Generation Support of Financial Reports by Textmining

Abstract

Recently, with the increase of individual investors, the necessity of investment support technologies is increasing. Although analyst reports on which professional securities analysts forecast business performances or stock prices of companies are regarded as important investment decision materials, writing an analyst report is heavy burden. In this research, we summarize newspaper articles and support the generation of analyst reports by using knowledge of information features which are referred to as reasons for analysts' forecasts of business performances or stock prices in analyst reports.