Title :
Chinese automobile demand prediction based on ARIMA model
Author_Institution :
Sch. of Econ. & Manage., Chongqing Normal Univ., Chongqing, China
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;
Conference_Titel :
Biomedical Engineering and Informatics (BMEI), 2011 4th International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-9351-7
DOI :
10.1109/BMEI.2011.6098744
