Stock market trend prediction with sentiment analysis based on LSTM neural network

This paper aims to analyze influencing factors of stock market trend prediction and propose an innovative neural network approach to achieve stock market trend prediction. With the breakthrough of deep learning recently, there occurred lots of useful techniques for stock trend prediction. This thesis aims to propose a method of feature selection for selecting useful stock indexes and proposes deep learning model to do sentiment analysis of financial news as another influencing factor influencing stock trend. Then it proposes accurate stock trend prediction method using LSTM (Long Short-term Memory). Index: Stock trend prediction, LSTM, Sentiment Analysis, Deep learning, Chinese Stock market, Feature Selection...