Examining the metal futures price discovery in China from multi-scale time

Metal mineral resources are important raw materials in industrial production, and metal as an important object in the futures market, its discovery function is an important sign to measure the level of market development. The price of metal futures market has the characteristics of high-frequency data, and the mechanism of price discovery in different frequencies needs to be realized by time series decomposition method. In this paper, the complementary ensemble empirical mode decomposition with adaptive noise vector autoregressive model is constructed to re-examine the price discovery of nonferrous metal futures from the aspects of multilevel, multi-subject, and different volumes. Four typical nonferrous metals are selected for empirical research in China. The results show that price discovery exists in China's nonferrous metal futures market. Meanwhile, there are significant differences in the functional efficiency of typical metal prices under different time scales. The volume of contracts will greatly affect the efficiency of price discovery. Finally, we also find that futures prices affect spot prices, but spot prices do not affect futures prices.