Forecasting Saudi Arabia Daily Stock Market Prices
Mahmoud Al-Zyood

1Mahmoud Al-Zyood, King Abdulaziz University, Finance College of Business, P.O. Box 344, Rabigh, Jeddah 21911, Saudi Araba.
Manuscript received on March 14, 2018. | Revised Manuscript received on March 16, 2018. | Manuscript published on July 30, 2018. | PP: 1-6 | Volume-8 Issue-2, May 2018. | Retrieval Number: B3117058218/2018©BEIESP
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Abstract: The Saudi stock market is regionally and globally important due to the country’s economic position as the world’s largest oil producer and its inherent socio-political role as a major world economy. Stock market prices are one of the main factors affecting the national economy, indicating economic strength and attracting investment. This paper inspects the best autoregressive integrated moving average (ARIMA) model to forecast daily stock market prices in Saudi Arabia. The results indicate that the optimum model is ARIMA (4, 4, 0, 0), due to the ACF having an exponential deterioration and the PACF having a spike at lag12, which is an indication of its being the best model to forecast Saudi Arabia stock market prices from 2000 to 2018. The least Akaike Information Criterion (AIC) value was used to select the appropriate model from 25 tentative ARMA models. The chosen model is the first one, AIC -5.404104. The selected ARIMA (4, 4) (0, 0) predicts the future values of time series (stock market prices) with 95% prediction intervals for the next year. It is important to focus on the improvement and development of other models to improve the forecasting process and improve the ability of companies to plan. The results expected by the model indicate economic strength in the near future, which stimulates the economic situation of the state and increases confidence in it.
Keywords: Bayesian Information Criterion, Akaike Information Criterion, Saudi Stock Exchange (Tadawul), Stock Prices, Prediction Models, Forecasting.