Abstract
PurposeThe purpose of this paper is to provide a stable model which covers market information of return to examine the empirical differences between the returns during night and day in Chinese commodity futures market.Design/methodology/approachCommodity indices are constructed using principal components analysis to represent the market returns for day and night trading in the Chinese commodity futures market. Then VAR models are employed to predict the commodity indices’ returns and squared returns.FindingsThe symmetric VAR model failed to model the market returns since the asymmetric effects of positive and negative returns are not taken into account. By allowing asymmetric behavior among positive and negative variables, asymmetric VAR model is utilized to trace the leading effect of overnight returns to daytime trading returns. However, the symmetric VAR model outperforms the asymmetric model when evaluating the predictive power of squared returns during night trading hours. Two major results based on asymmetric model for the return are: There is a 6-day leading effect of nighttime return to daytime return in Chinese commodity futures market. It is risky to hold day trading position overnight.Research limitations/implicationsAsymmetric VAR model provides a new approach to forecasting the direction of price movement.Practical implicationsInvestment managers are able to create a stable portfolio contains major market information. Day and night traders are likely to gain some suggestions to discover arbitrage opportunities.Social implicationsSince there is no commodity futures index in China, the method for creating indices for Chinese commodity futures is provided to market regulators.Originality/valueCombining principal component analysis and asymmetric VAR model provides a stable and predictable model to obtain market information.
Published Version
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