Relationship Between Japanese Stock Market Behavior and Category-Based News

Jun Nakayama () and Daisuke Yokouchi
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Jun Nakayama: Financial Strategy Program, Hitotsubashi University Business School, Tokyo 101-8439, Japan
Daisuke Yokouchi: Financial Strategy Program, Hitotsubashi University Business School, Tokyo 101-8439, Japan

Risks, 2025, vol. 13, issue 3, 1-29

Abstract: This study investigates the relationship between news delivered via the QUICK terminal and stock market behavior. Specifically, through an evaluation of the performance of investment strategies that utilize news index created based on its scores indicating positive or negative sentiment, we examine whether index construction that takes into account the content of individual news items contributes to improved predictive power with regard to stock prices. We verify the performance of this investment strategy based on signal indicators derived from news indices focusing on short-term trends using time-series decomposition. After refining the news indicators based on news categories, we observe an improvement in the strategy’s performance, demonstrating that the value of news varies across different categories and the importance of considering the content and meaning of text news.

Keywords: news; text mining; time-series decomposition; investment strategy (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2025
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