Research

The Pricing of Geopolitical Tensions over a Century

Andrei S. Gonçalves, Alessandro Melone, Andrea Ricciardi

News article: "Exploring a century of global conflicts and their impact on financial assets"

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Executive Summary

This study explores the role of geopolitical tensions in asset pricing over the past century. The authors propose a novel decomposition of geopolitical risk into two distinct components: Geopolitical Threats (GPT), which represent forward-looking concerns about potential adverse geopolitical events, and Geopolitical Acts (GPA), which capture the actual realization of such events, such as the outbreak of wars. Drawing on the Caldara and Iacoviello (2022) geopolitical risk index, the paper constructs and analyzes these components to investigate their distinct effects on financial markets and economic outcomes.

The analysis reveals that GPT, not GPA, plays a central role in shaping investors’ perception of risk. GPT rises prior to major geopolitical conflicts, reflecting investor fear and anticipation, while GPA merely reacts to realized shocks. Unlike GPA, GPT is consistently priced in asset markets. It correlates with institutional risk perceptions, predicts long-term consumption disasters, and explains both cross-sectional and time-series variation in expected returns. These features are particularly salient for long-term investors with Epstein-Zin preferences, who are sensitive to low-probability, high-impact events.

The empirical scope of the paper spans a wide range of asset classes, including U.S. equities, equity anomalies, and global stock and bond portfolios. Portfolios with high exposure to GPT earn significantly higher risk premia, with estimates as high as 4.17% per annum in U.S. equities. These premia are robust to the inclusion of standard asset pricing factors, including the CAPM, ICAPM, Fama-French factors and q-factors, and remain strong after controlling for other measures of uncertainty, such as economic and trade policy uncertainty, expected market volatility and war discourse.

In the time series, GPT significantly predicts equity risk premia over 3- and 5-year horizons, emphasizing its relevance for long-horizon asset allocation. The predictability is particularly strong during periods of heightened geopolitical attention, proxied by lagged levels of geopolitical risk. The evidence that GPT forecasts bond risk premia is limited.

The paper also documents real economic effects of geopolitical threats. Increases in GPT are followed by significant declines in corporate investment, likely reflecting a perceived increase in investment risk and political instability. No similar pattern is observed in response to GPA.

These findings carry important implications for both researchers and policymakers. From an academic perspective, the results underscore the need for asset pricing models to distinguish between anticipatory threats and realized events, as only the former appear to carry systematic risk. For practitioners and policymakers, monitoring forward-looking measures such as GPT can offer valuable insights into market vulnerability during periods of geopolitical stress and may inform both investment strategies and macroeconomic policy decisions.

Research completed by Dennis Hirsch and Aravind Chandrasekaran. The Final Report in the Business Data Ethics project examines: The threats that corporate use of advanced analytics creates for individuals and the broader society (Part III); What “data ethics” means to the companies that practice it (Part IV); Why companies pursue data ethics when the law does not require them to do so (Part V); The substantive principles that companies use to draw the line between ethical and unethical uses of advanced analytics (Part VI); The management processes (Part VII) and technologies (Part VIII) that companies use to achieve these substantive goals; and Corporate projects that use advanced analytics for the social good (Part IX).

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