• DocumentCode
    3564631
  • Title

    Stock Price Prediction Using the ARIMA Model

  • Author

    Ariyo, Adebiyi A. ; Adewumi, Adewumi O. ; Ayo, Charles K.

  • Author_Institution
    Sch. of Mathematic, Stat. & Comput. Sci., Univ. of KwaZulu-Natal, Durban, South Africa
  • fYear
    2014
  • Firstpage
    106
  • Lastpage
    112
  • Abstract
    Stock price prediction is an important topic in finance and economics which has spurred the interest of researchers over the years to develop better predictive models. The autoregressive integrated moving average (ARIMA) models have been explored in literature for time series prediction. This paper presents extensive process of building stock price predictive model using the ARIMA model. Published stock data obtained from New York Stock Exchange (NYSE) and Nigeria Stock Exchange (NSE) are used with stock price predictive model developed. Results obtained revealed that the ARIMA model has a strong potential for short-term prediction and can compete favourably with existing techniques for stock price prediction.
  • Keywords
    autoregressive moving average processes; forecasting theory; share prices; stock markets; time series; ARIMA models; NSE; NYSE; New York Stock Exchange; Nigeria Stock Exchange; autoregressive integrated moving average models; economics; finance; short-term prediction; stock price prediction; stock price predictive model; time series prediction; Computational modeling; Data models; Forecasting; Indexes; Mathematical model; Predictive models; Time series analysis; ARIMA model; Short-term prediction; Stock Price prediction; Stock market;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Modelling and Simulation (UKSim), 2014 UKSim-AMSS 16th International Conference on
  • Print_ISBN
    978-1-4799-4923-6
  • Type

    conf

  • DOI
    10.1109/UKSim.2014.67
  • Filename
    7046047