The Application of Machine Learning Algorithms in Stock Prediction

Abstract

With the development of science and technology, people pay more attention to predicting the price of stock by using different kinds of machine learning algorithms. Some algorithms have been used to forecast the direction of the stock prices and researchers have already got some achievements. In this thesis, we compare three distinct machine learning algorithms. Through the results of different experiments, feed-forward neural network model can reach a higher performance among the three models. The accuracy of prediction is more than 90% from this model. But it does not mean it’s the best model among these three models. Because of the characteristics of the stock market, the other two models also can get a good performance in sometime. Combining with more algorithms to forecast is what we need to do in the future.