Improvement of Prediction Accuracy in Predicting Market Trends by Newspaper Article Analysis Using Deep Learning

Abstract

In this paper, we analyze newspaper articles using deep learning to forecast market trends. We have proposed a method to forecast market trends based on time-series text analysis using deep learning. This method works very well for forecasting TOPIX from The Nikkei (Nihon Keizai Shinbun) between 2008 and 2014, but the prediction accuracy falls after 2015. In this paper, we propose to reduce the duration of the training data in order to improve the prediction accuracy after 2015. As a result of the period of training data over the past three years, the prediction accuracy has been improved by 12.2%, from 55.1% to 67.3%.