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This study constructs a climate risk attention indicator for Chinese funds by applying Word2Vec-based text analysis to annual fund reports. This study examines how climate risk attention affects excess returns in actively managed funds, using the Brinson model for performance decomposition. The results show that climate risk attention increases fund excess returns with notable heterogeneity: a 1% increase in acute physical risk attention raises excess returns by 24.675%, whereas the same increase in transition risk attention leads to a much smaller effect—only 2.746%, approximately 11% of the acute risk impact. Chronic physical risks, such as rising temperatures, do not significantly affect returns. These findings underscore the importance for fund managers to prioritize acute and transition risks, particularly acute physical risks, in climate-related investment strategies. This study extends the empirical experience in Chinese climate finance, validates a machine-learning-constructed climate risk dictionary, and provides practical insights for fund managers and regulators. A limitation is the reliance on annual reports, which may not capture real frequency shifts in risk attention.
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Yang et al. (2026) studied this question.
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