Two structural forces are colliding, geoeconomics – the use of economic means to gain leverage in international disputes - and technology, creating a financial market environment ripe for turbulence.

The shift from a unipolar to a multipolar world is making global politics more contested and crisis prone, with major powers increasingly weaponizing trade, capital flows, and supply chains. In parallel, artificial intelligence (AI) is making data, talent, computing power, and adoption capacity the key source of competitive advantage.

Here, we examine which currencies are fragile and which are “antifragile” in the face of these twin forces. In our framework, currency winners and losers depend on a country’s commodity leverage, global supply-chain dependency, AI preparedness, and external vulnerability.

Commodity leverage

We believe countries that control strategic commodities linked to energy, defense spending, and AI infrastructure are better positioned to benefit. Combining a country’s copper and aluminum exposure with its net energy balance (crude oil and natural gas production less consumption) is a straightforward way to gauge a country’s commodity leverage.

Copper provides the backbone of the AI boom because it powers the electricity infrastructure that makes large scale computing possible. Aluminum tops the list of NATO’s critical raw materials because it helps produce lightweight yet robust military aircraft and missiles.

Chart 1 shows commodity leverage is highest in Canada, Australia, and Brazil. The countries with the lowest commodity leverage are China, the Eurozone, Japan, and South Korea

Commodity Leverage

Supply chain dependency

Countries that are less integrated into the global value chain and which have a domestic demand driven economy are less vulnerable to supply shocks. We assess a country’s supply chain dependency through the lens of foreign value-added (FVA) trade and the share of household spending to the economy. FVA in gross exports reflects the portion of a country’s exports that is made up of imported intermediate inputs.

A high FVA in gross exports and low household spending to GDP mix signal an economy deeply embedded in the global supply chain, while a low FVA in gross export and a high household spending to GDP mix point to an economy less integrated into the global supply chain. 

Chart 2 shows the US with the lowest global supply chain dependency. Supply chain dependency is notably highest in Singapore, Vietnam, Hungary, and Czechia.

Supply Chain Dependency

AI preparedness

A country’s ability to benefit from the AI revolution depends on its ability to deploy, absorb, and scale the technology across the economy. That can be captured in large part by a country’s digital infrastructure and human capital. The IMF quantifies digital infrastructure by a country’s internet connectivity and e-commerce infrastructure. The IMF’s human capital pillar reflects education and digital skills and labor market flexibility.

Chart 3 shows that South Africa lags far behind some other countries in AI adoption readiness. In contrast, Singapore, New Zealand, US, Sweden, Australia, and the UK have relatively high AI adoption readiness

AI preparedness

External vulnerability

Countries with limited reliance on external financing with an undervalued exchange rate are generally more resilient to external shocks and less vulnerable to abrupt capital flow reversals. We assess a country’s external vulnerability via its basic balance (current account balance plus net foreign direct investment) and real effective exchange rate deviation from trend.

A basic balance surplus alongside an undervalued exchange rate signals low external vulnerability. In contrast, a basic balance deficit alongside an overvalued exchange rate signals high external vulnerability.

Chart 4 shows external vulnerability is lowest in China, South Korea, Indonesia, Japan, and Norway while highest in Romania.

External vulnerability

Bottom line

No single currency emerges as a clear winner or loser across all four lenses. But to better distinguish between currencies, we derive a ranking of the four factors using a simple scorecard (chart 5): currencies receive +1 when a factor is a tailwind, -1 when it is a headwind, and +0.5 for mixed exposure.

On balance, the Australian Dollar (AUD) stands out as the most antifragile currency, supported by strong commodity leverage and AI preparedness. In emerging markets, the Brazilian Real (BRL) is the most antifragile currency underpinned by strong commodity leverage, and limited supply chain and external vulnerabilities. Conversely, the Euro (EUR) and Turkish Lira (TRY) are the most fragile currencies reflecting their countries’ low commodity leverage, high supply chain dependency, and relatively low AI preparedness.

Scorecard

With special contributions from Sean Speegle and Leo Ellenberg.