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
Link To Document :
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