Why Berkshire Hathaway Might Stop Selling Bank of America Stock Once It Reaches This Number

Berkshire began liquidating its big stake in the banking company in mid-July—and has already unloaded about 15% of its interest. The selling has been fairly aggressive and has totaled about $6 billion. (Berkshire still holds 883 million shares, an 11.3% interest worth $35 billion based on its most recent filing on Aug. 30.)

The selling has prompted speculation about when CEO Warren Buffett, who oversees Berkshire’s $300 billion equity portfolio, will stop. The sales have depressed Bank of America stock, which has underperformed peers since Berkshire began its sell program. The stock closed down 0.9% Thursday at $40.14.

It’s possible that Berkshire will stop selling when the stake drops to 700 million shares. Taxes and history would be the reasons why.

Berkshire accumulated its Bank of America stake in two stages—and at vastly different prices. Berkshire’s initial stake came in 2017 , when it swapped $5 billion of Bank of America preferred stock for 700 million shares of common stock via warrants it received as part of the original preferred investment in 2011.

Berkshire got a sweet deal in that 2011 transaction. At the time, Bank of America was looking for a Buffett imprimatur—and the bank’s stock price was weak and under $10 a share.

Berkshire paid about $7 a share for that initial stake of 700 million common shares. The rest of the Berkshire stake, more than 300 million shares, was mostly purchased in 2018 at around $30 a share.

With Bank of America stock currently trading around $40, Berkshire faces a high tax burden from selling shares from the original stake of 700 million shares, given the low cost basis, and a much lighter tax hit from unloading the rest. Berkshire is subject to corporate taxes—an estimated 25% including local taxes—on gains on any sales of stock. The tax bite is stark.

Berkshire might own $2 to $3 a share in taxes on sales of high-cost stock and $8 a share on low-cost stock purchased for $7 a share.

New York tax expert Robert Willens says corporations, like individuals, can specify the particular lots when they sell stock with multiple cost levels.

“If stock is held in the custody of a broker, an adequate identification is made if the taxpayer specifies to the broker having custody of the stock the particular stock to be sold and, within a reasonable time thereafter, confirmation of such specification is set forth in a written document from the broker,” Willens told Barron’s in an email.

He assumes that Berkshire will identify the high-cost Bank of America stock for the recent sales to minimize its tax liability.

If sellers don’t specify, they generally are subject to “first in, first out,” or FIFO, accounting, meaning that the stock bought first would be subject to any tax on gains.

Buffett tends to be tax-averse—and that may prompt him to keep the original stake of 700 million shares. He could also mull any loyalty he may feel toward Bank of America CEO Brian Moynihan , whom Buffett has praised in the past.

Another reason for Berkshire to hold Bank of America is that it’s the company’s only big equity holding among traditional banks after selling shares of U.S. Bancorp , Bank of New York Mellon , JPMorgan Chase , and Wells Fargo in recent years.

Buffett, however, often eliminates stock holdings after he begins selling them down, as he did with the other bank stocks. Berkshire does retain a smaller stake of about $3 billion in Citigroup.

There could be a new filing on sales of Bank of America stock by Berkshire on Thursday evening. It has been three business days since the last one.

Berkshire must file within two business days of any sales of Bank of America stock since it owns more than 10%. The conglomerate will need to get its stake under about 777 million shares, about 100 million below the current level, before it can avoid the two-day filing rule.

It should be said that taxes haven’t deterred Buffett from selling over half of Berkshire’s stake in Apple this year—an estimated $85 billion or more of stock. Barron’s has estimated that Berkshire may owe $15 billion on the bulk of the sales that occurred in the second quarter.

Berkshire now holds 400 million shares of Apple and Barron’s has argued that Buffett may be finished reducing the Apple stake at that round number, which is the same number of shares that Berkshire has held in Coca-Cola for more than two decades.

Buffett may like round numbers—and 700 million could be just the right figure for Bank of America.

A sharp technology sell-off has exposed a new anxiety on global markets: whether the enormous borrowing behind the artificial-intelligence infrastructure boom can generate sufficient returns as interest rates rise and Chinese competition intensifies.

The artificial-intelligence investment boom has powered technology shares, semiconductor manufacturers and data-centre operators to extraordinary heights. Last week, investors were given a reminder that much of this expansion is being built with borrowed money.

The technology-heavy Nasdaq Composite fell 4.5 per cent over the week ended October 16, its weakest performance since late June. Semiconductor shares suffered an even deeper correction, with the Philadelphia Semiconductor Index losing about 11.4 per cent.

The selling spread quickly through global markets. Micron Technology fell 14.6 per cent over the week, while South Korea’s Samsung Electronics and SK Hynix dropped approximately 18 per cent and 24 per cent respectively.

This was more than a routine bout of profit-taking. Investors were reassessing three interconnected risks: higher interest rates, the rapidly expanding debt burden attached to AI infrastructure and the prospect of stronger competition from Chinese memory-chip manufacturers.

The debt behind the AI build-out

Artificial intelligence requires a physical infrastructure network of enormous scale. Data centres must be built, advanced processors purchased, power supplies secured and cooling systems installed before customers begin generating meaningful revenue from them.

Technology companies are increasingly supplementing their own cash with corporate bonds, syndicated loans, equipment leases, private credit and project-level financing.

JPMorgan describes the emerging funding model as a combination of conventional corporate borrowing and project finance tied to individual data-centre assets. In Australia, the Reserve Bank estimates that syndicated loans accounted for approximately three-quarters of data-centre financing during 2025 and 2026 to date.

The numbers are becoming large enough to affect broader credit markets. The Federal Reserve Bank of Dallas has cited Wall Street estimates suggesting AI-related investment-grade bond issuance could approach US$300 billion in 2026 alone.

That borrowing is not automatically problematic. Debt can be an efficient way to finance long-lived infrastructure when future revenue is sufficiently predictable. The concern is that AI technology, customer demand and computing economics are changing much faster than the repayment schedules attached to the assets.

A data centre financed today may carry debt for years. Investors must therefore make assumptions about future utilisation rates, electricity prices, chip performance, customer concentration and the amount businesses will ultimately pay for AI computing.

When interest rates rise, those assumptions become less forgiving.

Inflation changes the calculation

September’s US inflation data intensified the pressure. Consumer prices increased 3.7 per cent over the year, ahead of market expectations and up from 3.4 per cent in August.

The hotter reading reduced confidence that interest rates would fall quickly and pushed bond yields higher. That matters particularly for companies whose valuations depend on profits expected well into the future, as well as highly leveraged infrastructure operators that may need to refinance.

CoreWeave has emerged as a closely watched test case. The specialist cloud-computing company has accumulated substantial debt and lease obligations to build AI capacity, while relying on a concentrated group of large technology customers.

Its shares fell sharply during the sell-off, while the cost of insuring its debt against default climbed. CoreWeave has argued that its contracted backlog more than covers its obligations and that financial markets do not always understand its business model. Nevertheless, its securities have become a proxy for investor confidence in debt-funded AI infrastructure.

Oracle, another major investor in AI computing capacity, fell 8.8 per cent in Friday trading, while CoreWeave dropped 15.5 per cent.

The question is shifting from how much AI infrastructure can be built to how profitably it can be operated.

China adds another source of pressure

Interest rates were not the only catalyst. Reports of advances by Chinese memory-chip producer ChangXin Memory Technologies raised concerns that lower-cost Chinese products could increase competition across the global semiconductor industry.

Memory chips are essential to AI systems, but the industry is historically cyclical. Periods of tight supply and high pricing can encourage rapid investment, eventually producing oversupply and falling margins.

The prospect of a well-funded Chinese competitor expanding its technological capabilities unsettled investors in Samsung, SK Hynix and Micron. It also demonstrated that AI-related demand does not insulate chipmakers from conventional competitive pressures.

That combination—slower rate cuts, more expensive financing and potentially cheaper supply—challenged the assumption that every company exposed to AI would enjoy continually expanding margins.

A reset rather than the end of the boom

The sell-off does not establish that the AI boom is ending. Demand for computing power remains strong, the largest technology companies continue to generate formidable cash flows and many infrastructure projects are backed by long-term customer contracts.

What has changed is the market’s willingness to overlook the price and financing structure of that growth.

The most resilient companies are likely to be those able to fund investment from operating cash flow, secure long-duration customers and demonstrate that new capacity will earn returns comfortably above its financing costs.

More speculative operators may face greater scrutiny, particularly where debt is expensive, customers are concentrated or expected revenue depends on demand that has not yet materialised.

For Australian investors, the lesson extends beyond US technology shares. Local data-centre operators, infrastructure funds, electricity suppliers and property groups are increasingly exposed to the same investment cycle.

Artificial intelligence may remain one of the defining growth themes of the decade. But last week’s correction showed that enthusiasm for the technology does not eliminate financial discipline.

The next stage of the AI boom will be judged not only by computing power, model performance or demand for chips, but by something more traditional: whether the assets being financed can generate enough cash to repay the money borrowed to build them.

Fact box

Nasdaq Composite: Down 4.5 per cent for the week ended October 16, 2026

Philadelphia Semiconductor Index: Down approximately 11.4 per cent

Micron Technology: Down approximately 14.6 per cent

Samsung Electronics: Down approximately 18 per cent

SK Hynix: Down approximately 24 per cent

US September inflation: 3.7 per cent annually

Estimated 2026 AI-related investment-grade issuance: Approximately US$300 billion