Can International Market Indices Estimate TASI’s Movements? The ARIMA Model

• Main Authors: Hamzeh F. Assous, Nadia Al-Rousan, Dania AL-Najjar, Hazem AL-Najjar
• Format: Article
• Language: English
• Published: MDPI AG 2020-04-01
• Series: Journal of Open Innovation: Technology, Market and Complexity
• Subjects: stock market index; regression model; linear; power; logarithmic; cubic and quadratic
• Online Access: https://www.mdpi.com/2199-8531/6/2/27

This study investigates the effectiveness of six of the key international indices in estimating Saudi financial market (TADAWUL) index (TASI) movement. To investigate the relationship between TASI and other variables, six equations were built using two independent variables of time and international index, while TASI was the dependent variable. Linear, logarithmic, quadratic, cubic, power, and exponential equations were separately used to achieve the targeted results. The results reveal that power equation is the best equation for forecasting the TASI index with a low error rate and high determination coefficient. Additionally, findings of the AutoRegressive Integrated Moving Average (ARIMA) model represent the most important variables to use in order to build a prediction model that can estimate the TASI index. The ARIMA model (with Expert Modeler) coefficients are described as ARIMA (0,1,14). The results show that the SP500, NIKKEI, CAC40, and HSI indices are the most suitable variables for estimating TASI with an R² and RMSE equal to 0.993 and 113, respectively. This relationship can be used on the previous day to estimate the opening price of TASI based on the closing prices of international indices.