Stock Price Prediction Using the ARIMA Model

Adebiyi, A. A. and Ayo, C. K. (2014) Stock Price Prediction Using the ARIMA Model. In: 2014 UKSim-AMSS 16th 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: Conference or Workshop Item (Paper)
Subjects: H Social Sciences > HB Economic Theory
Q Science > QA Mathematics > QA76 Computer software
Depositing User: Mr DIGITAL CONTENT CREATOR LMU
Date Deposited: 23 Sep 2019 11:09
Last Modified: 23 Sep 2019 11:09
URI: https://eprints.lmu.edu.ng/id/eprint/2357

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