The goal of any trader is to buy low and sell high, and thus make maximum revenue with minimum risk of loss. In the financial market, prices change on daily bases, leaving traders with confusion about what decision to take, hold, buy, or sell, and when to take it. Many market analysis techniques were introduced to help traders take a winning decision at the right time, one of which was technical analysis. Technical analysis uses indicators to forecast trend and price movements. Therefore this analysis technique 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. In this study, three decision support systems based on a hybrid probabilistic- possibilistic general approach, are proposed and tested on historical prices of the EuroStoXX50, and the CAC40 indices. The following systems take advantage of the statistical claims of probability on historical data, the interpretability and uncertainty handling competences of possibility theory, and the foreseeing abilities of technical indicators, all merged together to arm traders with a reliable daily decision that assures risk-discounted revenue, with a contribution of efficiently taking advantage of multiple indicators. © 2014 Lavoisier.
