  Stock price prediction is a complicated and interesting task. Noisy trends
make stock pricing sensitive and complicated while the economical motivation
behind, keeps it interesting for researchers and investors. In this paper we
are to outline two novel ideas for stock pricing. We also test each of our
suggested algorithms for predicting the price of 6 stocks from different
sectors. To show the efficiency of our proposed algorithm, we compare the
predicted prices with real values and also perform a backtest to verify that
the annual returns based on real data and predicted price are almost the same.
