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Investment with New Sentiment Analysis in Japanese Stock Market: Expert Knowledge Can Still Outperform ChatGPT

Author

Listed:
  • Zhenwei Lin

    (Graduate School of Economics, The University of Tokyo)

  • Masafumi Nakano

    (GCI Asset Management)

  • Akihiko Takahashi

    (Faculty of Economics, The University of Tokyo)

Abstract

This paper presents a novel approach to sentiment analysis in the context of invest- ments in the Japanese stock market. Speci cally, we begin by creating an original set of keywords derived from news headlines sourced from a Japanese nancial news plat- form. Subsequently, we develop new polarity scores for these keywords, based on market returns, to construct sentiment lexicons. These lexicons are then utilized to guide invest- ment decisions regarding the stocks of companies included in either the TOPIX 500 or the Nikkei 225, which are Japan's representative stock indices. Furthermore, empirical studies validate the effectiveness of our proposed method, which signi cantly outperforms a ChatGPT-based sentiment analysis approach. This provides strong evidence for the ad- vantage of integrating market data into textual sentiment evaluation to enhance nancial investment strategies.

Suggested Citation

  • Zhenwei Lin & Masafumi Nakano & Akihiko Takahashi, 2025. "Investment with New Sentiment Analysis in Japanese Stock Market: Expert Knowledge Can Still Outperform ChatGPT," CIRJE F-Series CIRJE-F-1248, CIRJE, Faculty of Economics, University of Tokyo.
    • Handle: RePEc:tky:fseres:2025cf1248
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    References listed on IDEAS

    as
    1. Souta Nakatani & Kiyohiko G. Nishimura & Taiga Saito & Akihiko Takahashi, 2020. "Interest Rate Model with Investor Attitude and Text Mining," CIRJE F-Series CIRJE-F-1152, CIRJE, Faculty of Economics, University of Tokyo.
    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.
    3. Huck, Nicolas, 2010. "Pairs trading and outranking: The multi-step-ahead forecasting case," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1702-1716, December.
    4. Masafumi Nakano & Akihiko Takahashi, 2020. "A new investment method with AutoEncoder: Applications to crypto currencies(Forthcoming in "Expert Systems with Applications")," CARF F-Series CARF-F-489, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    5. Souta Nakatani & Kiyohiko G. Nishimura & Taiga Saito & Akihiko Takahashi, 2020. "Interest Rate Model with Investor Attitude and Text Mining (Published in IEEE Access)," CARF F-Series CARF-F-479, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
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