We consider a new time-series model that describes long memory and asymmetries simultaneously under the dynamic conditional correlation specification, and that can be used to assess an extensive evaluation of out-of-sample hedging performances using aluminum and fuel oil futures markets traded on the Shanghai Futures Exchange. Upon fitting it to the spot and futures returns of aluminum and fuel oil markets, it is found that a parsimonious version of the model captures the salient features of the data rather well. The empirical results suggest that separating the effects of positive and negative basis on the market volatility, and the correlation between two markets as well as jointly incorporating the long memory effect of the basis on market returns not only provides better descriptions of the dynamic behaviors of commodity prices, but also plays a statistically significant role in determining dynamic hedging strategies. Copyright 2009 The Author. Journal compilation 2009 East Asian Economic Association and Blackwell Publishing Ltd..