Forecast of copper price series using vector support machines

Abstract

We research the potential of Support Vector Machines (SVMs) for forecasting in chaotic series of copper's price; based on different combination of structure, and possibilities of discovering knowledge in big data. It was built models of SVMs to forecast the copper's price of the London Metal Exchange (LME).