Authors: Kate Anderson, PhD, Senior Manager, Network Science and Teddy DeWitt, PhD, Lead Computational Social Scientist
Markets across the globe crashed in response to last week’s tariffs, erasing more than $10 trillion and causing drops not seen since the beginning of COVID. The turmoil continued on Wednesday, with a series of retaliatory tariff announcements.
While the White House did announce a 90-day delay in country-specific tariffs, with a corresponding market rebound, these swings in the market are disruptive and reflect broader concerns around an uncertain economy.
However, the impact is not uniform. Some companies are seeing larger swings than others, indicative of additional financial risk. Thanks to interos.ai’s anomalous returns predictive model, we can leverage market data to identify which companies and industries have a greater likelihood of enhanced financial risk in this era of uncertainty and trade barriers.
A Tumultuous Financial Market: Tariffs and Trade War
Last week’s reciprocal tariffs executive order introduced a 10% tariff on all US imports, with steeper rates for dozens of countries, including some of the US’s biggest trade partners.
While the worldwide 10% tariff went into effect on Saturday, April 5th, this was then paused and for the next 90 days as of April 9th. The tariff rate on China went into effect on April 9th.
The other promised country-specific tariffs are scheduled to start after a 90-day period. These additional tariffs – impacting 86 countries – disproportionately affect some major US trading partners, including China, India, Vietnam, and Taiwan, with projected severe effects on supply chains and global markets.
The 10% world-wide tariff and “reciprocal tariffs” on other countries add to those already levied by President Trump earlier this year, including an additional 10% duty on imports from China, a 25% tariff on imported cars, 25% on steel, between 10-25% on aluminum, and import tariffs on a variety of Canadian and Mexican goods.
The new batch of US import tariffs hits several of the country’s largest trading partners, which interos.ai forecasts will have a dramatic effect on supply chains.
The initial announcements raised the tariffs on Chinese imports by 54%, to a total of over 64%, with updated announcements increasing rates to 125%.
Chinese goods represent 16% of US imports, including critical parts and raw materials such as rare earth metals. Other major US trading partners were threatened with similarly large tariffs.
India’s announced tariff rate rose from 2% in 2024 to 26%. The tariff rate in Taiwan—the source of most of the world’s semiconductors—rose from 1% to 32%. While semiconductors are not currently under tariff restrictions, President Trump has implied that they may lose that exemption. Tariffs on Vietnam—a significant exporter of electronics—are going from 4% to a staggering 46%.
These tariffs have triggered retaliatory measures by other countries:
- European Union reacted with tariffs on a wide range of goods commonly imported from the US.
These numbers are changing daily, fueling uncertainty and market instability.
Financial Instability: Identifying At-Risk Industries and Companies
The reaction of the markets to the tariff announcement was immediate and dramatic.
On April 3rd, the day the tariffs were announced, the markets experienced a drop of 4-6% — the largest single-day drop since the pandemic.
This kind of drop in market price suggests that investors are anticipating future financial instability.
While the markets rebounded after the 90-day stay announcement on Thursday, investors are still extremely nervous, and markets are likely to experience further big swings in the coming months.
As part of interos.ai’s comprehensive machine learning model for financial risk, the anomalous returns model captures unexpected shifts from expected market behavior.
Markets often reflect the collective knowledge of investors about the financial future of a company. By including daily market returns in our scoring, interos.ai leverages that collective knowledge to predict financial risk, especially important in identifying which companies or industries may be most affected.
interos.ai uses an algorithm to identify anomalies in return data—companies that experience a larger drop than would be expected given current market conditions and historical price volatility. This indicator was inspired by the Silicon Valley Bank (SVB) banking crisis, when the stock price of SVB experienced an abnormally large decline months before the actual crisis occurred.
Looking at the overall market certainly highlights the pessimism of the market.
However, it disguises an important factor — losses are not uniformly distributed across different parts of the economy.
While some industries experienced large drops in average returns, others saw no drop at all. The table below shows the interos.ai industries that saw the largest drop in market returns last week. Apparel, Manufacturing, and Retail industries saw the biggest hits, followed by Ship Building, Springs, Furniture Manufacturing, Electronic Components, and Freight and Transportation.
The picture is still more complex than that.
interos.ai’s Financial Model Shows Over 1,000 Companies Exposed to Abnormally High Financial Risk from President Trump’s Tariffs
After all, the entire market crashed on April 3rd, and even healthy companies likely took a hit. In addition, some industries are more volatile than others, meaning that what might be a large drop in market price for a metal manufacturer looks very different from what normal looks like in other industries. Our anomalous returns model identifies companies that saw a disproportionate fall in market returns, relative to declines in the rest of the market and relative to historical volatility.
Context is everything.
And makes the difference between getting in front of risk or being controlled by the risky fallouts. While electronics made headlines for seeing a big drop in returns on April 3rd, the data from the anomalous returns model suggests that the drop was not abnormally large. The electronics market is historically volatile such that we expect returns in that industry to drop with the smallest overall market decline.
In contrast, metal manufacturing and fossil fuel extraction are extremely stable industries. Seeing a large drop in the market returns for companies in those industries is a huge red flag, even if they are smaller in absolute terms than the drops in electronics.
interos.ai identified over a thousand companies globally that exhibited an abnormally large response to the market shifts.
These are companies that not only experienced losses, but unexpected losses—losses that are many times larger than would be expected given the overall market decline and are therefore at much greater financial risk.
Some companies experienced extraordinarily large losses, with the highest of these declines upwards of 50%.
Unsurprisingly, many of the penalized companies come from countries heavily impacted by the new tariffs, including Canada, Japan, and China.
Avoiding the Fallout from High Financial Risk
The uncertainty around the US’s position in the global economy continued this week as some announced tariffs went into effect and others were delayed.
The global response to the announcements were swift, with retaliatory tariffs levied against US imports and stock markets falling.
Jamie Dimon, Chaiman and CEO of JPMorgan Chase commented on the risk climate we have entered in his latest letter to shareholders. “The economy is facing considerable turbulence (including geopolitics), with the potential positives of tax reform and deregulation and the potential negatives of tariffs and “trade wars,” ongoing sticky inflation, high fiscal deficits and still rather high asset prices and volatility.”
During such an unprecedented time, supply chain resilience becomes even more critical. To stay afloat in a tumultuous trade war is to stay abreast of the regulatory shifts and to ensure visibility into your supplier dependencies.
If a critical supplier is buried in your supply chain and is exposed to abnormally high financial risk, you need to know. And you need to know so you can act before disaster strikes. Underlying market information can help surface growing financial risks.
interos.ai will continue tracking those companies and industries exhibiting anomalous returns, providing proactive intelligence for our customers as they weather such dramatic micro-economic fluctuations.
Supply chain disruptions cost financial services organizations $164 million per year on average.
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