On July 24, 2026, a major announcement at the San Francisco AI Summit sent shockwaves through the industry: South Korea’s Samsung Electronics and SK Group, together with leading US tech giants, unveiled a semiconductor partnership valued at a staggering $950 billion. As part of the deal, SK Group will supply $750 billion worth of chips to US tech companies like NVIDIA, while Samsung Electronics signed a $200 billion memorandum of understanding with Broadcom for advanced memory chip supply and AI chip foundry services.
Yet, the capital markets responded in the opposite direction. By the close of US trading that same day, SK Hynix ADR (SKHY) ended at $154.57, plunging 8.81% in a single session. The next day (July 27), Korea’s KOSPI index fell nearly 2% intraday, with SK Hynix dropping another 3% and Samsung Electronics sliding more than 1%.
Why are massive AI chip orders no longer driving share prices higher? This question highlights a profound shift in the valuation logic of the AI semiconductor sector.
Paradigm Shift in Market Logic: From "Concept Pricing" to "Performance Validation"
Over the past two years, AI semiconductor stocks have followed a clear pricing chain: AI concept hype → order growth expectations → rising share prices. During this phase, the market was willing to pay a premium for the "story" and "potential," generously discounting future profits.
But as we enter the second half of 2026, this transmission chain is breaking down. The new logic has become: AI concept → order growth → profit margin validation → cash flow validation → valuation repricing. The market is no longer satisfied with order volume alone; investors now demand to see these orders translate into sustainable profits and positive cash flow.
This shift is driven by multiple factors. In the first half of 2026, shares of AI leaders like Samsung, SK Hynix, NVIDIA, and AMD soared as optimism about AI computing power fueled rapid valuation increases. But in the second half, the narrative changed—capital began to scrutinize the authenticity of orders and the sustainability of profits.
At the same time, cloud service giants are feeling the squeeze of capital expenditures. While Google raised its 2026 capex guidance from $180–190 billion to $195–205 billion, its free cash flow fell to -$5.9 billion, turning negative for the first time. This has deepened investor concerns about the sustainability of massive enterprise capex.
JPMorgan strategists recently warned of growing divergence within AI-themed stocks—chip and infrastructure suppliers continue to gain, while hyperscale cloud giants making heavy AI investments have stalled. As profit divergence across the supply chain peaks, the high valuations of upstream hardware lose their logical support.
The Dual Narrative of SK Hynix: Certainty of Gains vs. Valuation Pressure
Upside: Irreplaceable Leadership in HBM
Fundamentally, SK Hynix’s industry position is nearly unassailable. Industry data shows SK Hynix holds nearly 58% of the global HBM (High Bandwidth Memory) market, making it a core supplier for AI computing storage. IDC data also confirms the company controls 56% of the global HBM market.
On the demand side, HBM production capacity for the entire year is already fully booked, with tight supply persisting. SK Hynix’s 2026 HBM capacity is entirely sold out, with standard orders lined up through Q1 2027, and long-term agreements with key clients like NVIDIA locked in through the end of 2027. Its long-term AI storage partnership with NVIDIA aims to jointly develop next-generation HBM products to meet the computing needs of large language models, agent-based AI, robotics, and other emerging applications.
Market consensus estimates SK Hynix’s Q2 2026 revenue at 84.1 trillion KRW, with operating margins between 75% and 77%. These record-breaking profit forecasts reflect its absolute leadership in the HBM sector.
Downside: Valuation Overhang and Cyclical Peak Risk
However, strong fundamentals don’t always translate into strong share performance. The concerns facing SK Hynix are equally clear.
First, the stock has already seen outsized gains. Driven by AI demand, SK Hynix and Samsung Electronics have both rallied sharply this year. After such a run-up, any positive news may trigger profit-taking rather than further gains. US investors currently hold SK Hynix shares at a premium to the Seoul market, a gap that has widened since the company’s record-breaking Nasdaq listing in early July.
Second, positive news is already priced in. Despite the announcement of several major deals, SK Hynix shares have retreated, indicating that the benefits of the AI narrative are already well-reflected in current prices. The market’s lukewarm response to recent AI news shows investors are more focused on valuation correction risks after the sector’s rally.
Third, the cyclical curse of memory chips. The memory chip industry is highly cyclical. Investors worry that SK Hynix’s aggressive capacity expansion could lead to future oversupply, pushing chip prices into another downward cycle. When crowded leveraged positions face macro shocks, even minor "expectation adjustments" can trigger sharp, stampede-like sell-offs.
The Logic of Valuation Reset: From "Explosive Growth" to "Mature Growth"
The current correction in AI chip stocks doesn’t reflect a rejection of AI chip demand, but rather a shift in valuation methodology—from "explosive growth pricing" to "mature growth pricing." This transition often comes with significant capital rotation and price volatility.
Since July, global markets have begun correcting for overtrading along the price-hike chain, with AI hardware stocks—especially memory—seeing sharp adjustments. Investors are increasingly questioning the rationale behind the semiconductor sector’s aggressive investment cycle.
It’s worth noting, however, that some institutions see this correction as an "overreaction." BlackRock recently stated that the sharp sell-off in tech and semiconductor stocks is "overdone," warning that the market is conflating "changes in the AI competitive landscape" with an "AI investment collapse." Cheaper AI models, they argue, won’t reduce AI spending but may actually accelerate AI adoption across industries.
Bank of America believes memory chips are undervalued, trading at a forward P/E of just 10x, even as they account for 35–40% of AI capital expenditures. SK Hynix is expected to have a 2026 P/E below 6x—by traditional valuation metrics, not expensive at all.
Crypto Markets Under Pressure: Systemic Contraction in Risk Appetite
The valuation reset in AI chip stocks isn’t happening in isolation. On July 27, the cryptocurrency market also experienced choppy consolidation. Bitcoin (BTC) traded around $65,150, holding firm above the key $65,000 support. Ethereum (ETH) rebounded to about $1,935. The total global crypto market cap hovered around $2.21 trillion.
While prices remained relatively stable, market structure suggests risk appetite hasn’t meaningfully recovered. In the past 24 hours, $54.71 million in leveraged positions were forcibly liquidated, with 88.71% being short positions. Derivatives trading volume rose 10.61% day-over-day, indicating short-term volatility is far from over. The Fear & Greed Index remains in the "fear" zone.
Although crypto and AI chip stocks are different asset classes, both are considered risk assets. When global capital becomes less tolerant of high-valuation, high-expectation assets, both markets tend to come under pressure simultaneously. The valuation reset in AI semiconductors is, in some ways, a microcosm of the broader, systemic contraction in global risk appetite.
Conclusion
SK Hynix’s $950 billion AI chip mega-deal failed to lift its share price—a seemingly paradoxical outcome that, in reality, reflects the market’s inevitable shift from "concept-driven" to "performance-driven" pricing logic.
The market isn’t dismissing long-term AI chip demand. HBM capacity is sold out through 2027, SK Hynix is expected to post over 80 trillion KRW in quarterly revenue, and NVIDIA’s sweeping $500+ billion partnership with SK Group all point to robust fundamentals. But capital markets are no longer satisfied with "stories"; they want to see AI revenue translate into real profits and free cash flow.
The next key test is just around the corner. On July 29, SK Hynix will release its Q2 2026 financial results. Samsung Electronics and Kioxia will also announce their latest earnings. Whether these three reports can demonstrate that AI demand is still converting into HBM, DRAM, and enterprise SSD orders will directly impact the next phase for chip stocks.
For investors, the long-term industrial trend for AI semiconductors remains intact. However, the restructuring of valuation frameworks means the era of "buy and watch it rise" is over. In this new era of performance validation, only companies that can turn orders into profits and revenue into cash flow will regain the market’s favor.
FAQ
Q1: Why did SK Hynix’s $950 billion mega-deal fail to boost its share price?
Market logic has shifted from "concept-driven" to "performance validation." The $950 billion deal is a long-term framework agreement, and capital markets are more concerned about whether these orders can be converted into short-term profits and positive cash flow. At the same time, SK Hynix’s share price had already run up significantly, and the good news was already priced in.
Q2: How long will the valuation reset in the AI semiconductor sector last?
The duration of the valuation reset depends on the outcome of corporate earnings reports. The Q2 results from SK Hynix on July 29, and upcoming earnings from Samsung Electronics and Kioxia, are key milestones. If profit data consistently beats expectations and free cash flow improves, the valuation recovery could be swift; otherwise, the adjustment period may be prolonged.
Q3: Has the underlying demand for HBM memory changed?
No. HBM production capacity for the entire year is fully booked, and supply remains tight. SK Hynix’s 2026 HBM capacity is sold out, with orders lined up through Q1 2027. The demand fundamentals remain strong; what has changed is the market’s tolerance for valuations.
Q4: How is the current AI chip stock correction different from the dot-com bubble of 2000?
According to Huatai Securities, today’s AI computing infrastructure is underpinned by real growth in token consumption, unlike in 2000. The industry is now transitioning structurally from "price-driven" to "capacity-driven" growth, which is fundamentally a redistribution of profits within the supply chain, not a reversal of the overall industry logic.
