Modeling the impact of tariffs on the global stock market

This article was written by Jose Menchero and Tizian Otto, Portfolio and Analytics Research at Bloomberg. 

Since returning to office, President Trump has promised to utilize tariffs as a tool to remake the global economy. His stated goals were to reduce trade imbalances, restore “fairness” in trade, and ultimately bring manufacturing jobs back into the United States.

On April 2, 2025, referred to by administration officials as “Liberation Day,” the US government unveiled its new tariff policy. It is based on two components: (1) A universal import tariff (a baseline 10% tariff on all imported goods), and (2) reciprocal tariffs (additional tariffs tailored to match the duties that other countries impose on US products, affecting imports from 90 nations).

These American tariffs prompted vows of retaliation from America’s leading trading partners, including China, Canada, the EU, and the UK. Global financial markets reacted swiftly: Prices tumbled, volatility spiked, and the specter of a global financial meltdown loomed large.

Just days later, in an attempt to stabilize financial markets, the US government announced a 90-day suspension of the new tariffs for select countries. Although the announcement was made after European markets had closed, it sparked a powerful rally in US equities, which posted their largest daily gain since the Global Financial Crisis.

In this article, we study the impact of these tariffs on the stock market using both the MAC3 Global Equity Model and the MAC3 US Equity Model. In particular, we analyze which factors have been most adversely impacted, and which factors have benefited. We also employ the factor returns to illustrate the “whipsaw” effect that occurred when the US suddenly paused the tariffs.

Risk model framework

For the analysis that follows, we employ two versions of the MAC3 Risk Model. The Global Equity Model consists of one market factor, 14 style factors, 56 industry factors, and 49 country factors. The US Equity Model consists of one market factor, 14 style factors, and 39 industry factors (and no country factors).

Factor returns are estimated by using cross-sectional regression to create pure factor portfolios, which have unit exposure to the target factor and zero exposure to all other factors. The market factor portfolio is 100% net long and essentially represents the cap-weighted market portfolio. All other pure factor portfolios are strictly dollar neutral. Style factors represent important sources of risk and return that are related to characteristics of the stock (e.g., momentum, size, etc.). The associated pure factor portfolios have unit exposure to the target style, zero exposures to all other styles, and have zero return contribution from industries and countries. Country pure factor portfolios are long a portfolio with unit exposure to the country, are short an equal dollar amount of the market, and have zero exposure to every style factor and zero return contribution from industries. In other words, country pure factor portfolios explain the return of the country net of the market and net of styles and industries. Similarly, industry pure factor portfolios explain the return of the industry net of the market, styles, and countries.

Factor return movements

We begin by analyzing the tariff-induced stock market meltdown from the start of 02-Apr-2025 to the end of 08-Apr-2025 (five trading days) through the lens of the MAC3 Global Equity Model. We standardize factor returns into z-scores by taking the cumulative five-day returns and dividing them by the one-week volatility forecast.

In Figure 1, we report the z-scores over this period for three different factor groups (market/style factors, industry factors, and country factors). Note that we retrieve factor volatility forecasts from the diagonal entries of the estimated factor covariance matrix. Those numbers represent volatility estimates for the true underlying factors and do not include the idiosyncratic risk component required to forecast volatility of the pure factor portfolios. For well diversified pure factor portfolios with strong underlying factors, the effects on z-scores are rather small and the findings in both cases are qualitatively similar. The bar charts illustrate the stock market reactions in the aftermath of “Liberation Day.” The GL Market factor shows a z-score of -6.17, indicating a massive negative return shock across the stock markets around the globe. The market-related factors such as Residual Volatility and Beta were also hit hard. This makes sense, since high-beta stocks and high-volatility stocks tend to underperform in sharp market downturns. On the positive side, we see that the return to the Profit factor was strongly positive, reflecting a classic “flight-to-quality” commonly observed during crisis periods.

At the industry level, we see that the hardest-hit factors were Consumer Electronics, Oil Exploration & Production, and Electronic Components. Given the massive concentration of consumer electronics manufactured in China, it is natural that firms in these industries would be hard hit by the threat of tariffs. Similarly, given the fear of a global economic recession induced by the tariffs, it is not surprising that firms in the Energy sector would also underperform. The top-performing industries were in the Consumer Staples and Health Care sectors. Given the domestic nature of these industries, it is no surprise that these industries would outperform in a market threatened by tariffs. Interestingly, the US country factor was the worst-performing country, with a z-score of -3.17.

Since the 90-day tariff suspension was announced after European markets had closed, analyzing the impact of the pause using the 09-Apr-2025 factor returns from the MAC3 Global Equity Model would be misleading. Instead, we analyze the effect of this announcement using the MAC3 US Equity Model. In this case, we convert the 09-Apr-2025 factor returns into z-scores by dividing them with the one-day predicted volatility at the start of 09-Apr-2025. In Figure 2, we plot the respective z-scores for style and industry factor groups.

For the style factors, what stand out are the large positive returns to the Market factor and the Beta factor. For the industry factors, we see that Banks and Specialty Finance had the worst performance, while Airlines and Semiconductors performed best.

Conclusion

Recent shifts in US tariff policies have renewed global trade tensions, sending tariff-induced shockwaves through international financial markets. As detailed in the analysis using our MAC3 Equity Models, the market reactions following “Liberation Day” illustrate the extent to which geopolitical uncertainty and anticipated trade disruptions influence investor confidence. The sharp decline and subsequent rebound across global equity markets (along with distinct return patterns at the style, industry, and country levels) underscores the far-reaching implications of this new phase in international trade. With market volatility elevated, these developments signal a pivotal moment for global economic dynamics and highlight the importance of analyzing the equity markets through the lens of a robust multi-factor model.