Written by: Xiao Bing

On November 5, the US stock market crashed, marking the worst November since 2008.

The Dow Jones Industrial Average plummeted by 1,833 points, a drop of 3.44%, the S&P 500 fell 4.36%, and the NASDAQ dropped 5.52%, evaporating $3 trillion in market value in a single day. It was the worst day since the pandemic panic in March 2020, with the VIX panic index soaring above 28.

The crash was sharply divided: while the AI narrative collapsed and hedge funds collectively scrambled out, Berkshire Hathaway hit a record high, and Walmart soared against the trend.

The same market, with two completely different outcomes.

This divergence points to a colder reality: AI is creating a K-shaped divergence that may last for a decade.

Scramble: Hedge Funds Collective Exit

There is an old saying on Wall Street: When you don't know who is selling, it means everyone is selling.

Goldman Sachs' Prime Brokerage data shows that hedge funds have net sold US stocks for six consecutive weeks. The amount of selling in the last two trading days reached the highest level recorded by Goldman Sachs. Goldman trader Cullen Morgan wrote in a weekend report to clients: "Friday was one of the most unsettling trading days in recent years."

After the S&P 500 broke below the crucial technical level of 6,725 points, trend-following hedge fund (CTA) models issued sell signals. Goldman estimates that just the CTAs could sell nearly $40 billion worth of stocks in the coming week. If the downward trend widens, total selling pressure could reach $65 billion.

Before the CTAs, tech stocks were already a disaster area.

Goldman data shows hedge funds sold tech stocks at the fastest pace in a decade, with the semiconductor sector being the hardest hit. Yet even so, tech stocks still accounted for 23.5% of Goldman’s global prime brokerage book, ranking in the 90th percentile over the past five years. After the frantic selling, hedge funds still held too many tech stocks and the selling was far from over.

At the fund level, Walleye Capital, managing $17 billion in assets, suffered a 5.9% loss in October, its worst performance since 2020, and was forced to undergo structural restructuring.

Millennium withdrew $1.5 billion from external managers.

Lone Pine was reported to face comprehensive liquidation risk. The most ironic case is the AI-themed fund Situational Awareness, which lost 67% earlier this year and was eventually acquired by Citadel at a discount.

Trader Noel Smith's judgment is very direct: "The market looks like a liquidation."

This is a structural scramble in the hedge fund industry. One fund is forced to sell, and the drop in prices triggers stop-loss lines for another fund, leading to further selling and more stop-loss triggers.

A hotel on fire, one person starts to run, everyone runs, and each person's movement makes the fire burn even more fiercely.

Trigger: The Democrats' "Data Center Moratorium"

The trigger for the crash came from Washington.

On November 3, the dust settled from the US midterm elections, with the Democrats sweeping both chambers of Congress. This outcome itself was not surprising, but the market underestimated one thing: The Democrats' hostility towards AI infrastructure is deeper, broader, and more enforceable than imagined.

Senator Sanders sent a clear signal on election night: "There should be a national moratorium on data centers immediately."

A more critical change occurred at the state level. Newly elected Democratic Governor Hinojosa of Texas promised to "suspend all data center approvals." Texas is one of the largest data center markets in the U.S., and newly elected Democratic governors in Georgia, Ohio, and Nevada made similar commitments.

Goldman provided a key number: 45% of the data center capacity under construction and in planning across the U.S. is located in states governed by these Democratic governors who support the moratorium. At the same time, about 40 local measures limiting data centers have been passed.

45% means that the core logical chain that has supported the US stock market over the past two years—"AI needs computing power, computing power needs data centers, data centers need capital expenditure"—has been interrupted in the middle.

Representative Ansari went further, calling for a "moratorium on advanced AI development" and banning ASI (superintelligent AI).

This extreme stance was enough to cause panic on Wall Street.

Elon Musk: The Biggest Gambler, The Worst Loser

In this crash, no one bled more than Musk.

On November 5, Tesla's stock plummeted 11% in a single day, after already falling 3.3% the day before. SpaceX's stock dropped 9%, falling below the IPO issuance price of $135. Musk's personal net worth evaporated by about $74 billion on the day of this crash.

Musk invested $366 million in political donations during this midterm election (with $276 million since July), making him the largest known single political donor, yet the Republican candidates he backed almost entirely collapsed.

Worse still, the threat of the data center moratorium following the Democrats' victory directly strikes at his most core assets, including the AI and autonomous driving narratives of Tesla, and the space data center plans that SpaceX is developing.

After the Democrats won control of both the Senate and the House of Representatives, Musk deleted a previously posted appeal on his own social platform X, urging voters to support Republicans, an unusual concession.

Berkshire and Walmart: The Other Side of the Divide

While the blood from tech stocks has not dried, another world is already celebrating.

Berkshire Hathaway Class A shares reached a historic high of $821,931, becoming the most sought-after stock in the market on a day when AI stocks crashed, this "most boring stock" was in high demand.

The reason is simple: Berkshire has $365 billion in cash reserves.

Everyone is debating whether AI is a bubble; hedge funds were forced to sell their best assets at the worst possible time, while Buffett (now led by successor Greg Abel) sits on a mountain of cash, waiting to pick up bargains.

Money is flowing from tech stocks into Berkshire, treating it as the best vehicle for "anti-AI trading."

Think about it—money that is the most optimistic about the future is pouring into a company known for "not touching things they don’t understand."

The story of Walmart is even more interesting.

In October, Walmart's stock price rose 13.9%, marking its best monthly performance since 2014. On the day of the crash on November 5, Walmart's stock rose 5.6%, outperforming the S&P 500 by nearly 13 percentage points, while the consumer staples sector ETF (XLP) has risen 13.5% year-to-date.

Walmart hasn’t gotten better. The change is happening to consumers: they are becoming poorer, or feel like they are becoming poorer.

High-income families are "downgrading their consumption," shifting from Whole Foods to Walmart.

K-shaped Divergence

The crash of AI stocks, the scramble of hedge funds, the stellar performance of Berkshire, the surge of Walmart, and the lines at McDonald's—these seemingly disjointed phenomena actually point to the same underlying logic: K-shaped economy.

The Oxford Economic Institute's data shows that AI has indeed brought over 7% growth in household wealth, but it is highly concentrated in the hands of a few. One of the most glaring data points for Q1 2026: AI-related economies grew by 31%, while non-AI economies grew by only 0.1%.

Societe Generale makes it very clear: The returns from AI ultimately flow to three types of people: those who own computing power, those who own data, and those who own models. For everyone else, AI is not an opportunity, but a cost.

BlackRock CEO Larry Fink has long warned that AI could exacerbate inequality.

The Oxford Economic Institute's predictions are even harsher: K-shaped divergence may last until 2035.

This somewhat explains the split in the flow of funds on the day of the crash:

AI stocks were sold off because the market realized that AI growth could be blocked by policy, and that this growth itself had not benefited the broader economy. Defensive consumer stocks rose against the trend because no matter how the AI story is told, people still need to eat, and an increasing number of people can only afford cheaper goods.

The rise of Berkshire and Walmart is not optimistic; their prosperity is built on the basis of most people's consumption downgrading; Berkshire’s new high is built on a demand for safe havens beside the ruins of tech stocks.

Their rise itself is a warning: smart money is pricing in a world where "AI has not saved everyone."

K-shaped divergence has already transformed from a market phenomenon into a structural reality of the era.

This pattern may last for a long time.