Tariffs have been front and center for obvious reasons, putting financial analysts in a challenging spot. They’re dealing with two big narratives that could shape how money moves around the globe and affect returns across asset classes. One narrative says tariffs specifically make the US economy less competitive, causing investors to look elsewhere. The other suggests tariffs hurt global trade broadly, slowing growth everywhere. Neither story is simple, but analysts have practical ways to break down and quantify each.
First, consider the idea that tariffs reduce American competitiveness. Analysts tackling this narrative focus closely on fund flows—where investors move their money when US assets seem less attractive. To figure this out, they look at data on cross-border investment flows from providers like EPFR and ICI, tracking patterns of capital leaving the US for Europe, Asia, or emerging markets. They use econometric models, such as regression analyses or vector autoregressions (VARs), to estimate how tariffs change investors’ preferences over time.
They also keep an eye on currencies, because if investors start shifting money abroad, the dollar could weaken against currencies like the euro or the yen. Analysts combine this currency data with market signals—like relative stock performance or bond yields—to build a clearer picture of how tariffs might redirect capital flows from US markets to foreign ones.
But tariffs don’t only impact America—they also influence the bigger picture of global trade. For analysts exploring this broader narrative, the key is tracking global economic indicators. They regularly monitor global trade volumes, manufacturing activity (using indicators like Purchasing Managers’ Indices), and economic forecasts from institutions like the IMF or OECD. They plug these numbers into large-scale economic models (often called CGE or DSGE models) to project how trade disruptions could affect global growth rates and investment returns worldwide.
Confidence matters, too. Analysts lean on specialized indices such as the Brookings-FT Tiger Index, which blends real economic data, financial market conditions, and consumer and business sentiment. If tariffs are shaking confidence, these indices will clearly reflect that, helping analysts model how nervous consumers and cautious businesses might pull back spending and investment, slowing global economic activity.
Supply chains add another important piece to the puzzle. Companies around the world rely on interconnected trade networks, and tariffs can disrupt these intricate relationships. Analysts use detailed input-output models to track how a disruption in one country (especially a big economy like the US) might ripple outward, affecting manufacturers, exporters, and ultimately, investors everywhere else.
Once analysts have quantified both narratives—US competitiveness versus global slowdown—they combine them in practical scenario analyses. They assign probabilities to each scenario using market-derived signals, like implied volatility, yield curves, or credit spreads. By comparing these scenarios, analysts build detailed expectations about returns in equities, fixed income, currencies, and commodities across regions.
In the end, the analyst’s goal isn’t to pick a side or predict what policymakers might do next. Instead, their job is to clearly map out how these competing stories might unfold, using solid data, quantitative modeling, and careful scenario analysis. This thoughtful, systematic approach is how analysts help investors navigate uncertain times—and tariffs are about as uncertain as it gets.