Forecasting financial market indices became a necessary operation for investors’ decisions in order to get the maximum return of investments. The stock market usually has fluctuations and sometimes perturbation due to political, psychological and even environmental factors that may affect market behavior. That results in nonlinear market characteristics with vagueness, incompleteness, and uncertainty of the used information. Therefore the process of predicting stock prices is complex and risky. This work proposes a short-term stock fuzzy decision system using a novel trading strategy based on mixture of technical indicators. Fuzzy logic is applied for both trading rules definition and portfolio management. The selected stock market technical indicators for designing trading rules consist of commonly used indicators and new developed one. That is based on daily candlestick information produces short and long entry signals. The proposed system is tested using the Athens Stock Exchange data. The results are compared to classical non-fuzzy systems in addition to latest fuzzy approaches. The proposals performance produced less losses and better profits. The results demonstrate that the fuzzy logic is promising in portfolio management with steady upward profit and low losses. However, that deserves more study.