stress testing – PJFP.com

Ken Griffin, founder and CEO of Citadel, sat down with Goldman Sachs’ Raj Mahajan at the firm’s Apex Symposium (recorded June 2, 2026) for this episode of Goldman Sachs Exchanges: Great Investors. It is their third public conversation in seven years, and Griffin is unusually candid: about the Friday he went home “shocked and depressed” over AI, the agentic system inside Citadel that compresses six weeks of PhD-level work into two hours, why a Chinese move on Taiwan would throw the US into a depression within six months, and the one question every hedge fund investor should ask their GP.

TLDW

Griffin names his two proudest leadership calls: dragging Citadel back to the office five days a week before it was acceptable (citing Fed research that remote work has hurt young Americans’ employment more than AI has), and Citadel’s pandemic role, from getting the FDA to approve experimental COVID drug trials in 72 hours to shaping the incentive design behind Operation Warp Speed, which he credits with saving roughly half a million American lives. On markets, he explains why the S&P sits at all-time highs despite wars in the Middle East and Europe: US energy insulation, stunning Chinese oil demand destruction, and record corporate earnings. On AI, he distinguishes hype from reality (a dinner of multinational CEOs gave him five stories of “AI transformation,” none of which were actually AI), then describes the internal breakthrough that changed his mind: an agentic system that reads, reproduces, and out-of-sample-tests academic finance papers in 2 to 3 hours instead of 6 to 8 weeks. The consequences: no layoffs at Citadel, but competitive moats across the economy are being filled in at lightning speed, setting up a golden age of entrepreneurship. He covers the compute market (all available compute is utilized all the time; market makers now spend hundreds of millions a year), China’s lead in roughly 67 of 74 critical technologies, the Taiwan scenario in which losing TSMC chips cuts US GDP 8 percent in six months, an energy doctrine built on nuclear, natural gas, and building data centers (with their own generation) in America, his stress-test approach to tail risk (definable, tolerable, still in business), and hedge fund economics: the industry’s cost of capital is roughly risk-free plus 4 percent, which is why Citadel has returned $25 to 30 billion to its LPs.

Thoughts

The most useful thing in this conversation is Griffin’s two-sided read on AI, because he refuses to pick a lane. The paper-replication story is the cleanest documented example yet of AI eating not just white-collar work but masters-and-PhD-level work, from the man whose firm profits from that labor. Yet in the same breath he reports zero headcount reduction, because Citadel has more problems to attack than people to attack them. Both things are true at once, and he names the synthesis honestly: the individual firm gets more productive while every firm’s moat gets shallower. Most commentary picks either the doom frame or the productivity frame. Griffin holds both, and his conclusion (a golden age of entrepreneurship, startups running on a few AI systems instead of 30 to 40 employees) is the actionable part.

His dinner-party anecdote deserves to be a standard reference. Five global CEOs effusing about AI transformation, and every single story was actually machine learning, optimization, or plain digitization. The C-suite cannot tell AI from technology at large, which means a meaningful slice of the “AI is transforming our business” narrative priced into the S&P is really a decade-old digital revolution wearing a new label. That is not a bearish observation, since the earnings are real either way, but it matters for anyone trying to figure out which companies actually have AI leverage and which have rebranded their IT budget.

The Taiwan section is the starkest risk framing you will hear from someone who runs both a hedge fund and one of the world’s largest market makers. An 8 percent GDP contraction in six months is not a market correction, it is Boeing halting production, new cars stopping, and consumer electronics freezing simultaneously, because TSMC chips are in every high-end product made. What makes his version distinctive is the second-order point: in a Taiwan blockade, he does not expect unified Western sanctions. Europe’s membership on “team USA” is less clear than it was two years ago, and the Middle East will play Switzerland because China buys its oil. Investors should notice that his answer to “how do you hedge this?” is not clever derivatives, it is his stress-test doctrine: know the worst case, size exposures so the loss is definable and tolerable, and stay in business to fight back.

Finally, the small structural details are where the conversation earns its Great Investors billing. Compute has become a commodity input like jet fuel, fully utilized at all times and allocated purely by willingness to pay, which quietly favors high-margin businesses and squeezes everyone else. Alternative data made the present transparent, so the remaining edge in stock picking is multi-year vision about which companies are building transformative products. And the hedge fund test he closes with is one any allocator can use tomorrow: is your GP in the asset management business or the performance business? Citadel returning $25 to 30 billion to LPs is what the performance answer looks like in practice.

Key Takeaways

Griffin’s proudest leadership call was bringing everyone back to the office five days a week, extremely early and against the culture, because humans are social creatures who learn through apprenticeship and mentorship.
He cites a Fed paper on reduced employment among workers under 30: remote work turns out to be a more important factor in diminished opportunities for young Americans than AI.
At the start of the pandemic, a hospital-system CEO called Griffin because he could not get FDA approval for drug trials on ventilated COVID patients; Citadel’s team got experimental trials approved in about 72 hours.
The key insight behind Operation Warp Speed, which Griffin discussed at length with Jared Kushner, was an incentives fix: the US government paid pharma to manufacture vaccines before FDA results existed, collapsing time-to-market from months to days.
By his math, the country spent a few billion dollars on that risk, saved a few trillion dollars of GDP, and saved roughly half a million American lives.
The S&P is at all-time highs despite a Middle East war, a still-raging war in Europe, and a potential skirmish over Cuba, because the US is relatively shielded from the energy shock.
China’s oil demand elasticity stunned even Citadel’s commodities business, one of the largest in the world; that demand destruction plus episodic oil flows out of the region has kept crude near the low $100s instead of the nearly $200 most models predicted if the straits closed.
Citadel has been a huge user of machine learning since TensorFlow arrived roughly a decade ago; the current wave is an acceleration of a digital revolution already underway, not a clean break.
At a dinner two years ago, Griffin asked global multinational leaders to share how AI was transforming their businesses: he got four or five great productivity stories and not one actually involved AI. They were machine learning, optimization, and digitization.
In the C-suite the nuance between AI and technology at large gets lost, but bigger budgets and CEO enthusiasm are pushing through real projects with real bottom-line impact; US corporate earnings are at all-time highs and multiples have actually come down as a result.
The use case that sent Griffin home shocked and depressed: a Citadel team member built an agentic AI system that reads an academic finance paper, reproduces it, verifies the published results, and tests them out of sample in 2 to 3 hours on average.
That same replication work previously took a legion of young masters and PhD hires roughly six to eight weeks per paper; Citadel finds a few tradeable ideas a year this way, and a few ideas can be worth a lot of money.
The point he stresses: this is not just a white-collar job being automated, it is a master’s or PhD-level job, and AI is now cracking problems (like the 80-year-old math problem OpenAI solved) that seemed beyond its reach two or three years ago.
Despite the breakthrough there has been no reduction in headcount at Citadel: the firm has more problems to attack than people, so Griffin takes every productivity gain he can get.
The flip side is that competitive moats across corporate America are being filled in at breathtaking speed, which Griffin expects to produce a golden age of entrepreneurial activity.
His example: a startup that would traditionally need 30 or 40 employees now runs with just a few AI systems, letting entrepreneurs take on incumbents in ways impossible 5, 10, or 20 years ago.
Some workers face genuinely hard transitions (his example is English-to-German translators), and the country needs to figure out how higher education can retrain these people quickly.
Stock picking remains a timeless business with a similar skill set, but the market will increasingly reward multi-year vision about which companies are creating transformative products rather than skill at calling quarterly earnings beats.
Alternative data (Citadel has access to the credit card spending of millions of Americans) made the here-and-now transparent a decade ago; AI plus bright people now triage the present almost instantly, so relative value accrues to those who can see years ahead.
At Citadel Securities, transformer models continue a decade of ML-driven improvement in pricing and risk management, and the same is true at other leading market-making firms.
For all intents and purposes, all available compute in the world is utilized all the time; access is decided by who will pay the most, and the per-unit price has risen beyond what anyone reasonably projected two or three years ago.
Large market-making firms now spend hundreds of millions of dollars a year on compute; Griffin compares compute inflation to jet fuel and egg prices, a cost that high-margin businesses can bear and low-margin businesses cannot.
China leads in roughly 67 or 68 of the 74 or 75 most important technologies in the world, including solar, EV batteries, and multiple quantum fields, and has pulled ahead in published academic papers.
The drivers are structural: 1.4 billion people, an extraordinarily strong educational culture, and far more STEM graduates, producing exactly the human talent needed to win in a high-IP world.
China is no longer relegated to producing low-margin products designed in America, and Griffin calls that shift a threat to the American way of life; the answer is not tariffs but educating US youth to out-compete, out-innovate, and out-problem-solve.
If China takes Taiwan and the US loses access to Taiwanese semiconductors, the rough estimate is US GDP falls 8 percent in six months: a great depression in the blink of an eye, unlike any before.
The mechanism is concrete: Boeing stops making planes within six months, most new cars stop being manufactured, consumer electronics production freezes, because TSMC chips are in every high-end product made.
There are no winners in a Taiwan escalation: tanking the US economy would have draconian knock-on effects for China given America’s importance as an export market.
In a Taiwan blockade Griffin does not expect unified global sanctions against China: where you sit determines your exposure, Europe’s place on team USA is less clear than two years ago, and the oil-exporting Middle East will play Switzerland.
On energy, the US must re-embrace nuclear, with small modular reactors a big part of the story: nuclear has effectively no carbon footprint and one of the lowest mortality rates of any energy source ever used (hydro has killed magnitudes more people).
He punctures the clean-energy veneer: solar cells are often made in western China by burning coal, with roughly a seven-year energy payback, and carbon fiber wind turbine blades last 20 years then fill landfills because they do not break down. No truly clean solution exists until fusion or broader nuclear.
Until then, natural gas is America’s huge asset: decades of cheap supply, and one of the few things that has actually brought down US carbon emissions.
Data centers are going to get built somewhere, and Griffin argues it would be inane for America to end up dependent on foreign countries for them; his fix for NIMBY politics is to require data center builders to construct corresponding power generation, tied to the grid for reliability, rather than pushing costs onto consumers.
His hedging doctrine for complicated risks: run stress tests, know exactly how much you lose and where in the worst case, and keep exposures sized so the loss is definable, tolerable, and leaves you still in business and able to fight back. You will never hedge every tail event.
Hedge fund industry economics: the long-run cost of capital is roughly the risk-free rate plus 4 percent; underperform and capital flows out, outperform and it flows in, and inflows dilute alpha because alpha capacity is finite.
Citadel has returned $25 to 30 billion to its limited partners to keep return on equity high: Griffin’s job is to grow annual alpha capacity, and any capital beyond what the portfolio needs goes back to LPs.
The alignment test for allocators: the biggest investor in Citadel’s funds is Griffin and his partners, and every LP should ask whether their GP is in the asset management business or the performance business.

Detailed Summary

Return to Office and the Cost of Remote Work

Asked what he is most proud of beyond the numbers, Griffin starts with Citadel’s early, countercultural demand that everyone return to the office five days a week. He frames it as a human capital decision, not a control decision: people learn through apprenticeship, mentors are critical to development, and the underdevelopment of talent from remote work has damaged the broader economy. He points to recent Fed research on falling employment among under-30s: remote work turns out to matter more than AI in diminishing opportunities for young Americans. Citadel not only brought its team back but publicly extolled the virtues of doing so, and Griffin believes history will be on his side.

72 Hours to FDA Approval and the Warp Speed Incentive Design

His second point of pride is Citadel’s pandemic chapter. As the first US COVID cases appeared, a former partner running a major New York hospital system called: he could not get FDA approval for experimental drug trials on ventilated patients facing imminent death, and believed only Griffin could make it happen. Citadel’s team, with decades of government experience, got approvals moving in about 72 hours. The second act was Operation Warp Speed, whose core idea Griffin discussed at length with Jared Kushner: pay pharmaceutical companies to manufacture vaccines before FDA results, so a positive result means days to market instead of the standard sequence losing three to six months. No company would spend billions producing vaccines that might be flushed down the sewer, so the US government took the manufacturing risk on unproven efficacy. A few billion dollars spent, a few trillion in GDP saved, and roughly half a million American lives.

All-Time Highs in a World at War

Griffin’s market picture is unsentimental: there is a war in the Middle East, a still-raging war in Europe, potential trouble in Cuba, and the peace both men grew up with is off the table. Yet the S&P sits at record highs. His explanation: America is relatively shielded from the war-driven energy crisis. China has curtailed oil demand with an elasticity that stunned even Citadel’s commodity desk, and episodic oil and LNG flows keep leaving the region, holding crude around the low $100s when most estimates had a strait closure producing nearly $200 a barrel. Meanwhile corporate earnings are at all-time highs, enough that multiples have actually compressed over the last 12 months.

The AI Story CEOs Tell Versus the One That Is True

Citadel has used machine learning heavily since TensorFlow arrived a decade ago, powering everything from radiology reads to self-driving cars across the economy, so Griffin sees today’s AI wave as an acceleration of an ongoing digital revolution. His favorite corrective: at a dinner with global multinational leaders two years ago, everyone was effusive about AI transforming their businesses, so he asked them to go around the table with specifics. Four or five genuinely impressive productivity stories emerged, and not one involved AI: they were machine learning, optimization, digitization, technology at large. The C-suite blurs the distinction, but the enthusiasm has unlocked bigger technology budgets and real bottom-line projects, which is part of why earnings are at records.

The Agentic System That Shocked Him

Then comes the story behind the famous “shocked and depressed” Friday. Citadel employs legions of young masters and PhD graduates to replicate academic finance papers: read the hypothesis, judge the work, reproduce results, and test whether the effect persists out of sample (does buyback activity predict outperformance, for example). Each paper takes six to eight weeks, and the process surfaces a few valuable ideas a year. A colleague built an agentic AI system that does the entire pipeline (read, reproduce, verify, out-of-sample test) in two to three hours on average. Griffin’s emphasis: this is not routine white-collar work, it is master’s and PhD-level work, and paired with OpenAI solving a math problem open for 80 years, it shows AI cracking problems considered out of reach two or three years ago. Notably, Citadel cut zero headcount on the back of the breakthrough; the firm has more problems worth attacking than people to attack them, so every productivity gain gets absorbed.

Filled-In Moats and a Golden Age of Entrepreneurs

The macro consequence Griffin draws is double-edged. Hold two thoughts at once: AI is reaching very high-level work in the job market, with some workers (translators, for instance) facing hard transitions that demand fast retraining through higher education. And simultaneously, the competitive moats of corporate America are being filled in at breathtaking rates. That means entrepreneurs can launch businesses at speeds impossible 5, 10, or 20 years ago: he mentions a startup running on a few AI systems where 30 or 40 employees would once have been required. He expects a wave of these stories over the next couple of years as founders use the technology to take on incumbents.

The Future of the Stock Picker

Griffin has called stock picking a timeless business, and he still sees a similar skill set for the portfolio manager of the future, with one shift in emphasis. Predicting quarterly earnings beats has gotten far harder over a decade as alternative data (credit card panels covering millions of Americans, telegraphing Starbucks and McDonald’s revenues) made the present transparent. Now bright people plus good AI triage the here-and-now almost instantly. The scarce, rewarded skill becomes vision: identifying which companies are building genuinely transformative products years before the market fully prices it.

Compute Is the New Jet Fuel

At Citadel Securities, which holds double-digit market share across equities, futures, and treasuries, transformer models extend a decade of machine learning gains in pricing and risk. The compute market backdrop is what Griffin calls breathtaking: essentially all available compute on Earth is utilized all the time, so access reduces to who will pay the most. Per-unit compute prices exceed what anyone reasonably projected two or three years ago, and large market makers now spend hundreds of millions of dollars annually. He treats it as straightforward input inflation, like jet fuel or eggs: high-margin businesses can bear it, low-margin ones cannot.

China’s Technology Lead and the Taiwan Equilibrium

Griffin states the cold reality: China is one of the most innovative, fastest-growing economies in the world, leading in roughly 67 or 68 of the 74 or 75 most important technologies (solar, EV batteries, several quantum fields) and now ahead in published academic papers. The foundation is 1.4 billion people, a culture with an extraordinary emphasis on education, and far more STEM graduates. China is no longer relegated to manufacturing low-margin products designed in America, and Griffin calls that a threat to the American way of life. His prescription is pointed: not tariffs, but educating American youth to out-compete, out-innovate, and out-problem-solve. Taiwan is the painful pressure point with no winner. If China takes Taiwan and the US loses TSMC chips, GDP falls an estimated 8 percent in six months: Boeing stops making planes, most new car production halts, consumer electronics freeze, a great depression in the blink of an eye. China would suffer draconian knock-on effects too. As an investor he thinks about position: sanctions in a Taiwan blockade would not be unified, Europe’s place on team USA is a genuine question mark now, and the oil-exporting Middle East would play Switzerland since China is its biggest customer.

Energy Realism: Nuclear, Gas, and American Data Centers

On powering AI, Griffin wants America to lead again in nuclear, with small modular reactors central: no meaningful carbon footprint and one of the lowest mortality rates of any energy source ever deployed (hydro has killed magnitudes more people). He challenges the superficial cleanliness of renewables: solar cells are often made in western China with coal power, requiring about seven years of energy capture to break even against the coal burned making them, and 20-year-old carbon fiber wind turbine blades do not break down and are already filling landfills. Until fusion or expanded nuclear, America’s real asset is natural gas: decades of cheap supply that has actually driven US emissions down. His data center position is blunt: they will get built somewhere, and depending on foreign countries for them would be inane, so build them in America. His answer to NIMBY politics: require data center developers to build corresponding power generation, tied to the grid for reliability, so the cost never lands on the American consumer.

Tail Risk, Tolerable Losses, and Hedge Fund Alignment

On hedging complicated risks, Griffin’s method is stress testing: if this happens, how much do we lose and where, and is that loss tolerable? You can never manage a portfolio for every possible tail event, but you can keep exposures sized so the worst case is definable and tolerable, leaving you still in business and positioned to fight back. On industry returns, he pegs the hedge fund cost of capital at roughly the risk-free rate plus 4 percent as the long-run equilibrium: underperformance drains capital, outperformance attracts it, and since recent outperformance keeps pulling money in, growing assets dilute alpha. That is why Citadel has returned $25 to 30 billion to LPs: alpha capacity is finite, Griffin’s job is to grow it, and excess capital goes back to investors to keep return on equity high. The closing advice is an alignment test: Citadel’s biggest investor is Griffin and his partners, and every allocator should ask whether their GP is in the asset management business or the performance business.

Notable Quotes

“Turns out that remote working is a more important factor to diminished employment opportunities for young Americans than AI.”
Ken Griffin, citing Fed research on under-30 employment

“We spent a few billion dollars as a country. We saved a few trillion dollars in GDP. We saved roughly half a million American lives.”
Ken Griffin, on Operation Warp Speed’s incentive design

“I got four or five incredible stories of how companies were achieving meaningful productivity gains. Not one involved AI.”
Ken Griffin, on his dinner with global multinational CEOs

“My colleague built an agentic AI system that would read a paper, reproduce it, verify the results that were published in the paper, produce the results out of sample, and do all this work in about on average 2 to three hours.”
Ken Griffin, on the breakthrough that replaced six to eight weeks of PhD-level work

“We’re likely to see a golden age of entrepreneur activity. Like entrepreneurs will be able to launch new businesses at breathtaking speeds and will be able to take on incumbents in ways that you just couldn’t do 5, 10, 15, 20 years ago.”
Ken Griffin, on AI filling in competitive moats

“All the available compute today is more or less utilized all the time. So the question is who’s willing to pay the most for it?”
Ken Griffin, on the global compute market

“The US loses access to Taiwanese semiconductor chips, our GDP falls by 8% in 6 months. Simply put, we go into a great depression in the blink of an eye unlike any we’ve seen before.”
Ken Griffin, on the Taiwan scenario

“We better damn well build the data centers in America because they’re going to get built somewhere in the world.”
Ken Griffin, on energy policy and AI infrastructure

“Definable, tolerable, still in business, still in a position to fight back from that point.”
Ken Griffin, summarizing his approach to hedging tail risk

“Are they in the asset management business or are they in the performance business?”
Ken Griffin, on the question every hedge fund investor should ask their GP

Watch the full conversation here: Ken Griffin on Goldman Sachs Exchanges: Great Investors.

Tag: stress testing

Ken Griffin on AI, the Golden Age of Entrepreneurs, and the Taiwan Chip Risk That Would Cut US GDP 8 Percent: Inside the Citadel Founder’s Goldman Sachs Great Investors Interview