DocumentCode
693865
Title
Forecasting the CPI Using a Hybrid Sarima and Neural Network Model with Web News Articles
Author
Hui Yuan ; Dailing Zhang ; Wei Xu ; Mingming Wang ; Wenda Dong
Author_Institution
Sch. of Inf., Renmin Univ. of China, Beijing, China
fYear
2013
fDate
14-16 Nov. 2013
Firstpage
84
Lastpage
88
Abstract
Web news fills our life from national affairs to small matters, containing the latent useful information that can reflect the trend of consumer price index. Most previous studies forecast the CPI basing on the historical data while in this paper, the external information is considered and modeled by using the combination of neutral network and seasonal ARIMA model in order to correct the forecasting error for more accurate prediction. The experiments show that the proposed method is better than both the single neutral network and the seasonal ARIMA. The findings imply the web news can bring more precise results in CPI forecasting.
Keywords
Internet; consumer behaviour; forecasting theory; neural nets; pricing; CPI forecasting; Hybrid Sarima; Web news articles; consumer price index; external information; forecasting error; historical data; neural network model; neutral network; Analytical models; Data models; Educational institutions; Predictive models; Semantics; Text analysis; Time series analysis; CPI prediction; SARIMA; hybrid model; neural networks; web news articles;
fLanguage
English
Publisher
ieee
Conference_Titel
Business Intelligence and Financial Engineering (BIFE), 2013 Sixth International Conference on
Conference_Location
Hangzhou
Print_ISBN
978-1-4799-4778-2
Type
conf
DOI
10.1109/BIFE.2013.19
Filename
6961096
Link To Document