• 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