Mustafa Afeef, Shahid Jan, Fayaz Ali Shah, Hamid Ullah, Raza Ullah


Investment in stock portfolios has never been a risk-free course of action as countless factors impinge on the end result of such a venture. Although fairly rewarding, the element of uncertainty involved keeps many potential investors away as they fail to adequately forecast what moves the stock market is going to make in the near future. The enticement of receiving returns, however, is appealing enough for investors to have their money invested in the stock market. But the ability to forecast the market remains their major necessity. In operational terms, there are two ways of forecasting the current and future values of any time series including stock indices. One way is to regress stock returns over all those factors that have an effect on stock market performance. The other method is making predictions on the basis of the past performance of the stock market. The current paper has adopted the second method of forecasting and has made use of the ARIMA technique. Monthly stock returns data of KSE 100 Index was collected from 1997 to 2019 which translated into 266 observations. It was realized that the technique used in the study helped in adequately predicting stock returns, although only in the short run. The outcomes of this study may be of help for prospective stock market investors, specifically short-term, in deciding when, and when not, to extend their investments at Pakistan Stock Exchange.


ARIMA, Box-Jenkins Methodology, KSE 100 Index, Prediction, Stationarity

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Sarhad Journal of Management Sciences by Sarhad University of Science & Information Technology is licensed under a Creative Commons Attribution 4.0 International License.
Based on a work at suit.edu.pk