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<p>This study examines the relation between investor climate sentiment and firm-level downside risk in the Chinese stock market, with particular attention to the timing of sentiment formation and firms’ exposure to the low-carbon transition. Using 52.3&#xa0;million Eastmoney Forum comments for CSI 300 firms from 2016 to 2025, we construct a firm-day measure of climate sentiment through a two-stage deep-learning framework and decompose it into trading hours and non-trading hours components. The results show that climate sentiment is significantly associated with two measures of downside risk, negative conditional skewness and down-to-up volatility, and that this relation is driven primarily by sentiment formed during non-trading hours. Moreover, this relation exhibits substantial cross-sectional heterogeneity: a one-standard-deviation increase in non-trading hours sentiment reduces NCSKEW by 0.020 for clean energy firms, but increases it by 0.017 for carbon-intensive firms. This asymmetry is consistent with the more complete processing of complex climate information outside active market hours, when investors face fewer attention constraints and reduced intraday microstructure noise. Instrumental-variable estimates based on Typhoon In-fa, using exposure-based interactions, provide additional support for the risk-amplifying effect of climate sentiment for carbon-intensive firms. Additional analyses show that ownership type further shapes the relation between climate sentiment and downside risk. Overall, these findings provide new empirical evidence consistent with an information-processing perspective on how climate-related discourse enters tail-risk pricing.</p>

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Short-term investor climate sentiment and stock markets

  • 期刊论文

  • 发表日期：

    2026年6月1日

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  • Zhiyi Wang,
  • Guangjin Yu

摘要

This study examines the relation between investor climate sentiment and firm-level downside risk in the Chinese stock market, with particular attention to the timing of sentiment formation and firms’ exposure to the low-carbon transition. Using 52.3 million Eastmoney Forum comments for CSI 300 firms from 2016 to 2025, we construct a firm-day measure of climate sentiment through a two-stage deep-learning framework and decompose it into trading hours and non-trading hours components. The results show that climate sentiment is significantly associated with two measures of downside risk, negative conditional skewness and down-to-up volatility, and that this relation is driven primarily by sentiment formed during non-trading hours. Moreover, this relation exhibits substantial cross-sectional heterogeneity: a one-standard-deviation increase in non-trading hours sentiment reduces NCSKEW by 0.020 for clean energy firms, but increases it by 0.017 for carbon-intensive firms. This asymmetry is consistent with the more complete processing of complex climate information outside active market hours, when investors face fewer attention constraints and reduced intraday microstructure noise. Instrumental-variable estimates based on Typhoon In-fa, using exposure-based interactions, provide additional support for the risk-amplifying effect of climate sentiment for carbon-intensive firms. Additional analyses show that ownership type further shapes the relation between climate sentiment and downside risk. Overall, these findings provide new empirical evidence consistent with an information-processing perspective on how climate-related discourse enters tail-risk pricing.