Portfolio management is a mean of making profit and expanding wealth through following different security trading strategies, such as the act of buying a financial security at a certain price, and selling it later at a higher price to make profit out of this trade. However, the main difficulty lies in the diligently varying nature of security prices in the financial market. In this research we apply multiple decision support systems to help investors and traders in making the right decision at the right time. These systems belong to a hybrid approach that takes advantage of both theories of probability and possibility. Since, probability theory is known for its power with learning statistical data, and possibility theory is known for its competences in handling uncertainty and processing any human factor incorporation. Thus, perfectly handles the challenges included in the situation understudy. The main objective of this applied research is studying the effects of multiple Technical indicators fusion on the risk and revenue upon making a trading decision. By that, taking advantage of the Kullback Leibler divergence and Dubois-Prade transformation techniques to provide each indicator with a weight factor that represents its efficiency. The work is completed by an exhaustive and transparent testing, comparison and validation of all the developed systems.