Key Takeaways
- • Deglobalisation identified as most likely structural regime shift: The primary scenario modeling positions deglobalisation—a split into two or more rival economic-technological spheres led by competing great powers—as the baseline forecast absent corrective policy intervention.
- • Four distinct geopolitical-economic futures mapped with differential asset impacts: Analysis frameworks Deglobalisation, Re-Americanisation, De-Americanisation, and Fragmentation each carry materially different consequences for asset returns, inflation dynamics, and portfolio construction strategies.
- • Methodological foundation combines political economy theory with quantitative modeling: Research synthesizes insights from political economist Mark Blyth alongside data science models built by the Oxford-Man Institute and Boston research center to parse economic datasets and detect real-time regime shifts.
- • Portfolio adaptation required for both defensive protection and alpha generation: Investors recognizing the deglobalisation regime shift and executing nimble strategy adjustments can mitigate portfolio risk while potentially identifying new return opportunities within the emerging paradigm.
- • Geopolitical developments including the Iran conflict inform current regime trajectory: Recent geopolitical events year-to-date are explicitly integrated into the analysis framework when assessing near-term positioning implications.
Summary
After one year of research inquiry, a team of political economists, data scientists, and investment strategists has concluded that deglobalisation represents the most structurally probable future for the global order. Rather than a cyclical adjustment or policy-driven aberration, the research treats the apparent retreat from globalization as a fundamental regime transformation—one where the world fragments into two or several competing economic and technological blocs, each anchored to rival great powers. This structural thesis stands in contrast to three alternative futures: a Re-Americanisation scenario centered on U.S. dominance, a De-Americanisation scenario reflecting relative American decline, and a broader Fragmentation scenario of multipolar economic atomization.
The analysis was grounded in an explicitly transdisciplinary methodology. Political economist Professor Mark Blyth provided theoretical and historical anchoring, while researchers at the Oxford-Man Institute and a Boston-based research center constructed quantitative models to extract signal from vast datasets of economic activity and market sentiment. By conceptualizing each era of global political economy as an "operating system" running on institutional "hardware," the framework allows for rigorous comparison of structural breaks and regime transitions. This approach moves beyond anecdotal observations of trade slowdown or supply-chain fragmentation to identify whether deglobalisation constitutes a durable shift in the underlying architecture of international commerce.
Each of the four scenario futures carries distinct implications for portfolio construction. Deglobalisation, as the base case, implies significantly different inflation dynamics, asset correlation patterns, and geographic return drivers compared to alternative regimes. The research explicitly addresses how geopolitical developments—notably recent conflicts including the war in Iran—influence near-term trajectory assessments and positioning decisions. For institutional investors and alternative investment professionals, the regime-shift framework demands a reassessment of traditional diversification assumptions, geographic exposures, and inflation hedges built on pre-deglobalisation conditions.
The central argument is that investors who recognize the structural nature of this transition, adapt their strategic allocations accordingly, and maintain operational flexibility can defend portfolio resilience while identifying new alpha-generation opportunities emerging from the reorganization of global economic relationships. The research translates high-level geopolitical and macroeconomic analysis into actionable scenario plans rather than offering single-point forecasts.
The analysis was grounded in an explicitly transdisciplinary methodology. Political economist Professor Mark Blyth provided theoretical and historical anchoring, while researchers at the Oxford-Man Institute and a Boston-based research center constructed quantitative models to extract signal from vast datasets of economic activity and market sentiment. By conceptualizing each era of global political economy as an "operating system" running on institutional "hardware," the framework allows for rigorous comparison of structural breaks and regime transitions. This approach moves beyond anecdotal observations of trade slowdown or supply-chain fragmentation to identify whether deglobalisation constitutes a durable shift in the underlying architecture of international commerce.
Each of the four scenario futures carries distinct implications for portfolio construction. Deglobalisation, as the base case, implies significantly different inflation dynamics, asset correlation patterns, and geographic return drivers compared to alternative regimes. The research explicitly addresses how geopolitical developments—notably recent conflicts including the war in Iran—influence near-term trajectory assessments and positioning decisions. For institutional investors and alternative investment professionals, the regime-shift framework demands a reassessment of traditional diversification assumptions, geographic exposures, and inflation hedges built on pre-deglobalisation conditions.
The central argument is that investors who recognize the structural nature of this transition, adapt their strategic allocations accordingly, and maintain operational flexibility can defend portfolio resilience while identifying new alpha-generation opportunities emerging from the reorganization of global economic relationships. The research translates high-level geopolitical and macroeconomic analysis into actionable scenario plans rather than offering single-point forecasts.
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