This paper proposes a novel trading system which plays the role of an artificial counselor for stock investment. In this paper, the stock future prices (technical features) are predicted using Support Vector Regression from the previous stock prices, average directional index, and parabolic stop and reverse index. Thereafter, the predicted prices are used to recommend which portions of the budget an investor should invest in different existing stocks to have an optimum expected profit considering their level of risk tolerance. Two different methods are used for suggesting best portions, which are Markowitz portfolio theory and fuzzy investment counselor. The first approach is an optimization-based method which considers merely technical features, while the second approach is based on Fuzzy Logic taking into account both technical and fundamental features of the stock market. The utilized dataset in this work is the New York Stock Exchange (NYSE). The experiments are performed on price prediction as well as optimum investment in various well-known stocks for a period of 30 days, and the results show the effectiveness of the proposed system.