Movements in a stock market index may safely be considered one of the mostwatched out phenomena by investors in almost every economy. One method to forecast the index is to study all those external factors that directly affect it. Another way, however, is to base ones predictions on the past behavior of the variable of interest. This paper has employed the method described latter and has, therefore, made use of the ARIMA modeling. In this connection, the daily stock market index data of the Karachi Stock Exchange 100 index was taken for twenty years from 1997 to 2017 which translated into 4940 observations. The study revealed that the model was decently efficient in forecasting the KSE 100 Index, though only for the short-range. The upshot of this study may be utilized specifically by short term investors in deciding on when, and when not, to invest in the stock market.

The stock market index can be forecasted in two ways --- either through taking those external factors that influence movements in the index or by basing ones predictions on the previous values of the index. The current study has used the method described later by employing the Box-Jenkins methodology --- a method famously used by most researchers while conducting ARIMA modeling--- by taking past figures of KSE 100 Index. Quarterly figures of the Index were, therefore, taken for 22 years from August 1995 to October 2017 that translated into 90 observations. Results revealed that the forecasting model used in the study did well in anticipating returns in the shortrun. The findings of the study can be consumed by investors, particularly short-term, in deciding when, and when not, to risk their hard-earned funds at Pakistan Stock Exchange.