Trading Tests of Long-Term Market Forecast by Text Mining

We propose a new approach for analyzing the Japanese government bond (JGB) market using text-mining technology. First, we extracted the feature vectors of the monthly reports from the Bank of Japan (BOJ). Then, the trends in the JGB market were estimated by a regression analysis using the feature vectors. As a result of comparison with support vector regression and other methods, the proposal method could forecast in higher accuracy about both the level and direction of long-term market trends. Moreover, our method showed high returns with annual rate averages as a result of the implementation test.