Applying Transfer Learning in Stock Prediction Based on Financial News

摘要

The most derived method and realistic way to predict the current stock price is via media resource and trusted new. In this paper, we will apply the current classifier text technique (Based LSTM) and pre-trained model from transfer learning to gain more intuition in financial news and precisely predict stock price. Finally, after using the latest pre-trained word embedding and a classification layer. We have achieved the robust success, and the experiment result shows that our method is able to outperform in accuracy than the previous one and have some advantage in the adaptive dataset.