Everything You Need to Know About the SpaceX Trading Debut

Elon Musk’s SpaceX is set to make its stock-market debut Friday in the largest IPO ever—and perhaps the most closely watched. The company sold an outsized portion of the offering to individuals. Its performance on Friday will be a crucial gauge of investor appetite for mega-offerings from OpenAI and Anthropic expected later this year.

The rocket maker, which derives most of its revenue from its satellite internet unit and has a nascent artificial-intelligence business, will trade under the ticker “SPCX.” It sold 555.6 million shares at $135 each, raising about $75 billion in a deal that valued the company at roughly $1.77 trillion.

When will shares open for trading?

SpaceX executives are set to ring the Nasdaq’s opening bell in New York, but shares in buzzy initial public offerings don’t tend to start trading until later in the day.

Bankers leading an IPO typically want to match buyers and sellers for about 10% of the shares sold before opening trading to lessen volatility. For SpaceX, that would be about 55 million shares, or roughly $7.5 billion worth.

Because pre-IPO investors are restricted from selling shares for a while, it can take time to find willing sellers among those who bought shares in a high-demand IPO.

Shares of Alibaba , the largest U.S. IPO until SpaceX, opened for trading a little before noon in its 2014 offering. Last year, one of the highest-profile offerings was that of software maker Figma , whose shares started trading just before 2 p.m.

It is possible that SpaceX’s bankers will decide to start trading without matching the typical portion of orders to ensure the shares have several hours of trading on their first day, people familiar with the matter say.

How volatile will the stock be?

Bankers and traders expect SpaceX’s share price could be volatile in initial trading, thanks in part to the large portion of its shares expected to be held by individual investors. Some who anticipate individuals will rush into the shares worry they could just as easily get spooked and rush out.

Any sharp movement in stock price could trigger so-called circuit breakers that could pause trading. For most newly listed companies, a 10% swing in either direction prompts a five-minute pause. Companies that had their shares halted include Figma and Cerebras Systems , the chip company whose shares soared in its May debut.

These forced timeouts applied to single stocks came after the so-called flash crash in 2010, when the Dow Jones Industrial Average fell 700 points in eight minutes before recouping much of the loss.

What is all the talk about the ‘green-shoe’ option?

If the stock starts trading erratically, bankers have a secret weapon to attempt to calm things down.

Underwriters typically sell more shares to investors than an IPO’s total offer size, colloquially called the green shoe. In SpaceX’s case, they sold about 15% more shares than the stated offering size.

Because this means they technically allocated more than the offering amount, the so-called stabilisation agent, in this case, Morgan Stanley , needs to buy back the excess number of shares to deliver them. If the stock starts to fall, the bank will buy the shares in the open market, which helps buoy the stock price. If the stock isn’t faltering, the stabilisation agent can buy the additional shares they need to deliver to investors directly from the company.

The term “green shoe” comes from the first company to employ a version of this method years ago, a shoemaker that was a predecessor to Stride Rite. When Meta Platforms , then known as Facebook, went public in 2012, its shares started dropping and its bankers stepped in to buy more shares.

How will Elon Musk’s take-it-or-leave-it pricing fare?

Like all things Musk, SpaceX’s IPO bucked the norms. Instead of approaching prospective investors with a possible price range for shares ahead of the IPO and incorporating their feedback, the company set an exact share price from the beginning: $135.

The idea was to limit drama for what is already the biggest IPO of all time. It did, however, remove what many see as an important step along the way: price discovery. The success of this approach will partly be judged by how SpaceX’s shares trade Friday. If the stock surges, critics will say SpaceX left money on the table by not pricing shares higher. If the stock falls or trades flat, there will likely be critiques that SpaceX and its advisers overestimated demand.

Will the machinery hold up—and what will be the wider market impact?

The sheer size of SpaceX’s IPO will test the trading infrastructure at Nasdaq and could have ripple effects in the broader market.

Nasdaq has practiced with mock openings to make sure its trading platform is prepared. When Facebook went public, some investors who tried to change or cancel orders ahead of trading didn’t get confirmations because of a technology malfunction. The confusion contributed to Facebook shares dropping on the first day of trading. They didn’t return back above their IPO price for more than a year.

Meanwhile, some market watchers expect added activity Friday in stocks that individual investors might sell to buy SpaceX shares, such as those of technology companies and Musk’s electric-car maker Tesla . Such sales already appeared to be under way earlier in the week, when individual investors dumped single-stock holdings on a net basis for two days in a row, according to Vanda Research. (To be sure, those sales came on days that were poor showings for tech stocks broadly.)

It will take several days for SpaceX shares to show up in any major index funds , so the offering’s wider impact on the market could play out over the next several weeks or longer.

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