Three-way PCA of interval data for dynamic features extraction in futures market

By applying Symbolic Data Analysis (SDA) methods, this paper investigates the dynamic features of Copper futures market of Shanghai Futures Exchange (SHFE) during 2005 to 2006. First, we pack up mass futures contracts as their different residual time (monthly) to the expiration dates, which forms the interval symbolic data and greatly reduces the dimension of the sample space. Based on that, three-way principal component analysis (PCA) of interval data is adopted to extract the dynamic principal characteristics of Copper futures market, which reduces the dimension of the variable space. The results of the case study, which are rightly coincident with the realities, verify the application value of SDA in analyzing mass, dynamic and complex database.