The goal of any trader is to buy low and sell high, and thus make maximum revenue with minimum risk of loss. Daily price changes in the financial markets leaves traders with confusion about what decision to make, hold, buy, or sell, and when to make it. Many market analysis techniques were introduced to help traders make a winning decision at the right time, one of which was technical analysis. Technical analysis uses indicators to forecast trend and price movements, hence aids traders with the decision making process. This analysis technique has shown great success, which made it the resort of most financial traders. However, the efficiency of this type of analysis is affected by many factors, putting into it a great deal of uncertainty, ambiguity and vagueness. This paper, introduces multiple probability-possibility decision support systems that studies the effect of multiple indicators fusion on the risk and revenue upon making a trading decision. The following systems make advantage of the statistical claims of probability on historical data, the interpretation and uncertainty handling competences of possibility theory, the foreseeing abilities of technical indicators, and the dependence measuring of mutual information, all merged together to arm traders with a reliable daily decision that assures risk-discounted revenue.