Forecasting Mineral Commodity Prices with ARIMA-Markov Chain

Abstract

Scientific prediction has an important significance for establishing industrial policy and making plan in economic market. For the purpose of forecasting mineral commodity price accurately, an ARIMA-Markov chain method is proposed based on the study of time series methods and stochastic process theory. In order to test the prediction effect of the proposed method, a case study is carried out through using mineral molybdenum price values as research data. The results of the case study indicate that the prediction precision of our proposed method is much higher and less limitation to prediction step length than ARIMA model. It is proven that ARIMA-Markov chain performs an excellent property for mineral molybdenum price prediction.