[1A5-GS-2] Machine learning: stock price prediction

[1A5-GS-2-05] Stock price prediction considering news information

〇Motoki Takenaka ¹, Shoichi Urano¹ (1. Meiji University)

Keywords:Stock price prediction, Machine learning, Natural language processing, Sentiment analysis, BERT

The objective of this study is to develop a highly accurate stock price prediction using news information. The authors have previously reported the construction of a sentiment classifier for news using machine learning to improve the accuracy of news sentiment analysis.In this paper, we propose a stock price prediction model that takes into account the impact of news by classifying news into positive, negative and neutral using the classifier constructed using BERT and incorporating the positive and negative classification results into the stock price data.The effectiveness of the proposed method is compared and verified by simulations, aiming at highly accurate stock price prediction.