Can AI Rebound as Expected Next Week? Four Key Catalysts That Could Shape the Market

U.S. AI stocks plunged on Thursday, sending the market into a state of extreme pessimism. A wave of negative factors came to the fore, including slower data center construction, cloud giants scaling back computing capacity purchases, and growing difficulty securing AI financing. The AI industry’s rapid expansion over the past few years seemed to have come to an end.

But on Friday, the market showed clear signs of recovery: chip stocks rebounded across the board, the Philadelphia Semiconductor Index rose 3%, and the S&P 500 gained 0.3%. The market began to gradually revise its extreme pessimism from Thursday. It is worth noting, however, that more than half of the index constituents were still down, indicating that confidence in the entire AI supply chain has yet to fully recover.

From a valuation perspective, leading AI stocks still have room for a short-term oversold rebound. Take NVIDIA, for example: even after rebounding to close up 3% on Friday, its trailing P/E ratio was only a little over 25x. Based on Wall Street’s earnings forecasts for next year, its forward P/E was about 14x, while its 24-month rolling P/E was just over 10x—a record low since 2013.

By comparison, Cisco, the leading company during the 2000 dot-com bubble, had a P/E ratio of over 100x. Traditional consumer stocks like Coca-Cola and Procter & Gamble now also have P/E ratios above 20x. Yet NVIDIA’s revenue surged 106% last quarter, and the market expects revenue growth of 91% and 83% in the next two quarters. For a tech giant with cash flow in the tens of billions and earnings nearing a twofold increase, its current share price effectively values future growth at “zero”—clearly unreasonable.

However, whether the AI sector can move from a technical recovery to a sustained rally still depends on four key catalysts:

1. U.S. Inflation and Fed Rate Expectations

Friday’s nonfarm payrolls added 165k jobs, far exceeding expectations of 65k, while the unemployment rate fell to 4.1%. This briefly pushed expectations for a December rate hike to around 85%, seemingly unfavorable for tech stocks. The stronger the economy, the more reason the Fed has to maintain tight policy, and the more likely the dollar and Treasury yields are to remain elevated.

But there is an opposing dynamic: sharp stock market volatility can itself constrain the Fed. The Fed looks not only at economic data but also at how financial conditions affect the economic outlook. AI has become the most important driver of U.S. corporate investment and economic growth. If AI stocks continue to fall, investor risk appetite will decline, AI companies will find it harder to raise funds, data center projects will be delayed, and cloud giants will cut capital spending. Financial markets will tighten financing conditions on their own, raising corporate financing costs and reducing investment appetite, which could in turn weaken economic demand and inflationary pressures.

The Fed’s new communications channel also noted that whether the recent sell-off in AI assets has already changed financial conditions could become the most important variable in December’s policy discussion. Meanwhile, oil prices fell sharply this week, with U.S. crude down 12% and Brent crude down 13%. If lower energy prices gradually feed through to inflation data, next Tuesday’s October CPI and Friday’s PPI data could create an opportunity for the market.

2. Can Panic Selling and Credit Markets Stabilize?

Goldman Sachs’ Volatility Panic Index reached 9.57. Historically, extreme fear has often been followed by opportunities for a medium-term rebound. But Goldman also estimates that trend-following strategies could still trigger $28 billion in S&P 500 futures selling over the next week, so Friday’s rebound does not prove that all passive selling is over.

More importantly, there is the credit market: during Thursday’s crash, investment-grade credit spreads widened by only 3.6 basis points, below the 8.2 basis points implied by models. This is actually good news, indicating that stock market panic has not spread into a broad deterioration in corporate credit risk.

Next, watch whether credit spreads can stabilize: if share prices stop making new lows and credit spreads do not continue to widen, it may mean the market is absorbing the shock. Conversely, if financing costs for AI data center companies continue to soar and credit risk starts spreading to the bond market, Thursday’s low may not hold.

3. AI Companies’ Financing Ability and Valuations

Whether AI companies can still raise money, and what prices investors are willing to pay, are key factors affecting the sector’s direction. This is especially true for Anthropic and OpenAI, which are preparing to go public. Discussions of Anthropic’s potential IPO valuation have moved down from the previous $1.4 trillion to $1.5 trillion range to $1.2 trillion–$1.3 trillion. OpenAI recently completed the first $11 billion tranche of its fundraising, at a valuation of $1.25 trillion, but its overall fundraising target was cut from as much as $30 billion to $20 billion.

The situation has two clear sides: the good news is that AI giants can still secure massive funding, showing that capital has not left the industry; the bad news is that investors are starting to demand more reasonable prices and are no longer willing to pay without limit for future growth.

If Anthropic launches its IPO roadshow as scheduled next week, institutional subscription demand will be crucial: if demand remains strong even after the valuation is lowered, it would show that the AI primary-market financing window is still open. If institutions continue to push for a lower price or even demand a smaller offering, the secondary market will need to reassess the AI supply chain’s ability to raise funds.

4. AI Supply Chain Orders and Profits

This is the key factor that will determine whether the rebound can shift from sentiment to fundamentals. The focus will be NVIDIA’s earnings call on November 17: how Jensen Huang responds to market questions, whether cloud giants will continue to increase capital spending, whether orders for next-generation chips are sufficient, whether data centers can be delivered on schedule, and whether computing utilization and customer returns can keep pace with investment.

Microsoft’s recent adjustments to computing capacity rentals for some older-generation chips are particularly notable. Customers are raising their purchasing standards, showing that AI demand remains strong—but that does not mean every new cloud provider, every type of GPU, or every data center will have the same growth opportunities.

Overall, this AI market is more about a new round of selection than a blanket buying opportunity. The market has already priced in extreme pessimism. If the four catalysts show marginal improvement, the AI sector could see an oversold rebound, but a sustained rally will still require further confirmation from fundamentals.