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Stock Price Prediction Using the ARIMA Model

Adebiyi, A. A. and Adewumi, O. A. and Ayo, C. K. (2014) Stock Price Prediction Using the ARIMA Model. International Conference on Computer Modelling and Simulation.

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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.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User: Mr Adewole Adewumi
Date Deposited: 20 Mar 2015 16:53
Last Modified: 20 Mar 2015 16:53
URI: http://eprints.covenantuniversity.edu.ng/id/eprint/4117

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