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Real-Time Climate Controversy Detection

Author

Listed:
  • David Jaggi

    (Zurich University of Applied Sciences; University of Zurich - Department of Finance)

  • Markus Leippold

    (University of Zurich; Swiss Finance Institute)

  • Tingyu Yu

    (University of Zurich - Department Finance)

Abstract

This study presents ClimateControversyBERT, a novel open-source language model for real-time detection and classification of corporate climate controversies (i.e., brown projects, misinformation, ambiguous actions) from financial news. Validated using RepRisk and Refinitiv metrics, the model effectively identifies inconsistencies between corporate climate commitments and actions as they emerge. We document significant negative market reactions to these controversies: firms experience an immediate average stock price drop of 0.68%, with further declines over subsequent weeks. The impact is intensified by high media visibility and is notably stronger for firms with existing emission reduction commitments, underscoring the market's penalty for perceived environmental failures.

Suggested Citation

  • David Jaggi & Markus Leippold & Tingyu Yu, 2025. "Real-Time Climate Controversy Detection," Swiss Finance Institute Research Paper Series 25-45, Swiss Finance Institute.
    • Handle: RePEc:chf:rpseri:rp2545
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    File URL: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5207850
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    More about this item

    Keywords

    Climate controversy; corporate greenwashing; natural language processing;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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