Extraction of Factors and Related Stocks of Individual Stocks Using Multiple Textual Dat Data

Abstract

In this study, we proposed a new method for extracting factors and related stocks which affect individual stocks. We combined t wo text text-mining methods which are CPR method for news articles and TF-IDF for summary of financial statements statements. We showed how stocks are connected through factors in each terms.