DocumentCode :
3361885
Title :
Forecasting Mineral Commodity Prices with ARIMA-Markov Chain
Author :
Li, Yong ; Hu, Nailian ; Li, Guoqing ; Yao, Xulong
Author_Institution :
Sch. of Civil & Environ. Eengineering, Univ. of Sci. & Technol. Beijing, Beijing, China
Volume :
1
fYear :
2012
fDate :
26-27 Aug. 2012
Firstpage :
49
Lastpage :
52
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.
Keywords :
Markov processes; autoregressive moving average processes; forecasting theory; industrial economics; minerals; molybdenum; pricing; time series; ARIMA; Markov chain; economic market; industrial policy; mineral commodity price forecasting; mineral molybdenum price value; stochastic process theory; time series method; Forecasting; Markov processes; Mathematical model; Minerals; Predictive models; Time series analysis; ARIMA; Forecasting; Markov chain; Mineral commodity price;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2012 4th International Conference on
Conference_Location :
Nanchang, Jiangxi
Print_ISBN :
978-1-4673-1902-7
Type :
conf
DOI :
10.1109/IHMSC.2012.18
Filename :
6305622
Link To Document :
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