DocumentCode :
3036271
Title :
Prediction of household food retail prices based on ARIMA Model
Author :
Wang, Yue ; Ye, XingYu ; Huo, Yudan
Author_Institution :
Sch. of Math. & Phys., China Univ. of Geosicences, Wuhan, China
fYear :
2011
fDate :
26-28 July 2011
Firstpage :
2301
Lastpage :
2305
Abstract :
Predictions of retail prices of household foods bear positive meanings in enhancing the living standard of residents. In our paper, first we subdivided the 41 kinds of household food into 5 subcategories basing on trends of their price movements during 2010 to 2011: Smoothly Rising, Rising with Fluctuations, Stable, Horizontal Fluctuating and Concave. Next, we structured separate ARIMA models for each subcategory, and applied such models to predict the prices of the respective subcategories in April and May of 2011. The results suggest that the ARIMA models can produce good simulations and predictions of the retail prices of foods: that the prices of all subcategories of household foods basically preserve an upward trend. The paper concludes with advice on relative policies by the author based on the results obtained, with reference values to the concerned government divisions and relevant parties.
Keywords :
autoregressive moving average processes; economic indicators; food products; pricing; ARIMA model; household food; living standard; price movement; retail price; Analytical models; Autoregressive processes; Economics; Fluctuations; Indexes; Predictive models; Time series analysis; ARIMA; household food retail prices; time series; two-step clustering;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia Technology (ICMT), 2011 International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-61284-771-9
Type :
conf
DOI :
10.1109/ICMT.2011.6002376
Filename :
6002376
Link To Document :
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