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 macroeconomic version of the APT is of great significance in examining the return on assets. It analyzes the estimated security return with reference to various macroeconomic variables. Despite availability of research studies related to the developed and emerging stock markets of the world, still a research gap exists for exploring the frontier markets like equity market of Pakistan. The study examines the long and short term impact of macroeconomic variables on the KSE 100 index for the period of July 1996 - June 2015. Cointegration technique and VECM models have been applied. Among these variables, GDP, inflation, exchange rate, unemployment rate, labor force cost and stock market of US were found significant for explanation of effects on return of stock market of Pakistan. The study findings have potential implications for both policymakers and investors pertaining to macroeconomic factors and stock market volatility.