AI Panic, Hynix Slumps

● AI Slowdown Panic, SK Hynix Slumps

AI Development Slowdown Debate Triggers Sharp Decline in SK Hynix Perpetual Futures; the Main Risk Is Investor Sentiment, Not Semiconductor Demand

The core issue is not simply that semiconductor stocks moved on a single call to slow AI development.
Over the weekend, while regular equity markets were closed, perpetual futures on crypto exchanges for SK Hynix, Micron, and other AI semiconductor names fell by roughly 4% to 5%.
The immediate trigger was Anthropic CEO Dario Amodei’s remarks on slowing the pace of frontier AI development.
However, the key factors to monitor are AI safety regulation, Big Tech data center investment, China-related AI restrictions, the semiconductor demand cycle, and global equity market sentiment, all of which are now intertwined.
This episode should also be viewed through the lens of possible “regulation as a tool to raise barriers,” as well as political messaging aimed at constraining China’s AI industry.

1. What Happened in the Weekend Perpetual Futures Market

During the weekend, perpetual futures tied to SK Hynix, Micron, and other major semiconductor names declined sharply.
Although regular stock markets were closed, equity-linked perpetual futures on crypto exchanges trade 24/7.
These products allow traders to take long or short exposure to stock prices using stablecoins such as USDT as collateral.
In practice, they function as derivative instruments for directional views on equities within crypto markets.

SK Hynix-related perpetual futures declined over the weekend.
Micron and other AI semiconductor names followed a similar pattern.
The decline was broadly in the 4% to 5% range.
Because this is not regular-session trading, it is not directly equivalent to actual share-price movement.
Still, it is often used as a reference for global risk sentiment over the weekend.

A key point is that the dominant participants in this market are not institutional investors.
Perpetual futures markets tend to be driven largely by retail traders and short-term speculators who react quickly to risk events.
As a result, the opening direction in regular equity trading can differ materially once actual market volume enters the picture.

2. Direct Trigger: Dario Amodei’s Call for Slower AI Development

The immediate catalyst was a post by Anthropic CEO Dario Amodei.
He argued that frontier AI research labs such as OpenAI, Anthropic, and Google DeepMind should moderate the pace of AI development to some extent.
Frontier AI refers to the most advanced models currently being developed.
In other words, the call was to slow the competition in leading-edge models such as GPT, Claude, and Gemini.

The market reaction intensified because several industry leaders appeared to align with the message.
OpenAI CEO Sam Altman, Elon Musk, and Google DeepMind’s Demis Hassabis were reported to have responded in ways that reinforced the same broad direction.
Investors interpreted this not as an isolated opinion, but as a coordinated signal from the top tier of the AI industry.

Slowing AI development implies lower near-term demand for GPUs.
It may also imply slower growth in data center investment.
That, in turn, can pressure semiconductor valuations.

This logic explains why SK Hynix and Micron were among the first names to weaken in weekend futures trading.
SK Hynix, in particular, is highly sensitive to changes in AI investment sentiment due to its exposure to the HBM supply chain and Nvidia-linked demand.

3. Why Amodei Advocated Slower AI Progress

Amodei’s position appears to be driven by two major concerns.
The first is recursive self-improvement.
The second is the risk that AI could be used for cyberattacks or other security threats.

3-1. Recursive Self-Improvement: AI Building Better AI

Recursive self-improvement is one of the most sensitive concepts in Silicon Valley.
It refers to AI systems that can help develop and improve the next generation of AI models.
Current AI systems already have coding capabilities.
In the end, AI models are built from code, algorithms, data, and infrastructure.

If AI systems begin to create better AI systems, and those improved systems then accelerate the next iteration, the pace of development could become difficult for humans to forecast or control.
This is the core risk Amodei appears to be highlighting.
The concern is that AI development may evolve from ordinary software innovation into a race with potentially uncontrollable speed.

3-2. Cybersecurity Risk: Fear of Behavior Outside Human Control

The second concern is that AI could be used in cyberattacks or hacking attempts.
Cases involving OpenAI and Hugging Face-related cybersecurity concerns have reinforced the view that AI can be linked to security threats.
The market has increasingly recognized the possibility that AI systems may be used in ways that are difficult to contain.

Amodei’s argument is that if AI is advancing rapidly and may also create security risks, stronger safeguards are necessary.
His position is therefore not limited to ethical concerns, but extends to institutional oversight and control mechanisms.

4. Core Policy Measures He Proposed

Amodei did not call for a full halt to AI development.
His position was closer to stronger safety evaluation and international coordination.
However, the market interpreted the message as a call to slow the pace of AI progress.
For semiconductor stocks, even that wording can be negative.

Resident evaluator system
A third party would be embedded within AI research labs to assess development and safety processes.
The proposal calls for access close to that of internal employees to ensure meaningful oversight.
Stronger pre-release safety validation
Frontier models should undergo risk assessment and controllability checks before launch.
International coordination among democratic countries
The US and allied countries should jointly establish AI safety standards and cooperate on enforcement.
Constraints on China
The proposal assumes that the West should remain ahead of China even if it moderates its own pace.

5. Why China Remains Central to the Debate

Any discussion of slower AI development quickly connects to China.
If the US and other Western countries slow down while China continues advancing, the balance in AI competition could shift.
That is why China-related language appeared in the debate.

Restrict China’s access to advanced semiconductors.
Strengthen export controls on AI chips.
Prevent Chinese firms from distilling Western AI models.
Block model-weight theft.
Maintain Western technological advantage to preserve negotiation leverage.

Distillation refers to training smaller models using the outputs or knowledge of more powerful AI systems.
There is concern that Chinese AI companies could use this method to narrow the gap quickly.
Amodei’s view is that restricting such pathways is necessary to slow China’s catch-up process.

6. Why Semiconductor Stocks Sold Off First

Semiconductor stocks sit at the front end of the AI investment cycle.
As Big Tech builds larger AI models, spending rises on GPUs, HBM, servers, networking equipment, power infrastructure, and data centers.
SK Hynix is widely regarded as a key supplier in the HBM segment.

Accordingly, the phrase “slower AI development” is quickly translated into a chain of potential implications.

Possible slowdown in AI model development
Possible slowdown in GPU purchasing
Possible deceleration in HBM demand growth
Reassessment of data center spending
Concerns about a peak in the semiconductor cycle
Deterioration in investor sentiment toward semiconductor equities

Semiconductor stocks were already trading in an environment where sentiment was not fully constructive.
Strong AI demand had been largely priced in, and investors were debating whether expectations had already run ahead of fundamentals.
In that context, remarks from top AI executives on slowing development were enough to trigger a cautious response.

7. However, Near-Term Fundamental Damage Appears Limited

This is a negative short-term development.
That said, it remains unlikely that Big Tech will abruptly reduce semiconductor purchases or materially slow AI investment next year.
The reason is game theory.

If Anthropic slows down, will OpenAI really do the same?
If OpenAI slows down, will Google, Meta, xAI, Amazon, and Microsoft all pause together?
If US firms slow down, will China do the same?
In practical terms, that is unlikely.

AI is not just a technology race; it is tied to national competitiveness, cloud computing, search, enterprise software, defense, and cybersecurity.
The economic payoff for the winner is too large for the competition to stop easily.
Even when companies say that safety matters, investment competition tends to continue.

8. The Real Risk Is Investor Sentiment, Not Demand

The core issue is not whether semiconductor earnings deteriorate immediately.
The market is more likely to reprice valuations if it begins to question the durability of the AI semiconductor cycle.
Investors buy equities based on future earnings potential.
If that future revenue outlook becomes uncertain, valuations adjust first.

One challenge for semiconductor equities is that earnings verification takes time.
Investors need time to confirm whether 2026, 2027, and 2028 revenue expectations remain intact.
By contrast, stock prices move now.
That time gap is often the most difficult part of the investment case.

For this reason, the current event should be viewed less as a direct hit to fundamentals and more as a sentiment-driven shock to an already sensitive market.
That effect can be especially pronounced in high-valuation AI semiconductor names.

9. The Most Important Point Missing From Many Reports

The key issue is not only AI safety, but also industrial strategy.
Many reports frame the story as a simple link between AI moderation and lower semiconductor prices.
A deeper reading suggests that established players may use the regulation narrative to raise barriers to entry.

9-1. Possible Barrier Raising Through Regulation

OpenAI, Anthropic, and Google DeepMind already have substantial capital and infrastructure.
They grew rapidly during a period of relatively lighter regulation.
If every model launch now requires external evaluation, resident oversight, and formal safety checks, smaller firms may find the process difficult to absorb.

If each release adds significant compliance cost, startup competition becomes harder.
In that sense, safety regulation can also work to the advantage of large incumbents and frontier AI leaders.
That is the logic behind the barrier-raising argument.

9-2. Possible Signaling to Intensify China Restrictions

Amodei’s comments also included the need to slow China’s AI progress.
This is not only a safety issue; it is also a geopolitical strategy issue.
The message may be intended to push the US government and allied countries toward tighter export controls, stronger model-weight security, and more aggressive limits on distillation.

In other words, the public message may be “slow down because AI is risky,” while the strategic objective could be “tighten controls so China cannot catch up.”
That distinction matters for semiconductor investors.
Tighter China restrictions may create short-term demand concerns, but they can also reinforce a Western-centered AI supply chain over time.

9-3. Possible Effort to Ease Data Center Spending Pressure

One market interpretation is that AI firms may not be trying to stop development for safety reasons alone.
They may also want to ease the burden of next-generation model training and data center spending.

AI companies are spending heavily on GPUs, power, servers, data centers, and talent.
Framing a slowdown as a safety measure gives the decision more legitimacy than simply saying that costs are too high.
This interpretation is plausible.

9-4. Possible Desire to Stabilize Current Monetization

Another interpretation is that major AI companies want more time to monetize their current models.
If the next model arrives too quickly, the commercial life of the existing model shortens.
Development costs continue to rise while the payback period becomes shorter.

Slowing the pace for a period could allow companies to expand enterprise adoption, API revenue, and subscription revenue from the current model set.
In that scenario, safety language may also serve as a mechanism to support profitability and industry-wide pacing.

10. Why Trump’s AI Remarks Matter

Trump responded to a question about whether AI development should slow by emphasizing that the winner in AI ultimately prevails.
The message was interpreted as an indication that the US cannot afford to fall behind in the AI race.
While safety measures may be necessary, the administration is unlikely to adopt an aggressively anti-growth stance toward AI.

This is important for policy expectations.
A major US government-led slowdown in AI development appears unlikely.
The more probable outcome is continued support for AI industry expansion within the broader US-China technology competition.

11. What SK Hynix Investors Should Watch

For SK Hynix and semiconductor investors, the weekend futures decline is only one data point.
The more important indicators are regular-session trading volume, foreign inflows, HBM demand expectations, and Big Tech capital expenditure plans.

Regular-session trading volume
Whether the futures decline leads to actual selling in the cash market.
Nvidia and Big Tech CAPEX
Whether capital spending plans at Microsoft, Google, Amazon, and Meta remain intact.
HBM supply contracts
Whether SK Hynix maintains delivery schedules and pricing power.
Actual strength of AI regulation
Whether the discussion remains rhetorical or becomes binding policy.
China policy direction
Whether tighter export controls hurt near-term revenue or support long-term supply chain reconfiguration.

12. Is the Current Semiconductor Pullback Fear or Opportunity?

This is not a positive development.
In the short term, it is likely to weigh on semiconductor stocks.
However, it does not necessarily signal the end of the AI semiconductor cycle.

The central question is whether AI development can actually be slowed in a meaningful way.
In practical terms, that appears difficult.
Big Tech investment, cloud competition, national security concerns, China-related strategy, and enterprise AI demand all remain aligned in favor of continued spending.

Accordingly, this looks more like a sentiment-driven correction than a fundamental break.
Still, sentiment corrections can be substantial when valuations are elevated.
Investors should therefore consider both long-term AI demand and short-term volatility management.

13. Final Watch Point: The Market Ultimately Wants Numbers

Going forward, the market will focus on actual data rather than statements.
It will watch whether Big Tech reduces data center spending, whether Nvidia order trends weaken, and whether SK Hynix’s HBM shipment outlook changes.

If Big Tech CAPEX remains intact and HBM demand stays strong, this event may fade into short-term noise.
If AI safety regulation leads to delayed investment and slower data center expansion, semiconductor valuations may face a longer adjustment period.

In conclusion, this event does not necessarily indicate that AI growth has ended.
It does suggest that the AI investment cycle is increasingly colliding with politics, regulation, geopolitics, and capital intensity.
Semiconductor stocks are therefore becoming an asset class that must be analyzed alongside the broader macroeconomic outlook, technology competition, AI regulation, and US market liquidity.

< Summary >

Over the weekend, perpetual futures tied to SK Hynix, Micron, and other AI semiconductor names declined sharply.
The immediate trigger was Anthropic CEO Dario Amodei’s call to moderate frontier AI development.
The market interpreted this as a potential slowdown in AI investment, GPU demand, and HBM demand growth.
However, a broad halt in AI competition by Big Tech or China remains unlikely.
The main risk is not a sudden deterioration in fundamentals, but weaker investor sentiment.
A more important issue is that AI safety regulation may also function as a barrier to entry, a tool for China containment, or a rationale to ease data center spending pressure.
Investors should focus on actual trading volume, foreign flows, Big Tech CAPEX, and HBM order trends in regular-session trading.

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*Source: [ 내일은 투자왕 – 김단테 ]

– 인공지능 개발 멈추자?에 하이닉스 무기한 선물 폭락

● Fed-Rate-Shift, Inflation-Spillover, Oil-Driven-Shock

9월 FOMC rate-hike pivot risk, and why the key issue is not CPI itself but whether inflation is broadening

The three points that matter most in this article are as follows.

First, whether the August CPI report was truly a rate-hike signal.

Second, why CME FedWatch probabilities and U.S. Treasury yield movements delivered different messages.

Third, the key issue the market is largely missing: whether higher crude oil prices have spread into core inflation and services inflation.

The bottom line of the original analysis is that a September FOMC rate hike is less likely than a hold.

That said, this is not a matter of right or wrong, but of how the Federal Reserve prioritizes data.

In particular, many market participants focused too heavily on a single month-over-month number in the CPI release, while the Fed’s inflation assessment is structurally closer to year-over-year trends.

For that reason, the September FOMC outlook should not be reduced to the simple conclusion that “higher CPI means a rate hike.”

U.S. inflation, crude oil, Treasury yields, the policy rate, and the AI semiconductor earnings season must all be considered together to understand the next market direction.

1. Did the August CPI beat or match expectations?

The starting point for this debate is the August CPI release.

Following the data, the market interpreted the report as increasing the odds of a September FOMC rate hike.

However, the original analysis takes a different view.

CPI can be divided into four measures.

Headline CPI year over year
Headline CPI month over month
Core CPI year over year
Core CPI month over month

In this release, three of the four measures were broadly in line with expectations.

The exception was core CPI month over month.

The market had expected a 0.2% increase, but the actual result was 0.3%.

This single print led to the “CPI shock” narrative.

However, the original analysis argues otherwise.

If three of four measures were in line, and the year-over-year measures, which the Fed emphasizes more, also matched expectations, then it is more reasonable to conclude that the report was broadly in line overall.

In other words, it is difficult to infer a clear rate-hike pivot from one month-over-month figure alone.

2. The Fed watches inflation levels less than inflation rates

One concept is critical here.

The Federal Reserve does not exist to lower the price level itself.

What the Fed targets is the rate of inflation, not the absolute level of prices.

For example, if burger meals, coffee, and restaurant spending feel more expensive, that is valid from a consumer perspective.

But for monetary policy, the key issue is how much prices have risen versus a year earlier.

If the central bank had to raise rates every time prices became expensive, it would need to hike almost every year.

That is because the price level in most economies rises over time.

The Fed’s objective is not to return prices to prior levels, but to stabilize inflation near 2%.

Without this distinction, it is easy to drift into the simplistic conclusion that “prices are still high, so rates must rise.”

In practice, FOMC rate decisions are much more nuanced.

3. Why year-over-year matters more than month-over-month

Month-over-month data captures short-term volatility.

For that reason, it can drive market reactions on the day of release.

However, when the Fed evaluates its long-term inflation objective, it places greater weight on year-over-year trends.

The Fed’s 2% price-stability target is also fundamentally a year-over-year concept.

GDP growth, corporate earnings growth, and CPI inflation are all primarily interpreted using year-over-year comparisons in a longer horizon.

The original text emphasizes this point strongly.

Month-over-month data can matter on release day, but inflation history is recorded in year-over-year terms.

Therefore, a core CPI print that was only 0.1 percentage point above expectations does not by itself justify the conclusion that the Fed will immediately shift to a rate hike.

4. CME FedWatch is not the FOMC outcome, but a futures-market bet

Many investors looked at CME FedWatch and concluded that the probability of a September FOMC rate hike had become very high.

The original analysis notes that FedWatch implied a rate-hike probability above 87%.

The hold probability was reflected at roughly 12%.

However, one important point must be made.

FedWatch is not the Federal Reserve’s official outlook.

It is a probability derived from 30-day federal funds futures prices.

In simple terms, it reflects where futures traders are placing their bets.

This probability changes daily.

And historically, it has often been wrong.

Therefore, a high FedWatch probability does not mean the FOMC will necessarily hike rates.

FedWatch is an important reference, but not the final conclusion.

5. The more important market signal was U.S. Treasury yields

The original analysis placed more weight on Treasury yields than on FedWatch.

Immediately after the CPI release, the U.S. 10-year Treasury yield fell sharply.

The 2-year Treasury yield also declined after the release.

The implication is straightforward.

The bond market did not initially interpret the CPI report as a shock that would force a stronger rate-hike response.

If the CPI had truly delivered a much stronger-than-expected inflation signal, Treasury yields would likely have risen sharply on release.

Instead, they fell.

There was a later move higher in yields, but the original analysis attributes that more to crude oil, Middle East risk, Treasury supply, and fiscal concerns than to CPI itself.

In other words, the first market reaction was closer to a report that broadly matched expectations.

6. U.S. inflation remains in a disinflationary phase over the long term

U.S. CPI reached 9.1% in June 2022, the highest in 41 years.

At that time, the Fed responded with aggressive rate hikes.

As a result, the policy rate rose to the mid-5% range, and inflation gradually eased thereafter.

The original analysis describes this as a disinflationary phase.

Disinflation does not mean prices are falling.

Prices may still rise.

It means that the pace of inflation is slowing.

Although Middle East conflict and surging crude oil created a temporary distortion, the broader U.S. inflation trend remains disinflationary.

In particular, a decline in core CPI from 2.9% toward 2.6%, 2.5%, and 2.4% supports a hold rather than a hike.

7. The key point overlooked by many reports: oil did not broadly spill into other prices

This is the most important point in the analysis.

Higher crude oil prices can pressure headline CPI.

But the real inflation risk emerges when energy prices spill into food, core goods, core services, wages, and housing costs.

The original text argues that the latest CPI data did not show a broad transmission of energy price increases into other categories.

This matters because the Fed is concerned not with a temporary energy shock, but with broad-based inflation diffusion.

If energy prices rise while core services and core goods remain stable, the case for further tightening weakens.

In particular, the slowdown in housing inflation to around 3.0% and the moderation in wage growth to around 3.1% are important.

Housing and wages are central components of services inflation.

If both are easing, the probability of a structural inflation reacceleration is limited.

This is one of the most underreported elements in market commentary.

8. Countries that need rate hikes are not in the same position as the United States

The original analysis compares the United States with Korea, the euro area, and Japan.

Korea faced inflation of around 3% with a policy rate of about 2.5%, creating a stronger case for rate hikes.

The euro area also encountered inflation from a low-rate environment, making tightening more defensible.

Japan has likewise been in a position that requires policy normalization from ultra-low rates.

The United States is different.

The U.S. has already maintained a relatively high policy rate.

In real rate terms, policy is already restrictive enough to weigh on inflation.

For that reason, it cannot be assumed that the U.S. must respond in the same way as Korea or the euro area.

Monetary policy is entering an era of differentiated rate paths across countries.

9. The FOMC internal balance is not straightforward

The original text also examines the views of FOMC members.

The Fed’s rate decision is not made by one person alone.

Board governors and regional Federal Reserve Bank presidents participate in the vote.

The New York Fed president is a permanent voting member, while other regional presidents participate on a rotating basis.

According to the original analysis, some members are closer to a hike, while others are closer to a hold.

Some are also classified as data-dependent rather than politically driven.

Several members already argued for a hike at the July FOMC.

But the data environment in July and September is not the same.

At that time, there was less confidence that inflation had peaked.

Now, however, the slowdown in core CPI, housing, and wages is more visible.

Therefore, members who favored a hike in July cannot be assumed to reach the same conclusion in September.

10. A hold probability of 55% and a hike probability of 45%

The original analysis concludes that a hold remains slightly more likely.

Roughly, the view is 55% for a hold and 45% for a hike.

This does not mean a hike is impossible.

A further rise in crude oil could reawaken inflation expectations.

The Fed could also choose a preemptive or insurance hike.

Political considerations cannot be ruled out entirely.

However, from a pure monetary-policy perspective, the case for a hike is not strong in the current data.

Policy is already restrictive, and core inflation, wages, and housing are easing.

11. The claim that higher policy rates are needed to stabilize Treasury yields is not well founded

The market also holds another common misconception.

That is, the idea that the Fed must raise rates to stabilize Treasury yields.

The original analysis views this as a flawed sequence.

U.S. Treasury yields rise for two main reasons.

Rising inflation expectations
Worsening supply-demand conditions due to higher Treasury issuance and weak demand

If Treasury yields are already pricing in some degree of rate hikes, then a failure to hike at the FOMC could actually stabilize yields.

Conversely, if the market concludes that the Fed has lost control of inflation, yields could rise again even after a hold.

In other words, it is not correct to assume that a hold always means higher yields, or that a hike always means stable yields.

What matters is whether the market still trusts the FOMC decision.

That trust depends not only on CPI, but also on inflation diffusion, expectations, Treasury supply, and fiscal policy.

12. In October, earnings season may matter more than the FOMC

The original text also highlights the October calendar.

After the September FOMC, market attention is likely to shift quickly to earnings season.

AI semiconductors and large-cap technology earnings will be especially important.

October 6-8: Preliminary earnings release expected for Samsung Electronics
Late October: Final earnings release expected for Samsung Electronics
October 21-27: Earnings release expected for SK hynix
October 15: TSMC earnings release scheduled
October 29: Earnings releases from Alphabet, Microsoft, Meta, and other major platforms
October 30: Earnings releases from Amazon and Apple scheduled
October 29: U.S. GDP release scheduled

October 29 is a particularly important date.

That is when earnings from Alphabet, Microsoft, and Meta could confirm the pace of AI infrastructure spending.

AI semiconductor demand, data center investment, cloud growth, advertising trends, and consumer demand may all become visible.

From that point, corporate earnings may drive equity direction more strongly than macro data.

Samsung Electronics and SK hynix are directly linked to AI memory, HBM, and server demand.

TSMC is a key indicator of the global AI semiconductor cycle.

After the September FOMC, investors should therefore focus more on earnings quality than on rates.

13. Key items for investors to monitor

Investors should focus on the following points in assessing the September FOMC and the CPI release.

Whether year-over-year CPI trends matter more than month-over-month CPI
Whether core CPI resumes an upward trend
Whether higher crude oil prices spill into food, goods, and services inflation
Whether housing inflation and wage growth continue to moderate
Whether inflation expectations rise again
How the 2-year and 10-year Treasury yields react after the FOMC
Whether October AI semiconductor and large-cap technology earnings show signs of demand slowdown

Viewing the issue only as a binary choice between a hike and a hold oversimplifies the market interpretation.

The key question is which data the Fed prioritizes, and whether those data actually point to a renewed inflation cycle.

14. The core view of this analysis

The core view of the original analysis is not a claim that a hold will definitely occur.

No one can know the FOMC outcome with certainty.

Even Fed officials cannot fully know the final vote before it takes place.

What matters is the basis for the judgment.

The analysis gives slightly more weight to a hold, based on current CPI trends, easing core inflation, stabilizing housing and wages, limited energy spillover, and the existing policy rate level.

That said, a rate hike remains possible if crude oil rises further, geopolitical risk intensifies, inflation expectations climb again, or political considerations become more relevant.

For that reason, this FOMC is not just a rate event, but a test of how the Fed distinguishes between an energy shock and true inflation.

< Summary >

In the August CPI report, only core CPI month over month came in above expectations, while the other key measures were broadly in line.

The Fed focuses on inflation rates rather than price levels, with year-over-year trends carrying greater weight.

CME FedWatch reflects futures-market positioning, not the actual FOMC decision.

The decline in U.S. 10-year and 2-year Treasury yields immediately after the CPI release suggests the market did not treat the report as a major shock.

The most important issue is that higher crude oil prices did not broadly spill into core goods, core services, food, wages, or housing inflation.

Accordingly, from a monetary-policy perspective, a September FOMC hold is slightly more likely than a hike.

However, geopolitical risk, renewed inflation expectations, and possible political considerations still leave room for a hike.

After the September FOMC, the October earnings season for Samsung Electronics, SK hynix, TSMC, and major U.S. technology companies is likely to become the main market driver.

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*Source: [ 경제 읽어주는 남자(김광석TV) ]

– [생방송] 9월 FOMC ‘금리인상 급선회’ 사실인가? [즉시분석]

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