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

Some Ideas for Improving Stock Price Prediction Based on Machine Learning