EPJ Data Sci. (2017) 6: 26
https://doi.org/10.1140/epjds/s13688-017-0123-7

Regular article

Novel and topical business news and their impact on stock market activity

¹ National Institute of Informatics, Hitotsubashi, Chiyoda-ku, Tokyo, 101-8430, Japan
² Department of Informatics, SOKENDAI (The Graduate University for Advanced Studies), Hitotsubashi, Chiyoda-ku, Tokyo, 101-8430, Japan
³ PRESTO, Japan Science and Technology Agency, Hitotsubashi, Chiyoda-ku, Tokyo, 101-8430, Japan
⁴ Graduate School of Information Science and Technology, The University of Tokyo, Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan
⁵ Graduate School of Economics, The University of Tokyo, Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan
⁶ The Canon Institute for Global Studies, Marunouchi, Chiyoda-ku, Tokyo, 100-6511, Japan

^* e-mail: mizuno@nii.ac.jp

Received: 10 March 2016
Accepted: 28 September 2017
Published online: 11 October 2017

Abstract

We propose an indicator to measure the degree to which a particular news article is novel, as well as an indicator to measure the degree to which a particular news item attracts attention from investors. The novelty measure is obtained by comparing the extent to which a particular news article is similar to earlier news articles, and an article is regarded as novel if there was no similar article before it. On the other hand, we say a news item receives a lot of attention and thus is highly topical if it is simultaneously reported by many news agencies and read by many investors who receive news from those agencies. The topicality measure for a news item is obtained by counting the number of news articles whose content is similar to an original news article but which are delivered by other news agencies. To check the performance of the indicators, we empirically examine how these indicators are correlated with intraday financial market indicators such as the number of transactions and price volatility. Specifically, we use a dataset consisting of over 90 million business news articles reported in English and a dataset consisting of minute-by-minute stock prices on the New York Stock Exchange and the NASDAQ Stock Market from 2003 to 2014, and show that price volatility, transaction volumes, and the number of transactions exhibited a significant response to a news article when it was novel and topical.