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
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