The World Meteorological Organization confirmed that 2024 was the warmest year on record, registering global average temperatures exceeding 1.5°C above pre-industrial levels. This increase in temperature averages due to global warming accompanies a rise in temperature variability, which poses a significant risk to human societies. Specifically, extreme climate events are more dependent on changes in the temperature variability than to its average conditions (Katz & Brown, 1992). Despite the rise in variability, research exploring the relationship between temperature phenomena and financial markets is sparse. To shed light on this question, in Bortolan, Dey, and Taschini (2025) we isolate two geographic statistical representations of temperature—changes in the mean and changes in the standard deviation of temperature anomalies. We find that increased temperature variability, rather than average temperature changes, materially impacts returns and profitability for firms located in the US. The predominance of variability over the mean largely stems from its statistical properties in representing changes across the whole temperature distribution, both hot and cold, and capturing well extremes.
Temperature, returns, and firm performance
Our paper begins by empirically analysing the impact of temperature on stock prices. Using a long-short portfolio strategy based on firms’ geographic exposure to temperature metrics, we go long on firms in low-variability states and short those in high-variability states. This strategy yields positive excess returns, averaging 39 basis points per month, adjusted for common risk factors. The returns are primarily driven by the long side, indicating that firms in less temperature variable regions enjoy higher profitability. We observe declines in profitability, measured by return-on-assets, with increased temperature variability across industries, including construction, healthcare, and insurance. For example, high variability causes operational disruptions in construction and higher insurance payouts, whereas the utilities sector benefits from increased electricity demand during temperature extremes. These findings demonstrate how variability in temperature anomalies affect sectors, influencing their returns and profitability. Notably, changes in mean temperature show little correlation with returns or profitability, consistent with Addoum et al. (2020).
Mechanisms
We identify two mechanisms through which temperature variability affects firms: household spending (consumption) and labour productivity (production). Higher temperature variability correlates with decreased aggregate consumer spending across non-durables, durables, and apparel sectors, while increasing utility expenditure such as electricity costs. Additionally, we find that temperature variability hampers labour productivity, most evident in construction and other temperature-sensitive industries where workers face reduced working hours, leading to decreased productivity and operational challenges for firms within these sectors.
Investor attention also rises with increased temperature variability. We use Google Search Volume for “Climate Change” and the Engle et al (2020) Wall Street Journal climate change news index as proxies for investor awareness. We show that temperature variability increases investor and media attention to climate-related topics. Sell-side analysts’ also become aware as earnings calls include more discussions of physical climate risks, correlating with the degree of temperature variability faced by firms. This heightened attention suggests that temperature variability acts as a “wake-up call,” stirring investor behaviour and impacting asset prices.
Practical applications
Firms face pressure to disclose their material exposure to climate risks, while investors need reliable metrics to compare investment exposures, though current disclosures are largely qualitative and hard to use (Christensen et al., 2018). We illustrate through examples that only three simple elements can be used to report exposure, allowing this metric to significantly reduce the complexity of climate risk reporting: (i) a geographic footprint, (ii) projected change in variability for key locations, and (iii) risk threshold identification. Once the regulator defines the risk thresholds (iii), and with projected changes in temperature variability (ii) being largely available from public sources such as climate models and meteorological agencies, firms only need to provide (i) their geographic footprint. This drastically simplifies the reporting burden. In a second exercise, we illustrate how portfolio managers can integrate temperature variability into mean-variance allocation models as a constraint to account for temperature risk without simply excluding regions with higher variability.
Related papers
Our research extends several pioneering financial studies that examine the relationship between weather and firm performance. Addoum et al. (2020) find that firm establishments experience no change in economic activity, i.e., firm-level sales, productivity, and profitability, when they experience above 30°C days. On the other hand, Addoum et al. (2023) show that extreme temperature affects corporate earnings in 40% of industries, with some industries harmed and others benefitting. Analysts often fail to fully anticipate these impacts, leading to earnings surprises in several sectors. Pankratz et al. (2021), on the other hand, find that investors underreact to temperature shocks.
Ponticelli, Xu, and Zeume (2024) find that rising temperatures reduce the number of small manufacturing plants while reallocating labour to larger ones, thereby increasing average plant size by 6% due to greater industrial concentration. Large plants adapt more effectively to climate change by leveraging lower energy prices, enhanced managerial skills, and better access to finance. Somanathan et al. (2021) also note that high temperatures harm productivity and labour supply in Indian manufacturing, causing substantial output declines and increased absenteeism, although climate control offers some mitigation.
We build on their research by shifting focus from absolute temperatures to carefully isolating climate induced weather changes. This focus allows us to capture the exacerbating effects of climate change on temperature and its effects on firms, investor behaviour, consumers, and the labour force. Our research complements these works by introducing a scalable and globally accessible available metric that quantifies temperature variability and demonstrating that this metric has materially relevant consequences for firms and investors.
Conclusion
The significance of this research lies in its contribution to the financial and regulatory landscape surrounding climate risks. The variability metric offers a scalable, standardized approach to measuring firms’ exposure to climate-related risks, improving the quality and comparability of disclosures.