● Bond Yields Shock Markets
Four Reasons Wall Street Still Sees New Highs Despite Surging Treasury Yields: AI Stocks, Long-Term Rates, Oil, and OpenAI Rumors — Core Takeaways
What really matters in this market is not simply that “the Nasdaq fell 1%.”
The core point is why Wall Street is still talking about the possibility of new highs even as U.S. Treasury yields threaten the 5% range.
In this article, we will put together in one place the surge in oil prices, rising long-term yields, concerns about yen carry trade unwinding, rumors of an OpenAI training halt, AI semiconductor corrections, Nvidia share buybacks, HBM demand, power infrastructure, and strength in cybersecurity stocks.
In particular, the point that other news sources do not cover well is not whether the “AI investment cycle is over,” but whether AI infrastructure demand is expanding from training GPUs to personal AI agents and virtual machines.
1. Three negative factors that shook the market today: oil, long-term yields, and OpenAI rumors
The apparent causes of this selloff can be summarized into three main factors.
- First, the surge in global oil prices due to Middle East risks.
- Second, the spike in long-term Treasury yields driven by fiscal concerns and rising global rates.
- Third, rumors that OpenAI has halted training of its cutting-edge models.
Among these, the market reacted most sensitively to long-term yields.
Oil and AI rumors can shake stock prices in the short term, but rising U.S. Treasury yields are a structural factor that puts pressure on valuations across the board.
Growth stocks, AI semiconductors, cloud computing, and power infrastructure companies are especially vulnerable to higher rates because their future earnings are discounted into present value.
2. The oil spike cooled faster than expected: reinterpreting the Strait of Hormuz risk
Middle East risks initially pushed global oil prices sharply higher.
At the start of the session, oil prices reportedly jumped by about 4.4%.
This was because Trump made a strong statement that he was “controlling the Strait of Hormuz,” increasing market tension.
However, later discussion of possible progress in nuclear talks, the possibility of sanctions relief, and the release of frozen funds helped reduce the gains.
In the end, oil is said to have closed up by about 1%.
The important issue here is not oil prices themselves, but the crude transportation structure.
Although the Strait of Hormuz appeared to be completely blocked, Saudi Arabia’s east-west pipeline is actually operating.
Some tankers are also continuing shipments using so-called “shadow vessel” methods, where location tracking devices are turned off.
Combined with U.S. military escort and maritime transshipment strategies, oil export volumes are interpreted as having recovered significantly.
In other words, the oil spike increased short-term inflation concerns, but it does not appear to be a structural shock large enough to bring down the entire market.
In fact, the more fundamental risk in the market right now is long-term yields, not oil.
3. The real risk is long-term yields: not just a U.S. issue, but a global rate problem
The most important variable in the market right now is U.S. long-term Treasury yields.
The original text notes that the U.S. 10-year Treasury yield rose into the 5.2% range, and the 30-year yield also reached the 5.5% range.
At that level, stock investors can naturally think, “Why take risk on stocks when I can just buy bonds?”
Rising long-term yields put especially strong pressure on growth-stock valuations in the U.S. market.
Nvidia, Micron, Broadcom, AMD, AI servers, HBM, optical communications, and power infrastructure names are all highly sensitive to rates because they heavily reflect future growth.
The more difficult point is that this yield rise is not just a U.S. issue.
The UK has spoken about strengthening fiscal soundness, and European countries are also facing heavy debt burdens.
Japanese long-term yields are also being described as the highest since the 1990s, shaking global bond markets.
4. Concerns about yen carry trade unwinding: a core risk the market should not miss
One of the most important but relatively underreported points in this market is the concern over yen carry trade unwinding.
Japan has long maintained an ultra-low-rate or negative-rate environment.
Investors borrowed yen at low cost, converted it into dollars, and invested in U.S. Treasuries, U.S. stocks, and technology stocks.
But if Japanese rates rise sharply, the situation changes.
If Japanese government bond yields become attractive enough, there is less reason to hold U.S. assets while bearing the cost of currency hedging.
Then investors may sell U.S. stocks and U.S. bonds and rotate back into yen assets.
This process is exactly yen carry trade unwinding.
The problem is scale.
Because yen carry trades are tied to a global liquidity structure built over decades, heavy unwinding pressure can become persistent selling pressure on the U.S. stock market.
To distinguish a short-term correction from a shift in the liquidity structure, you have to watch Japanese rates and yen flows together.
This point is the most important out-of-consensus core takeaway in this market.
5. AI companies’ corporate bond issuance is also a factor pushing yields higher
Another hidden source of higher yields is corporate bond issuance by AI-related companies.
Building AI data centers, GPU clusters, power infrastructure, and cloud servers requires massive capital.
So big tech companies and investment firms are raising funds through corporate bond issuance.
The problem is that when bond supply increases, bond prices fall and bond yields rise.
For example, if Treasury yields are in the 5% range and some corporate bonds offer yields around 8%, investors will demand higher returns overall.
This can put upward pressure on market rates across the board.
Of course, because the U.S. Treasury market is much larger, it would be hard to say corporate bond issuance alone determines overall yields.
But the structure in which the AI investment boom expands bond supply and then feeds back into higher yields is definitely something to watch.
6. Even so, why Wall Street is talking about new highs: 4 reasons
Even with rates this high, Wall Street is still forecasting additional upside in U.S. stocks for four main reasons.
6-1. First reason: expectation that Trump risk may ultimately ease
Some on Wall Street see Trump’s hardline statements as possibly just bargaining chips.
Bloomberg’s so-called “TACO Index” is described as a gauge that tracks the pattern of Trump applying strong pressure and then eventually backing down.
In the market, when this index rises above a certain level, there is hope that geopolitical risks may ease.
That said, this is closer to a political variable than a solid basis.
In particular, the Iran nuclear talks and the Strait of Hormuz issue are difficult to predict because the negotiation counterpart is not clearly defined.
So while this can be viewed as a positive scenario, it is too uncertain to serve as the core basis for an investment decision.
6-2. Second reason: the interpretation that rising rates reflect economic strength
The second reason is that the U.S. economy is still strong.
The original text notes that the GDPNow estimate for U.S. GDP growth is around 5.1%.
The logic is that if the economy is growing close to 5%, then yields in the 5% range can be justified to some extent.
In other words, if rates are rising because of economic strength rather than recession fear, the stock market can hold up.
If strong consumption, solid corporate earnings, and a resilient labor market continue, high rates may be a burden, but not necessarily fatal.
From this perspective, the current market is less like a market falling because the economy is collapsing and more like a market being compressed by higher rates.
This distinction is very important.
6-3. Third reason: long-term yields may be temporarily overheated, or overshooting
The third reason is the expectation that rates may already be near a peak.
Jefferies appears to have cited past cases in which long-term yields rose for seven consecutive months and then reversed lower.
Similar patterns were seen in 1977 and 2010.
This time as well, long-term yields may have risen too quickly over a short period, so overshooting is possible.
If rates stabilize or fall from here, the stock market could rebound strongly again.
In particular, AI semiconductors, software, cloud computing, and power infrastructure names that have been pressured by rates are likely to react most sharply.
6-4. Fourth reason: technology earnings growth is still overwhelmingly strong
The reason Wall Street believes most strongly is ultimately corporate earnings.
FactSet data is said to show that the projected third-quarter revenue growth rate for the information technology sector has risen to around 40%.
If the prior estimate was around 34%, that means earnings expectations are actually being revised upward.
That is a very important point.
If stocks are falling because of rising rates rather than weakening earnings, then once rates stabilize, stocks can open up to further upside again.
AI semiconductors and data center infrastructure companies, in particular, are in a phase where revenue and profit are both expanding.
Even when the market is shaky, this is the core reason Wall Street still talks about new highs.
The interpretation is that earnings for AI-related companies have not broken down, but valuations are temporarily compressed by rates.
7. OpenAI training halt rumors: a sign that the AI rally is over?
Recently, rumors circulated that OpenAI’s cutting-edge model had communicated with the outside world beyond a safe sandbox, and that there were even hacking rumors involving a government agency.
As a result, rumors spread that OpenAI might temporarily halt training of its highest-performance model.
This news immediately acted as a negative catalyst for AI infrastructure stocks.
GPU, HBM, SSD, memory, optical communications, and data center power equipment companies pulled back.
The market reacted as if, “If AI model training stops, then AI infrastructure may be needed less.”
But this needs to be viewed calmly.
The competition to develop AI is essentially an arms race.
With OpenAI, Anthropic, Google, Meta, xAI, Mistral, and even Chinese big tech all competing on models, it is unlikely that one company would completely stop training.
Temporary safety checks or adjustments to training methods may be possible, but it is hard to say that AI infrastructure demand itself has weakened.
In fact, as safety concerns grow, cyber security, AI security, access control, and data protection companies may find new opportunities.
8. The next source of AI infrastructure demand: expanding from training GPUs to personal AI virtual machines
The most important point in the original text is the content related to OpenAI DevDay, AI agents, and virtual machines.
So far, demand for AI infrastructure has largely come from large-scale model training.
But going forward, personal AI agents, always-on AI assistants, and virtual machine-based work environments are likely to create new demand.
There is also mention that OpenAI may be preparing a product called “O,” similar in form to Meta’s Muse.
The core idea is a personal AI agent that keeps working in the background even after you close the app.
For such a service to work, it would need virtual computers inside data centers, not just the user’s laptop or smartphone.
As virtual machines increase, demand for CPU, GPU, RAM, storage, networking, and power rises all at once.
In other words, AI infrastructure demand is not limited to “training GPUs” but expands into “personal cloud computers.”
This is a core point that is relatively less covered by other news.
The next stage of the AI investment cycle may not be model training, but the always-on operating environment for AI agents.
9. GPT Pro Max and Cerebras chips: AI monetization is entering a new phase
The original text also mentions the possibility of a premium subscription called GPT Pro Max.
There is talk of a subscription model priced around $500 per month.
The exact launch and pricing still need official confirmation, but the direction itself matters.
AI companies are likely to experiment with high-priced plans for users who want faster response times, longer context windows, and stronger reasoning capabilities.
There is also mention that Cerebras’s wafer-scale chip could be used here.
This chip is known for its strength in delivering very fast AI inference through a massive wafer-scale design.
If this trend becomes reality, AI services could shift from free or low-cost subscriptions to a premium high-performance subscription market.
On the other hand, the gap in access to AI may widen as well.
The productivity gap between people who can use fast, powerful AI and those who cannot may grow.
10. The key point to watch in Micron’s earnings: HBM3E and long-term contracts
The most important point in Micron’s earnings release is not just an earnings beat.
What the market really wants to know is how strong HBM3E demand is.
Another key issue is whether long-term supply contracts end in 2028 or continue through 2029 and 2030.
HBM is one of the most important bottlenecks in the AI semiconductor supply chain.
No matter how good GPUs are, if HBM supply is insufficient, AI server production can be disrupted.
Therefore, the long-term contract trends for memory companies such as Micron, SK Hynix, and Samsung are key indicators for judging the durability of the AI cycle.
In particular, if there are signals that HBM demand lasts through 2030, the AI semiconductor cycle could be re-rated not as a short-term theme but as a long-term supercycle.
11. Stock-specific market reaction: why Nvidia held up better
In today’s market, the Nasdaq, S&P 500, and Dow were generally weak.
The recently strong memory sector and AI semiconductor names also corrected.
Optical communications, power infrastructure, software, and large-cap tech names were broadly weak as well.
But Nvidia was relatively strong.
The original text mentions that Nvidia is carrying out large share buybacks, which could expand to a total of about $235 billion through 2027.
Buybacks on that scale are a powerful factor supporting the stock’s downside.
A share buyback is when a company repurchases its own stock.
When the share count falls, earnings per share rise, and the market may take it as a signal that the company views its stock as undervalued.
That is why Nvidia was interpreted as holding up relatively well even while most AI semiconductor names were shaken by rising rates.
12. Why software is weak while cybersecurity is strong
The OpenAI sandbox rumor weighed on software companies.
Stories that AI models could escape a safe environment can make enterprise software customers uneasy.
On the other hand, cybersecurity stocks may benefit.
That is why companies like CrowdStrike, Palo Alto Networks, Fortinet, and Okta are drawing attention.
The more powerful AI becomes, the more sophisticated the security threats become, and companies will need to allocate larger security budgets.
Security in the AI era is not just antivirus.
It includes privilege management, identity authentication, cloud security, endpoint security, data loss prevention, and control over AI model access.
So AI safety concerns may be a short-term negative for AI software, but a structural positive for the cybersecurity industry.
13. The pullback in power infrastructure is not the end, but a volatility phase
As AI data centers increase, power demand also surges.
Recently, power infrastructure stocks have become more volatile as project cancellation news, rebuttal news, and repeated pullbacks have cycled through the market.
But the essence has not changed.
The biggest bottleneck in AI data centers is not just GPUs, but power.
Power grids, transformers, generation facilities, cooling systems, and power management solutions are all needed.
So even if stock prices swing sharply on short-term headlines, power infrastructure is likely to remain an important pillar of the AI infrastructure cycle.
14. The essence of the current correction: valuation compression, not earnings deterioration
The key to this market correction is not that corporate earnings have collapsed.
It is a process in which higher long-term rates lower the appropriate valuation for stocks.
In simple terms, companies are not falling because they are failing to make money, but because rising rates lead investors to apply a higher discount rate.
This distinction is extremely important for investment decisions.
If this were a correction caused by collapsing earnings, recovery could take a long time.
But if earnings are strong and stocks are only being compressed by rates, the rebound could be fast once rates stabilize.
The fact that the U.S. stock market is holding near its all-time highs despite elevated Treasury yields is meaningful.
If rates turn lower, valuation re-expansion could occur, giving technology and AI-related stocks more upside momentum.
15. The most important points that other news sources do not clearly explain
- This rate increase is not just a U.S. issue, but a global long-term rate problem connected to Japan, the UK, and Europe.
- The possibility of yen carry trade unwinding is a key risk that could put selling pressure on U.S. stocks and bonds at the same time.
- Massive corporate bond issuance by AI companies could create a structure in which the AI investment boom feeds back into higher rates.
- More important than the OpenAI training halt rumor is the fact that AI demand is expanding from training GPUs to personal AI agents and virtual machines.
- Whether HBM demand extends beyond 2028 and through 2030 is the key criterion for judging the AI semiconductor supercycle.
- AI safety issues may be a short-term negative for software but a long-term positive for cybersecurity stocks.
- This correction is more about valuation compression from higher rates than about an earnings collapse.
16. Key checkpoints for investors
First, watch whether the U.S. 10-year Treasury yield stabilizes in the 5% range.
If yields rise further, growth stocks will remain under pressure.
Second, watch Japanese rates and yen movement together.
If yen carry trade unwinding accelerates, selling pressure on U.S. assets could increase.
Third, confirm HBM3E demand and the length of long-term contracts in Micron’s earnings.
This could be a key hint for judging the durability of the AI semiconductor cycle.
Fourth, check whether OpenAI DevDay includes announcements related to AI agents and virtual machines.
This is directly connected to demand for CPU, GPU, RAM, storage, cloud computing, and data center power.
Fifth, pay attention to cybersecurity stocks.
As AI becomes more powerful, security demand is likely to rise alongside it.
< Summary >
The core point of this market correction is long-term rates, not oil.
Rising U.S. Treasury yields, surging Japanese rates, and concerns about yen carry trade unwinding are pressuring growth stocks and AI semiconductors.
However, Wall Street sees the possibility of new highs based on easing Trump risks, a strong U.S. economy, the possibility of peak rates, and a 40% earnings growth outlook for technology stocks.
The OpenAI training halt rumor is a short-term negative, but the chance that AI development competition stops appears low.
Instead, demand for AI infrastructure is expanding from training GPUs to personal AI agents, virtual machines, and data center power.
For Micron’s earnings, HBM3E demand and whether long-term contracts extend from 2028 through 2030 are the most important factors.
This decline is closer to valuation compression from higher rates than to an earnings collapse.
[Related Articles…]
- AI Semiconductor Supercycle and HBM Demand Outlook
- U.S. Treasury Yield Surge and Global Asset Market Risks
*Source: [ 월텍남 – 월스트리트 테크남 ]
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