Use of Time Series Analysis Models to Predict the Emerging Financial Market Index: A Case Study on the General Index of the Dubai Financial Market

Abstract

This research seeks to build a random changes model for the DFM index values, using time series analysis models, which are Box - Jenkins models, especially ARIMA (p, d, q) , then predicting future changes to the values of the Dubai Financial Market index, for the first two months of 2019. This would help investors to have accurate assessments of the reality of investment in the Dubai market and the movement of the index in the future. Thus, they would act based on these assessments by either investing in the market by creating a portfolio close to the general index of the market in the event of positive assessments, or not investing in the event of negative assessments and searching for other areas for investment. The researcher relied on the daily closing prices of the general index of the Dubai Financial Market in the actual trading days during the period 2010 - 2018 and obtained 2464 views representing the closing prices of the index from the official website of the Dubai Financial Market. The researcher concluded that the appropriate model for forecasting is the ARIMA (1,1,0) , as it showed high efficiency and great ability to predict accurate future values at 98.70%. It predicted the estimated values of the index for the first two months of 2019 accurately. The values were very close to the actual values of the Dubai Financial Market Index. The study also showed that the general trend of the Dubai Financial Market Index is an upward trend, attracting and encouraging investment. Moreover, the inefficiency of Dubai Financial Market scored low level. The study recommends that investors in the Dubai Financial Market need to study and analyze the movement of the market index as a sign of all fluctuations of share prices of companies listed in the market, in order to identify the trends of the market and have the right investment decisions.