Machine Reading Comprehension of News on Stock Price Changes

Seiji Suzuki, Gakuto Tsutsumi, Takehito Utsuro

Abstract: One of the reasons why stock prices fluctuate greatly is because of IR announcements, which are information for investors, and news reports on events that are closely related to the companies. When a stock price change occurs, news sites for investors may report the stock price change and the reason for the change. However, such articles report only a certain portion of overall events that are closely related to reasons for stock price changes. Thus, in order to provide investors with information on those reasons for stock price changes, it is necessary to develop a system to collect information on events that could be closely related to the stock price changes of certain companies from the Internet. As the first step towards developing such a system, this paper takes an approach of employing a BERT-based machine reading comprehension model, which extracts causes of stock price changes from news reports on stock price changes. Those extracted reasons are intended to be further used to train a system to collect information on events that could be closely related to the stock price changes of certain companies from the Internet.