Chinese automobile demand prediction based on ARIMA model

Author

Chen, Daoping

Author_Institution

Sch. of Econ. & Manage., Chongqing Normal Univ., Chongqing, China

Volume

4

fYear

2011

fDate

15-17 Oct. 2011

Firstpage

2197

Lastpage

2201

Abstract

Chinese automobile industry is a pillar industry of national economy. Forecasting on automobile demand of China is helpful for government to draft automobile industry policies and for automobile enterprises to plan their output. In this paper, based on autoregressive integrated moving average (ARIMA) time series model, I build a forecast model of automobile demand of China by using the monthly data of automobile sales from China Association of Automobile Manufactures (CAAM) in 2001.01-2011.06. Furthermore, I evaluate the forecasting performance of established model and find that it is very well.

Keywords

automobile industry; autoregressive moving average processes; biological techniques; demand forecasting; time series; ARIMA time series model; Chinese automobile demand prediction; Chinese automobile industry; automobile enterprises; automobile industry policy; autoregressive integrated moving average; demand forecasting; forecasting performance; Automobiles; Correlation; Forecasting; Industries; Mathematical model; Predictive models; Time series analysis; ARIMA model; automobile; demand; prediction;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Engineering and Informatics (BMEI), 2011 4th International Conference on

Conference_Location

Shanghai

Print_ISBN

978-1-4244-9351-7

Type

conf

DOI

10.1109/BMEI.2011.6098744

Filename

6098744