Abstract
In this study, we proposed a new text-mining methods for long-term market analysis. Using our method, we analyzed monthly price data of financial markets; Japanese government bond market, Japanese stock market, and the yen-dollar market. First we extracted feature vectors from monthly reports of Bank of Japan. Then, trends of each market were estimated by regression analysis using the feature vectors. As a result, determination coefficients were over 75%, and market trends were explained well by the information that was extracted from textual data. We compared the predictive power of our method among the markets. As a result, the method could estimate JGB market best and the stock market is the second.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
