Figure 1: 4-day S&P500 returns
Panel A: 4-day
S&P500 returns distribution
Panel B: Industry-level 4-day
return distribution
This figure reports two panels. Panel A depicts the frequency of demeaned 4-day cumulative returns from all publicly listed firms during the weeks of March 26th to April 1st, 2025, and April 2nd - April 8th, 2025. It shows that the dispersion of returns during April 2nd - April 8th, 2025, is larger than the previous 4 days March 26th to April 1st, 2025, making the case that it is possible to discriminate about the impact of trade policies on firms. Panel B reports the cumulative returns over the business days 3-8 of April 2025 for each one of the 49 industries defined by Fama and French. For each industry, we report the number of stocks used, and the average (dots) and 95 percentile (bars) returns across these stocks. The dash line represents the median return across industries in each panel. Industries with post April 2 returns below the median are in red, while industries above the median are in green. In black, we report Colors identify the cumulative 4-day returns over the four business days up to (and including) April 2, 2025, for each one of the 49 industries defined by Fama-French. The right panel reports the cumulative returns over the business days 3-8 of April 2025 for the same 49 industries. The dash line represents the median return across industries in subperiod. This second panel shows that also in the same industry there is a much larger variation in stock prices. Together, the patterns in these two figures illustrate how trading days dominated by unexpected changes in foreign trade policy provide a quasi-natural experiment for identifying firms' and industries' differential exposure to disruptions in foreign trade. Sources include CRSP from WRDS.
Figure 2: Trade-Sensitive Sectors
This figure reports the average cumulative equity returns of all publicly listed firms, grouped by the 48 Fama-French industries. The horizontal axis shows cumulative returns during four separate days in 2018 identified as market reactions to predominantly trade disruptions. The vertical axis shows average cumulative equity returns during April 2–8, 2025. Both axes represent returns demeaned by the cross-sectoral average for the respective period. The dashed red lines indicate the mean return, dividing the chart into four quadrants: Vulnerable (lower-left), Resilient (upper-right), Has Weakened (lower-right), and Has Strengthened (upper-left). The table provides the industry definitions for a selection of sectors. As expected, the Vulnerable group includes industries heavily reliant on foreign trade or global supply chains, such as electronics and computer equipment, as well as others, like oil and gas extraction or air transportation, which may be sensitive to the broader recessionary effects arising from disruptions to global trade. Conversely, industries in the upper-right green-shaded quadrant performed above average in both episodes and are classified as least vulnerable. Many of these industries—such as precious metals and utilities— tend to fare better during periods of heightened macroeconomic uncertainty as they serve investors as a hedge. Data sources include CRSP via WRDS.
Figure 3: Figure 3: Banks Returns and Exposure to Trade-Sensitive
Sectors
This figure presents the cumulative equity returns during the week of April 2ⁿᵈ–8ᵗʰ, 2025, on the vertical axes, against our measure of banks’ vulnerability to trade policy shocks: the ratio between banks’ total assets and C&I loans of borrowers from the [20] vulnerable industries. Because we cannot disclose bank-level information, each dot represents a group of four banks with similar (vulnerability, return) characteristics, while the fitted line is estimated using individual bank data. As the figure shows, there is a statistically significant negative correlation of -0.42 between banks’ vulnerability and returns, with our proposed measure explaining 18% of the cross-sectional return variation. These results are consistent with the view that banks’ exposure to trade-sensitive borrowers is an economically meaningful driver of banks’ performance during disruptions to foreign trade.