This paper examines the validity of Technical analysis on Karachi Stock Exchange by investigating the tools used in Technical analysis for the sample period of 1997 to 2014. The KSE-100 index was examined to investigate the efficiency of stock exchange by employing Wright’s sign based variance ratio test. The results indicate that KSE-100 index is not efficient in its weak form. The study then compared a broad range of technical trading rules based on Simple Moving Averages, Exponential Moving Averages, with Generalized Regression Neural Network (GRNN) to find the forecasting ability of these indicators individually as well as in combination. The results indicate the predictive power over future stock price behavior. The insertion of GRNN enhances the profit generating capacity of above average return. To know that whether it is possible to beat buy-and-hold strategy, the study proposes two trading strategies based on these rules. The proposed strategies have the capability to outstrip the buy-and-hold strategy, even in the presence of transactional cost. Technical analysis is very effective for the investors in creating excess return for the sample period.
Keywords: Market Efficiency, Karachi Stock Exchange, Moving Averages, Artificial Neural Network, Technical Analysis