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<p>We investigate whether changes in temperature anomalies, along with their second, third, and fourth statistical moments, can serve as indicators of physical climate risks and provide valuable insights for forecasting historical stock return volatility in Canada, France, Germany, Italy, Japan, the United Kingdom (UK), and the United States (US) the G7 countries. This analysis controls for factors such as leverage, skewness, and excess kurtosis in stock price fluctuations. Using extensive monthly data spanning from 1915 to 2024 for Canada and Italy, from 1898 to 2024 for France, from 1870 to 2024 for Germany, from 1914 to 2024 for Japan, from 1693 to 2024 for the UK, and from 1791 to 2024 for the US, our findings indicate that the moments of stock markets play a more significant role than climate risks in accurately forecasting stock return volatility. Further analysis confirms that the impacts of climate risks are already reflected in the statistical moments of stock returns. We discuss the implications of these findings for investment decisions and economic policy, suggesting that investors and policymakers in the G7 countries should focus more on statistical moments rather than physical climate risks when producing forecasts of stock market volatility for their decision-making processes.</p>

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Forecasting the volatility of stock returns in the G7 countries over centuries: the role of climate risks

  • 期刊论文

  • 发表日期：

    2026年1月26日

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  • Elie Bouri,
  • Rangan Gupta,
  • Asingamaanda Liphadzi,
  • Christian Pierdzioch

摘要

We investigate whether changes in temperature anomalies, along with their second, third, and fourth statistical moments, can serve as indicators of physical climate risks and provide valuable insights for forecasting historical stock return volatility in Canada, France, Germany, Italy, Japan, the United Kingdom (UK), and the United States (US) the G7 countries. This analysis controls for factors such as leverage, skewness, and excess kurtosis in stock price fluctuations. Using extensive monthly data spanning from 1915 to 2024 for Canada and Italy, from 1898 to 2024 for France, from 1870 to 2024 for Germany, from 1914 to 2024 for Japan, from 1693 to 2024 for the UK, and from 1791 to 2024 for the US, our findings indicate that the moments of stock markets play a more significant role than climate risks in accurately forecasting stock return volatility. Further analysis confirms that the impacts of climate risks are already reflected in the statistical moments of stock returns. We discuss the implications of these findings for investment decisions and economic policy, suggesting that investors and policymakers in the G7 countries should focus more on statistical moments rather than physical climate risks when producing forecasts of stock market volatility for their decision-making processes.