Preprint Article Version 1 This version is not peer-reviewed

Modeling and Forecasting the Algiers Stock Exchange Returns using the Box-Jenkins Methodology

Version 1 : Received: 12 September 2019 / Approved: 13 September 2019 / Online: 13 September 2019 (12:33:41 CEST)

How to cite: Boudrioua, M.S. Modeling and Forecasting the Algiers Stock Exchange Returns using the Box-Jenkins Methodology . Preprints 2019, 2019090134 (doi: 10.20944/preprints201909.0134.v1). Boudrioua, M.S. Modeling and Forecasting the Algiers Stock Exchange Returns using the Box-Jenkins Methodology . Preprints 2019, 2019090134 (doi: 10.20944/preprints201909.0134.v1).

Abstract

The Algiers Stock Exchange (ASE) is the only stock exchange in Algeria. It’s one of the newest and smallest emerging stock exchanges in the world. The focus of this paper is to model and forecast monthly returns of the ASE index (DZAIRINDEX) using The Box- Jenkins methodology. The period of this study is from Jun 2010 to July 2019. According to Akaike’s Information Criterion (AIC) estimator, the Seasonal Autoregressive Integrated Moving Average SARIMA(2,0,0)(0,0,1) is chosen as the best model for forecasting the monthly DZAIRINDEX returns. Diagnostic tests confirm that the fitted model is adequate, where the residuals of this model are normally distributed with no autocorrelation and no heteroskedasticity. The forecast of the monthly DZAIRINDEX returns for one year ahead using this model shows a decreasing fluctuations trend. Based on different measures of forecast accuracy such as ME, MAE, RMSE, MASE, we show that the forecast accuracy of SARIMA(2,0,0)(0,0,1) is acceptable and this model performs much better than a naïve model. These results could be used by the financial communities in Algeria to deal with stock exchange risks and to improve their decisions.

Subject Areas

Algiers Stock Exchange; Box-Jenkins methodology; SARIMA model

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