[4N3-IS-1b] Knowledge engineering (2/3)

[4N3-IS-1b-05] Machine Reading Comprehension of Stock Price News

〇Seiji Suzuki¹, Tingxuan Li¹, Shuting Bai¹, Gakuto Tsutsumi¹, Takehito Utsuro¹, Yasuhide Kawada² (1. University of Tsukuba, 2. Logworks Co., Ltd.)

キーワード：stock price news, machine reading comprehension, BERT

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 reasons for 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.