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EU stock market integration: Policy impact and drivers

Jin Suk Park & Mohammad Khaleq Newaz

Economic Systems2025https://doi.org/10.1016/j.ecosys.2025.101338article
AJG 2ABDC B
Weight
0.44

Abstract

This study examines the dynamics of EU stock market integration (ESMI) by disentangling it from global stock market integration (GSMI). Using ESMI’s strength relative to GSMI, we assess how EU policies, financial crises, and cross-country disparities in economic, business, and market conditions influence integration, employing both machine learning and econometric models. The results indicate that ESMI is predominantly influenced by GSMI. Among potential drivers, differences in expected corporate performance across EU member states, i.e., expectation disparity, are the most significant. In contrast, EU-level policies exhibit no or only short-lived effects. Brexit and the COVID-19 pandemic appear to increase ESMI through synchronized market reactions. These findings suggest that EU financial integration is heavily shaped by global forces and internal asymmetries, thereby raising questions about the long-term effectiveness of EU integration policies. • EU stock market integration is primarily driven by global forces. • Relative EU integration trends differ from earlier studies. • EU policy effects on integration are weak or short-lived. • Investors’ expectation disparity is the strongest driver of integration. • Brexit and COVID-19 increased integration.

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https://doi.org/https://doi.org/10.1016/j.ecosys.2025.101338

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@article{jin2025,
  title        = {{EU stock market integration: Policy impact and drivers}},
  author       = {Jin Suk Park & Mohammad Khaleq Newaz},
  journal      = {Economic Systems},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1016/j.ecosys.2025.101338},
}

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Evidence weight

0.44

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.32 × 0.4 = 0.13
M · momentum0.57 × 0.15 = 0.09
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.