Stocks, currencies, and geopolitical shocks: Evidence from advanced and emerging markets

This study investigates how geopolitical risk shapes the relationship between stock and currency markets. We address the limited evidence on their joint dynamics under uncertainty. While prior literature shows that geopolitical risk affects individual financial markets, less is known about its role in the stock–currency interdependence across different economies. Using local Gaussian partial correlations and bootstrap inference for advanced and emerging economies, we analyze nonlinear and asymmetric dependence patterns. Our results show that in advanced economies, stock returns and currency changes are negatively linked, consistent with portfolio balance and flow-oriented theories, whereas emerging markets display positive dependence, reflecting capital flow and risk-based channels. Lead–lag effects reveal that exchange rates dominate in emerging markets, while advanced markets exhibit bidirectional interactions. Under elevated geopolitical risk, dependence strengthens and tail risks become more synchronized, particularly in emerging markets. These findings advance our understanding of cross-market transmission and inform policies on financial stability during geopolitical crises. • The study examines stock–currency market linkages for advanced and emerging economies. • Advanced economies show negative links; emerging markets show positive. • The currency market has a dominant role on lead–lag interactions in emerging economies. • Flight-to-quality effects strengthen in advanced economies under high geopolitical risk. • Geopolitical risk amplifies co-movement and volatility synchronization.

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Publication Details

Journal
Economic Modelling
Published
2025-12-26
DOI
https://doi.org/10.1016/j.econmod.2025.107454
Primary Topic
Financial Risk and Volatility Modeling
Type
article
Field-Weighted Citation Impact
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article

Stocks, currencies, and geopolitical shocks: Evidence from advanced and emerging markets

Georgios Papapanagiotou, Theodore Panagiotidis, Georgios Bampinas, Ioannis Karfakis
Economic Modelling
Financial Risk and Volatility Modeling
article

Stocks, currencies, and geopolitical shocks: Evidence from advanced and emerging markets

Georgios Papapanagiotou, Theodore Panagiotidis, Georgios Bampinas, Ioannis Karfakis
article en

Abstract

This study investigates how geopolitical risk shapes the relationship between stock and currency markets. We address the limited evidence on their joint dynamics under uncertainty. While prior literature shows that geopolitical risk affects individual financial markets, less is known about its role in the stock–currency interdependence across different economies. Using local Gaussian partial correlations and bootstrap inference for advanced and emerging economies, we analyze nonlinear and asymmetric dependence patterns. Our results show that in advanced economies, stock returns and currency changes are negatively linked, consistent with portfolio balance and flow-oriented theories, whereas emerging markets display positive dependence, reflecting capital flow and risk-based channels. Lead–lag effects reveal that exchange rates dominate in emerging markets, while advanced markets exhibit bidirectional interactions. Under elevated geopolitical risk, dependence strengthens and tail risks become more synchronized, particularly in emerging markets. These findings advance our understanding of cross-market transmission and inform policies on financial stability during geopolitical crises. • The study examines stock–currency market linkages for advanced and emerging economies. • Advanced economies show negative links; emerging markets show positive. • The currency market has a dominant role on lead–lag interactions in emerging economies. • Flight-to-quality effects strengthen in advanced economies under high geopolitical risk. • Geopolitical risk amplifies co-movement and volatility synchronization.

Economic ModellingVol. 156
University of Hertfordshire (GB), University of Macedonia (GR)
Openalex Percentile: Top 27%
Financial Risk and Volatility Modeling
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