IDEAS home Printed from https://ideas.repec.org/a/gam/jrisks/v13y2025i3p50-d1607495.html
   My bibliography  Save this article

Relationship Between Japanese Stock Market Behavior and Category-Based News

Author

Listed:
  • Jun Nakayama

    (Financial Strategy Program, Hitotsubashi University Business School, Tokyo 101-8439, Japan
    Sumitomo Mitsui Banking Corporation, Tokyo 100-0005, Japan)

  • Daisuke Yokouchi

    (Financial Strategy Program, Hitotsubashi University Business School, Tokyo 101-8439, Japan)

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.

Suggested Citation

  • Jun Nakayama & Daisuke Yokouchi, 2025. "Relationship Between Japanese Stock Market Behavior and Category-Based News," Risks, MDPI, vol. 13(3), pages 1-29, March.
  • Handle: RePEc:gam:jrisks:v:13:y:2025:i:3:p:50-:d:1607495
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-9091/13/3/50/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-9091/13/3/50/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Leland Bybee & Bryan Kelly & Yinan Su & Tarun Ramadorai, 2023. "Narrative Asset Pricing: Interpretable Systematic Risk Factors from News Text," The Review of Financial Studies, Society for Financial Studies, vol. 36(12), pages 4759-4787.
    2. Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Linying Lv, 2025. "Do Sell-side Analyst Reports Have Investment Value?," Papers 2502.20489, arXiv.org, revised Mar 2025.
    2. Jesús Villota, 2025. "Predicting Market Reactions to News: An LLM-Based Approach Using Spanish Business Articles," Working Papers wp2025_2501, CEMFI.
    3. Jian Chen & Guohao Tang & Guofu Zhou & Wu Zhu, 2025. "ChatGPT and Deepseek: Can They Predict the Stock Market and Macroeconomy?," Papers 2502.10008, arXiv.org.
    4. Müller, Karsten, 2020. "German forecasters' narratives: How informative are German business cycle forecast reports?," Working Papers 23, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    5. Goedde-Menke, Michael & Langer, Thomas & Pfingsten, Andreas, 2014. "Impact of the financial crisis on bank run risk – Danger of the days after," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 522-533.
    6. David E. Allen & Michael McAleer & Abhay K. Singh, 2019. "Daily market news sentiment and stock prices," Applied Economics, Taylor & Francis Journals, vol. 51(30), pages 3212-3235, June.
    7. Yan Luo & Linying Zhou, 2020. "Textual tone in corporate financial disclosures: a survey of the literature," International Journal of Disclosure and Governance, Palgrave Macmillan, vol. 17(2), pages 101-110, September.
    8. Jiao Ji & Oleksandr Talavera & Shuxing Yin, 2018. "The Hidden Information Content: Evidence from the Tone of Independent Director Reports," Working Papers 2018-28, Swansea University, School of Management.
    9. Lixiang Wang & Wendi Hou & Yupei Liu, 2023. "How do co‐shareholding networks affect negative media coverage? Evidence from China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(4), pages 4221-4249, December.
    10. Kamaladdin Fataliyev & Aneesh Chivukula & Mukesh Prasad & Wei Liu, 2021. "Stock Market Analysis with Text Data: A Review," Papers 2106.12985, arXiv.org, revised Jul 2021.
    11. Bennani, Hamza, 2018. "Media coverage and ECB policy-making: Evidence from an augmented Taylor rule," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 26-38.
    12. Christopher N. Avery & Judith A. Chevalier & Richard J. Zeckhauser, 2016. "The "CAPS" Prediction System and Stock Market Returns," Review of Finance, European Finance Association, vol. 20(4), pages 1363-1381.
    13. Rui Liu & Jiayou Liang & Haolong Chen & Yujia Hu, 2024. "Analyst Reports and Stock Performance: Evidence from the Chinese Market," Papers 2411.08726, arXiv.org, revised Mar 2025.
    14. Keval Amin & Erica Harris, 2022. "The Effect of Investor Sentiment on Nonprofit Donations," Journal of Business Ethics, Springer, vol. 175(2), pages 427-450, January.
    15. Femg, Xunan & Johansson, Anders C., 2019. "News or Noise? The Information Content of Social Media in China," Stockholm School of Economics Asia Working Paper Series 2019-52, Stockholm School of Economics, Stockholm China Economic Research Institute.
    16. King, Timothy & Srivastav, Abhishek & Williams, Jonathan, 2016. "What's in an education? Implications of CEO education for bank performance," Journal of Corporate Finance, Elsevier, vol. 37(C), pages 287-308.
    17. Kirtac, Kemal & Germano, Guido, 2024. "Sentiment trading with large language models," Finance Research Letters, Elsevier, vol. 62(PB).
    18. André Betzer & Jan Philipp Harries, 2022. "How online discussion board activity affects stock trading: the case of GameStop," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 36(4), pages 443-472, December.
    19. Bouyaddou, Youssef & Jebabli, Ikram, 2025. "Integration of investor behavioral perspective and climate change in reinforcement learning for portfolio optimization," Research in International Business and Finance, Elsevier, vol. 73(PB).
    20. repec:diw:diwwpp:dp1393 is not listed on IDEAS
    21. Sapkota, Niranjan, 2022. "News-based sentiment and bitcoin volatility," International Review of Financial Analysis, Elsevier, vol. 82(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jrisks:v:13:y:2025:i:3:p:50-:d:1607495. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.