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Highlighting the Role of Morality in News Framing and Its Short-Term Effects on Stock Market Fluctuations

Author

Listed:
  • Paula T. Wang

    (Media Neuroscience Lab, Department of Communication, University of California Santa Barbara, Santa Barbara, CA 93106, USA)

  • Musa Malik

    (Media Neuroscience Lab, Department of Communication, University of California Santa Barbara, Santa Barbara, CA 93106, USA)

  • René Weber

    (Media Neuroscience Lab, Department of Communication, University of California Santa Barbara, Santa Barbara, CA 93106, USA
    Department of Psychological and Brain Sciences, University of California Santa Barbara, Santa Barbara, CA 93106, USA
    Division of Communication and Media, Ewha Woman’s University, Seoul 03760, Republic of Korea)

Abstract

The Model of Intuitive Morality and Exemplars (MIME) suggests that news audiences, including investors, evaluate news based on their moral frames, and that these moral evaluations shape behavior. We extracted moral signals from 382,185 news articles across an 8-month period and examined their predictive effect on stock market movement. Results indicate that morality is a strong predictor during low economic periods and is driven by subversion and sanctity. Overall, our study suggests that moral framing and its foundations are important considerations for research on news effects, especially during periods of economic instability. The study provides an additional theoretical perspective on stock market fluctuations as well as practical implications for stakeholders with an interest in dampening collective panics and stabilizing investor sentiment.

Suggested Citation

  • Paula T. Wang & Musa Malik & René Weber, 2025. "Highlighting the Role of Morality in News Framing and Its Short-Term Effects on Stock Market Fluctuations," IJFS, MDPI, vol. 13(2), pages 1-19, June.
    • Handle: RePEc:gam:jijfss:v:13:y:2025:i:2:p:107-:d:1674580
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    References listed on IDEAS

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    5. Nyman, Rickard & Kapadia, Sujit & Tuckett, David, 2021. "News and narratives in financial systems: Exploiting big data for systemic risk assessment," Journal of Economic Dynamics and Control, Elsevier, vol. 127(C).
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