N°25-45: Real-Time Climate Controversy Detection

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.