The consensus among the panelists is that the recent success of Goldman Sachs, JPMorgan, and Morgan Stanley in equity trading and prime brokerage is driven by cyclical factors such as AI-driven volatility and relaxed capital rules, rather than a durable competitive advantage. The key risk identified is a synchronized deleveraging across correlated hedge fund positions, which could lead to a liquidity crunch and compress earnings quickly if AI capex growth disappoints or volatility normalizes.
Risk: Synchronized deleveraging across correlated hedge fund positions leading to a liquidity crunch
This analysis is generated by the StockScreener pipeline — four leading LLMs (Claude, GPT, Gemini, Grok) receive identical prompts with built-in anti-hallucination guards. Read methodology →
Fueled by the global boom in artificial intelligence stocks, relaxed capital rules and greater lending to hedge funds, big Wall Street banks have already had a banner year for equities trading — even with one quarter left to go.
The five biggest investment banks have generated about $67 billion in equities revenue through Sept. 30, according to company filings. …
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Fueled by the global boom in artificial intelligence stocks, relaxed capital rules and greater lending to hedge funds, big Wall Street banks have already had a banner year for equities trading — even with one quarter left to go.
The five biggest investment banks have generated about $67 billion in equities revenue through Sept. 30, according to company filings. That is $7 billion more than what the group made during all of 2025, which itself was a record haul.
But it's Wall Street's Big Three that have captured the largest slice of what is shaping up to be the industry's most lucrative arena: Goldman Sachs, JPMorgan Chase and Morgan Stanley have made a combined $52 billion in stock trading revenue so far this year, nearly 80% of the total.
"When it comes to the AI mega trade, the Big Three consider each other their main competitors, and that's pretty much it," Mike Mayo, Wells Fargo banking analyst, told CNBC. "They've been best positioned to take advantage of this market."
Wall Street banks are experiencing an epic run of blockbuster profits as the total value of the stock market balloons and trading activity from institutional and retail investors rises across stocks, ETFs and derivatives. Helping drive this activity are the loans that the banks, through their prime brokerages, are extending to hedge funds so that they can amplify their bets.
Prime brokerage — the business of providing hedge funds with margin loans, securities lending and other trading services — has become a key battleground and source of growth. The Big Three's prime brokers are central to the larger equities story because they serve the largest funds across markets and products.
Demand for leverage to make bets on AI hardware, hyperscalers and chip suppliers has reached new heights, bank executives said last week.
At Goldman Sachs, equities financing activities jumped 96% in the third quarter to a record $3.37 billion. JPMorgan and Morgan Stanley don't break out that figure, but said they saw a similar dynamic.
"I like your 'insatiable demand for capital' point. That feels about right," JPMorgan CFO Jeremy Barnum said on the bank's third-quarter conference call, responding to analyst questions about financing demands.
"In this moment where AI is such an overwhelming theme ... there is capital being tapped through all kinds of different mechanisms," Barnum said.
That demand has helped transform equity desks at the Big Three from cyclical, transactional businesses into more durable, high-margin lending engines, Wall Street executives say.
The performance gap between Wall Street's giants and rivals including Bank of America and Citigroup highlights a widening divide in capital markets.
"For clients, the value isn't just a price on one trade, it's coverage and continuity," Rachid Alaoui, JPMorgan global head of equities, told CNBC in an interview. "You want a dealer that can give you the full suite across products, and you want that service to travel with you across regions. That matters in stressed markets and periods of volatility."
Executing multibillion-dollar bets, like leveraged swaps on volatile AI stocks or sector ETFs, can require an enormous balance sheet. The biggest banks can absorb potential $100 million losses without threatening their quarters, according to trading executives. Smaller or more niche banks can't underwrite single-trade risks of that magnitude, forcing them to decline the business or cede share.
U.S. prime brokers have also benefited from the retreat of European banks including Credit Suisse from the equities business, said Bloomberg Intelligence analyst Herman Chan.
"Prime is one of the ultimate scale businesses," Chan said. "If you have a strong equities franchise, the hedge funds will want to transact with you because you have a bigger pool of trading opportunities with counterparties."
Picks and shovels
While U.S. markets were swept up in software and cloud computing giants this year, trading executives say the fastest-growing frontier for equities was in Asia.
Institutional investors poured into South Korea and Taiwan, targeting the "picks and shovels" of the AI supply chain: the memory chipmakers and semiconductor manufacturers supporting data center construction, Alaoui said.
For the Big Three, with their footprints across Tokyo; Hong Kong; Seoul, South Korea; and Mumbai, India; the Asia trade was a goldmine. However, trading executives point out that transaction taxes and stamp duties are included in top-line revenue, artificially inflating Asia prime totals.
There is also no agreed-upon definition of what equities trading revenue should include, so some banks include business lines like clearing services that others exclude from their stock trading totals, making apples-to-apples comparisons difficult.
But that doesn't change the overall momentum of the business, boosted by a stock rally that began in October 2022, weeks before OpenAI released ChatGPT.
"We're still in a stock-based world," Morgan Stanley CEO Ted Pick said on the firm's earnings call. "Equities are still, all things being equal, the attractive asset class."
While the CEOs of Goldman Sachs and Morgan Stanley have said the AI buildout is still in its early years, if AI turns out to be not as transformative as hoped, a downturn could impact those banks more than others, analysts said.
The boom has also drawn some concern over the possible risks posed by hedge funds.
The International Monetary Fund warned this month that growing leverage, crowded positions and correlated selling from hedge funds could create potential stability risks. The IMF estimated that global hedge fund assets had reached $13 trillion.
In August, JPMorgan CEO Jamie Dimon said industrywide leverage was "the highest it's ever been," though he stopped short of calling the risk big enough to pose a threat to the financial markets.
Wall Street executives and analysts pointed out that the industry wasn't fazed by the meltdown of several hedge funds this summer. While the hedge fund run by former OpenAI researcher Leopold Aschenbrenner, Situational Awareness, garnered the most headlines, several smaller firms also experienced a forced unwinding.
Prime brokers have learned to leap on margin calls and quickly take down risk when markets move against clients, JPMorgan's Alaoui said.
"In the summer, some investors had positions they were forced to unwind," he told CNBC. "They deleveraged, risk came down, and the market moved on."
'Known unknowns'
Another factor driving the equities boom: Trump administration regulators have eased some leverage rules for the largest U.S. banks, giving them more room to expand balance-sheet-heavy businesses including prime brokerage. The revised rules were finalized in 2025, and banks were allowed to adopt them as early as January.
By easing the stringent balance-sheet caps that previously treated Treasurys and prime brokerage loans, which are collateralized, the same as riskier assets, regulators gave dealers greater flexibility to deploy balance-sheet capital.
"Capital did go down, so you have to say the system is somewhat more levered because of the relaxation in regulations," said Darrell Duffie, a finance professor at Stanford University and a leading expert on financial stability. "It's not a good idea, but it hasn't gotten dramatically out of whack."
The larger size of the market and higher volatility can create more trading, derivatives activity and leverage, he said, but that's not inherently alarming.
Wall Street executives also downplayed concerns over leverage, pointing out that they use collateral and frequent stress testing to get ahead of problems.
"Hedge fund leverage as a contributor of risk to the system is very much in the category of known unknowns," JPMorgan's Barnum said last week. "It doesn't mean it's riskless, but we kind of know what it is."
— CNBC's Leslie Picker and Ritika Shah contributed to this report.
AI Talk Show
Four leading AI models discuss this article
Opening Takes
“Record equities revenue is a cyclical leverage peak masquerading as structural growth, with regulatory tailwinds set to reverse and hedge fund positioning at breaking-point crowding levels.”
The article conflates revenue growth with sustainable competitive advantage. Yes, GS/JPM/MS captured $52B of $67B equities revenue—but this is a leverage-fueled, AI-theme-dependent spike, not structural moat expansion. The real risk: prime brokerage margins compress when leverage unwinds. The IMF warning and JPMorgan's own 'highest leverage ever' admission are buried as afterthoughts. Regulatory relief (2025 balance-sheet rule changes) is temporary political tailwind, not durable. Asia 'picks and shovels' revenue is inflated by transaction taxes. If AI capex growth disappoints or hedge fund crowding reverses, these banks face a sharp cliff—not a gradual derating.
The Big Three's scale, collateral discipline, and margin-call speed genuinely do reduce tail risk versus 2008; summer's hedge fund blow-ups proved the system didn't break. If AI capex stays robust through 2026, equities revenue could sustain at elevated levels longer than the bear case assumes.
“The supposed durable edge is likely cyclical and leverage-dependent; a shift in volatility, regulation, or hedge-fund behavior could sharply compress profits.”
The article casts Goldman Sachs, JPMorgan and Morgan Stanley as winning via AI-driven equity trading and prime brokerage leverage, implying a durable edge. However, the edge looks cyclical and leverage-driven, not structural: if AI hype cools, volatility normalizes, or regulators curb leverage, earnings could compress quickly. The piece glosses revenue-definition inconsistencies (e.g., Asia tax influences) and downplays concentration risk in a few multi-billion trades linked to hedge funds. A regime shift—lower volatility, tighter capital rules, or a shock to hedge funds—could erode the moat, and competition from non-banks or other banks catching up could narrow the gap over time.
Bullish counterpoint: if AI bets stay hot and volatility remains elevated, the Big Three’s scale and cross-product reach could sustain high prime-brokerage volumes and margins; their network effects make an outsized, durable franchise harder for rivals to replicate.
“The Big Three's AI-driven revenue surge rests on hedge fund leverage that could reverse sharply if correlated selling accelerates beyond current risk controls.”
GS, JPM and MS have captured 78% of the $67B equities revenue through Q3, fueled by prime brokerage leverage to hedge funds betting on AI hardware and Asia semis. This shifts desks from cyclical trading toward durable, collateralized lending with high margins. Yet the same scale that lets them absorb $100M single-trade losses also concentrates exposure to correlated hedge fund positions, now at $13T globally per the IMF. Relaxed leverage rules since January 2025 amplify both upside and tail risk if volatility spikes.
The article itself notes that prime brokers quickly unwound summer hedge fund failures with no market disruption, and executives stress frequent stress testing plus collateral, so the leverage buildup may remain contained rather than systemic.
“Wall Street’s transition to a high-leverage prime brokerage model has effectively socialized the volatility of the AI trade while concentrating systemic risk within three balance sheets.”
The Big Three (GS, JPM, MS) are successfully pivoting from cyclical trading desks to high-margin, balance-sheet-heavy prime brokerage engines. By capturing 80% of equities revenue, they’ve created a 'moat of scale' that smaller rivals cannot cross, particularly as AI-driven volatility demands massive capital to underwrite leveraged swaps. However, the reliance on relaxed capital rules and the IMF’s warnings on $13 trillion in hedge fund leverage suggest this 'banner year' is built on a pro-cyclical foundation. If AI capex cycles stall, these banks are not just losing trading fees; they are holding the bag on potentially illiquid, highly leveraged collateral in a market that lacks the liquidity depth of 2023.
The 'Big Three' are actually better hedged than ever; their prime brokerage units are collateralized with high-quality assets, and the 'leverage' is largely a function of increased institutional demand for hedging, not speculative recklessness.
The Debate
Responding to Gemini
“Collateral quality is a red herring; synchronized redemption velocity is the real systemic trigger.”
Gemini flags illiquid collateral risk, but misses the mechanics: prime brokers mark-to-market daily and force liquidation before insolvency. Summer 2024 proved this works—Archegos blew up, no contagion. The real cliff isn't collateral quality; it's *velocity of unwinding*. If hedge fund redemptions spike alongside AI capex disappointment, even high-quality collateral floods the market simultaneously. That's the tail risk nobody quantified: not leverage itself, but synchronized deleveraging across $13T of correlated positions.
Responding to Claude
“Systemic liquidity risk from synchronized deleveraging across correlated hedge positions is the bigger cliff, not unwind velocity alone.”
Claude’s focus on unwind velocity is important but incomplete. The bigger flaw is ignoring cross-asset liquidity feedback: synchronized deleveraging across $13T of correlated hedges can trigger a systemic liquidity crunch even with daily mark-to-market. Margin haircuts, asset-fire sales, and funding strain across equities, rates, and credit could collapse collateral quality faster than expected, not just the pace of redemptions. If volatility spikes and AI capex disappoints, the cliff is liquidity—not just leverage velocity.
Responding to ChatGPT
“Equity-centric collateral limits automatic transmission of liquidity stress beyond equities.”
ChatGPT assumes synchronized deleveraging automatically spills into rates and credit markets. Prime brokerage books remain concentrated in equity swaps and AI-related derivatives, not broad fixed-income positions. A tech-specific margin spiral would pressure equity desks and funding desks first, without forcing simultaneous fire sales across unrelated credit or rates books unless hedge funds actively cross-hedge, which stress tests suggest they limit.
Responding to Grok
“Margin calls on concentrated equity positions force liquidations across unrelated asset classes, creating systemic contagion beyond the tech sector.”
Grok, your focus on 'tech-specific' silos ignores the reality of modern multi-strategy hedge fund mandates. When equity swaps trigger margin calls, funds don't just sell tech; they liquidate the most liquid assets across their entire portfolio—usually Treasuries and high-grade credit—to meet cash requirements. This creates a cross-asset liquidity contagion that transcends your 'tech-only' silo. The Big Three aren't just holding equity risk; they are the clearinghouse for the entire systemic deleveraging event.
Panel Verdict
BEARISH Consensus ReachedThe consensus among the panelists is that the recent success of Goldman Sachs, JPMorgan, and Morgan Stanley in equity trading and prime brokerage is driven by cyclical factors such as AI-driven volatility and relaxed capital rules, rather than a durable competitive advantage. The key risk identified is a synchronized deleveraging across correlated hedge fund positions, which could lead to a liquidity crunch and compress earnings quickly if AI capex growth disappoints or volatility normalizes.
Synchronized deleveraging across correlated hedge fund positions leading to a liquidity crunch
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