Real-Time Climate Controversy Detection

David Jaggi, Markus Leippold and Tingyu Yu
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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

No 25-45, Swiss Finance Institute Research Paper Series from Swiss Finance Institute

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.

Keywords: Climate controversy; corporate greenwashing; natural language processing (search for similar items in EconPapers)
JEL-codes: G14 (search for similar items in EconPapers)
Pages: 40 pages
Date: 2025-04
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Persistent link: https://EconPapers.repec.org/RePEc:chf:rpseri:rp2545

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