An unmistakable shots-fired moment in the US-China tech war arrived in early 2024 — via the Netherlands.
“We do not expect to get export licenses for our most advanced immersion systems — the NXT:2000 and up — for China in 2024,” executives at ASML Holding NV, the Dutch lithography giant at the heart of the global semiconductor supply chain, said on their earnings call in January that year, warning that the curbs, a result of years of US pressure, would knock 10% to 15% off the company’s core China equipment sales.
For global investors, this was Washington flexing its hegemonic muscle to delay a key rival’s race to the frontier of artificial intelligence, just as it was becoming the defining general-purpose technology of our era. But the disclosure raised more questions than it answered: What does a warning like ASML’s mean for investment portfolios? Who will bear the costs and reap the profits — the US, which designed the restrictions, or China, their intended target? And how are risks and returns being rewritten for companies caught in the crossfire across the world?
The investment community has some answers in Geoeconomic Pressure, a paper written by Christopher Clayton, a Yale School of Management finance professor, and other economists. They fed more than 600,000 corporate earnings calls — spanning two decades and 22,000 listed firms worldwide, including China — to open-source large language models running on Stanford University’s computing systems. The algorithm listened for genuine causality: not merely whether CEOs mentioned flashpoints, but if state coercion actually forced them to alter prices, divert investments, or redraw supply chains.
That nuance matters because traditional keyword searches stumble over context. Even sophisticated statistical tools unleashed on a bag of words fail to do the job: A routine maintenance shutdown can get flagged as business disruption and ascribed to a tariff action. A pre-trained language model, by contrast, grasps sentence-level intent, weeding out such false positives.
Language models are just as effective against false negatives. On public calls, corporate executives are notoriously reticent, loath to linger on the fallout of government diktats — particularly those from their own political leaders. To look past this hesitation, the researchers ran the same models over equity analysts’ reports. The AI’s reading of C-suite disclosures matched independent sell-side assessments almost in lockstep.
By latching on to what corporate bosses prefer to downplay, AI captured a nuanced account of pains and gains. In the US, firms subjected to Washington’s restrictions faced lost volumes and compressed margins. Across the Pacific, the shock worked like an adrenaline shot. In roughly 40% of Chinese earnings calls flagged for export curbs, management reported ramping up R&D. Among calls detailing higher spending, two-thirds aligned with a category that AI labeled as “Core Technology Indigenization” — pouring money into homegrown chip gear to escape the US chokehold. (The algorithm didn’t just sort transcripts into pre-assigned slots; it coined the category names.)
Other geopolitical shocks produced similar ironies. When Western sanctions hit Russia after its 2022 invasion of Ukraine, firms in Europe and the US shouldered write-downs, asset forfeitures, and higher logistics bills. The real winners were non-aligned bystanders in China and India. Freed from Western competition, they rushed into the vacuum and scooped up heavily discounted Urals crude.
Nor did Donald Trump’s 2025 tariff offensive go as intended. Foreign exporters didn’t “eat” the duties, as the US president had predicted. In nearly three-quarters of instances where management disclosed an effect, the impact was negative. Among those reporting outright harm, close to 60% pointed to inflated input bills. The rare domestic winners were those insulated from foreign supply chains. Without being saddled with the extra costs paid by their import-reliant rivals, they could still raise prices. Foreign producers, meanwhile, absorbed the pressure not by slashing export prices, but by moving factories to Vietnam and Mexico.
Whether the weapon is a tariff, a sanction, or a chip ban, economic statecraft is rarely a surgical strike. More often than not, it’s a messy carpet bomb that leaves substantial collateral damage in its wake. Investors profit from being able to spot unintended consequences before they appear in the price. Machines reading corporate chatter may just give them the edge to bet on geopolitics before the rest of the market catches on.
This column reflects the personal views of the author and does not necessarily reflect the opinion of the editorial board or Bloomberg LP and its owners.
Andy Mukherjee is a Bloomberg Opinion columnist covering industrial companies and financial services in Asia. Previously, he worked for Reuters, the Straits Times and Bloomberg News.
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