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Ariyo, A.A., Adewumi, O.A. and Ayo, C.K. (2014) Stock Price Prediction Using the ARIMA Model. UKSim-AMSS 16th International Conference on Computer Modelling and Simulation, Cambridge, UK, 105-111.
https://doi.org/10.1109/UKSim.2014.67

has been cited by the following article:

• TITLE: A Short-Term Stock Exchange Prediction Model Using Box-Jenkins Approach

  AUTHORS: Paul Boye, Yao Yevenyo Ziggah

  KEYWORDS: ARIMA, Bayesian Information Criterion, Ghana Stock Exchange, Perfor-mance Indicator

  JOURNAL NAME: Journal of Applied Mathematics and Physics, Vol.8 No.5, April 26, 2020

  ABSTRACT: This paper developed a short-term stock exchange prediction model using the Box-Jenkins approach. In this study, monthly data from Ghana Stock Exchange market report that spans from March 2013 to February 2018 were used to develop the model. ARIMA (0, 2, 1) model was fitted to the data based on the Bayesian Information Criterion (BIC) for model selection. Diagnostic checks showed that the residuals of the fitted model were uncorrelated. The developed model was used for forecasting for a period of six months. The trend of the forecasted values showed a significant increase in the Ghana Stock Exchange performance for the next six months.