Some Ideas for Improving Stock Price Prediction Based on Machine Learning

Abstract

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.