Explaining Asymmetries and Long Memory for Hedge Effectiveness in China Aluminum and Fuel Oil Futures Markets
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A new time series model is developed to describe long memory and asymmetries simultaneously under the dynamic conditional correlation specification and can be used to assess an extensive evaluation of the out of sample hedging performance using aluminum and fuel oil futures markets in Shanghai Futures Exchange. Upon fitting it to the spot and futures returns of aluminum and fuel oil markets, we find 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 provide better descriptions of dynamic behavior of the commodity prices, but also plays an important role in determining the dynamic hedging strategies.
Abstract
A new time series model is developed to describe long memory and asymmetries simultaneously under the dynamic conditional correlation specification and can be used to assess an extensive evaluation of the out of sample hedging performance using aluminum and fuel oil futures markets in Shanghai Futures Exchange. Upon fitting it to the spot and futures returns of aluminum and fuel oil markets, we find 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 provide better descriptions of dynamic behavior of the commodity prices, but also plays an important role in determining the dynamic hedging strategies.
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