After the Inflation Shock, the Market Begins to Worry About Who Can Withstand Higher Rates

Wall Street faced a session in which multiple risks were unleashed simultaneously. Hotter-than-expected inflation data pushed rate hike expectations higher, the energy market remained under pressure, and the selloff in AI-related bonds began to influence stock investors' judgment.

Data released by the U.S. Bureau of Labor Statistics showed that September CPI rose 0.6% month-over-month and 3.7% year-over-year; core CPI, excluding food and energy, rose 0.3% month-over-month and 2.6% year-over-year. Gasoline contributed more than half of the overall monthly increase, but housing, healthcare, and airfare also rose, showing that price pressures were not confined to energy.

The market's initial reaction was typical of an inflation shock: U.S. Treasury yields rose, rate hike expectations intensified, the dollar strengthened, and gold, crypto assets, and rate-sensitive stocks came under pressure.

But subsequently, U.S. Treasuries regained buying interest as stocks weakened further. Innes believes this shift is more noteworthy than the initial selloff: investors are beginning to consider just how much pressure current financing costs will place on the economy and corporations.

Elevated inflation means the Federal Reserve may need to maintain tighter policy; falling stocks and widening credit spreads will further tighten financial conditions beyond policy. Corporate financing becomes more expensive, investors' willingness to take risks declines, and economic activity may also be suppressed.

This makes policy judgment more complicated. Even if the Federal Reserve has not yet taken new action, the market itself may have already delivered an additional tightening effect.

Therefore, the rebound in U.S. Treasuries does not mean the inflation problem has been resolved. In the author's view, it more likely reflects that the market has begun trading two risks simultaneously: inflation that won't come down, and high financing costs gradually eroding growth.

AI valuations and profit expectations are under pressure at the same time

For AI-related stocks, rising interest rates are only part of the pressure.

Higher interest rates reduce the present value of future cash flows, making valuations that depend on future growth harder to sustain. At the same time, changes in the competitive landscape may also affect how much profit companies can ultimately earn.

In the past, investors were willing to pay high valuations for some AI companies based on an important premise: demand would be large enough, and leading companies would also have the ability to preserve high profit margins over the long term.

Innes questioned this premise. Taking memory chips as an example, if Chinese manufacturers narrow the technology gap, industry capacity continues to increase, and the supply tightness in server DRAM eases somewhat, then current high profit margins may contain a strong cyclical component and be difficult to extrapolate directly over the long term.

This is still a competitive scenario that needs to be verified by subsequent data, but it explains why the market is adjusting both valuations and earnings expectations at the same time.

When the cost of capital rises and expected profits are also threatened by competition, the return threshold companies need to clear rises further.

This is especially true for infrastructure companies. Data centers, servers, and supporting energy facilities require large upfront investment, while revenue is realized gradually in the future. The more expensive financing becomes, the more projects need to rely on high utilization rates, stable customers, and sustainable pricing to support returns.

The bond market asks: can companies hold out until revenue is realized?

Compared with equities, the concerns conveyed by the credit market are more direct.

CoreWeave's previously issued bonds maturing in 2031 with a coupon rate of 9.75% fell in intraday trading on October 14 to about 81% of face value, corresponding to a yield of more than 15%. The cost of protection against debt default also rose significantly, indicating that investors are demanding higher risk compensation.

Here it is necessary to distinguish between the coupon rate and the market yield. A decline in bond prices and a rise in yields does not mean that the company's interest expenses on existing fixed-rate debt increase immediately; it reflects a change in the return investors require to hold the bond, and it may also affect the conditions for future new borrowing and refinancing.

Innes believes the AI trade is now entering a new phase.

Whether computing power demand grows is still important; but for creditors, the more urgent question is: can the companies financing these needs maintain debt-servicing capacity and access to financing before revenue is fully realized?

A company can have a large order book and still come under funding pressure if upfront investment is too heavy and cash collection is too slow. There is no automatic equal sign between business growth and financial soundness.

Once such concerns persist, the risks can reinforce one another: wider credit spreads raise the cost of new financing; more expensive financing lowers project returns; weaker return expectations hit equity valuations; and falling share prices can in turn weaken a company's ability to replenish funds through equity financing.

The capital markets that previously supported expansion may also become more cautious as a result.

What can break this loop is stronger profitability, clearer cash flow guidance, and operating data sufficient to prove project returns. The market needs to see that companies can not only build facilities, but also convert investment into cash that can be used to service debt and continue operations.

Market leaders are weakening, and the market's buffers are also fading

The reason AI financing pressure can affect the broader market also lies in the fact that the companies involved have become important pillars of the rally.

When gains are concentrated in a handful of companies, their earnings expectations, capital expenditure, and financing capacity have a greater impact on overall risk appetite. Once the market leaders come under pressure at the same time, other sectors may not be able to pick up the baton in time.

Innes also incorporated options dealers' hedging behavior into the analysis. Under certain positioning structures, dealers' hedging purchases and sales can help buffer market volatility; but as prices and positions change, that effect may weaken and in some cases even amplify volatility.

This does not mean that breaking below a certain level will necessarily trigger a chain of selling. More precisely, it means that when market leaders weaken and buying support declines, new sell orders may produce larger price moves.

The energy market adds further uncertainty to this picture. In addition to crude oil prices, the author also focuses on diesel refining margins and tanker freight rates. If pressure in transportation and refined fuel links persists and is further transmitted to end-user prices, bringing inflation down could become even harder.

For AI companies that rely on financing to expand, this means interest rate pressure may not ease quickly.

Innes also discussed the possibility of future government support for strategic technology companies, but this is a scenario exercise and cannot be used to assume that AI companies have already obtained a financing backstop.

For now, investors still need to make judgments based on companies' own financial capacity. The core question raised by this round of adjustment is: under higher funding costs, which companies can convert AI demand into sufficient cash flow to support expansion and meet debt obligations?

Welcome to join the official BlockBeats community:

Telegram Subscription Group: https://t.me/theblockbeats

Telegram Discussion Group: https://t.me/BlockBeats_App

Official Twitter Account: https://twitter.com/BlockBeatsAsia