract, soybean oil futures on Dalian Commodity Exchange. Unlike previous studies, we constructed two market indices for agribusiness companies listed on the Shanghai Stock Exchange and the Shenzhen Stock Exchange as proxy for stock market performance. Based on the bivariate GARCH-type framework, important evidences are illustrated in our empirical results and it provides global traders with worthwhile implications for optimal utilization of futures contracts. To improve the weakness of symmetric GARGH model, we employ the GJR-GARCH model to capture the asymmetric effect in volatility of financial variables. Owing to the implementation of the split share structure reform in 2005, more tradable shares on stock market might lead to a substantial increase in liquidity. Further, since the existence of the cycle in agricultural crop production, the hedge period length and hedging frequency serve a vital role in agricultural futures hedging. Our finding offers insightful suggestion for domestic individuals and institutional shareholders who suffer from the price fluctuation in agricultural market.