THE APEX TIMES
Cramer defends memory stocks after South Korea’s selloff, but flags risk around SK Hynix’s planned $28 billion raise
CNBC’s Jim Cramer said the market is being too harsh on memory makers despite Samsung’s strong results, while he pointed to uncertainty tied to SK Hynix’s large funding plans.
Wall Street’s AI hardware trade took another hit after South Korea’s broader market fell sharply overnight, pulling down shares of memory-related companies that benefit when data centers expand. In that setting, CNBC host Jim Cramer said the selloff looked excessive, arguing that profitability trends and the long runway for AI infrastructure remain supportive for the industry.
Cramer said Samsung, a key supplier of memory components, posted a record quarter. He used that performance as evidence that at least part of the memory complex is still finding pricing power and demand as customers build out servers and other systems for AI workloads.
Even so, Cramer flagged what he described as a warning tied to SK Hynix. The concern centers on SK Hynix’s planned $28 billion raise, which the market can treat as a sign of aggressive balance-sheet plans at a moment when sentiment is fragile. The risk, in Cramer’s framing, is that such activity could add uncertainty even if underlying demand remains strong.
The memory debate is tightly linked to the broader “AI infrastructure” stack. While NVIDIA has been the most visible winner in the AI boom, investors also watch the parts that help AI servers actually run: memory, storage, and networking components. In the CNBC context cited in the research, the memory and storage ecosystem has participated in large share price moves during the AI boom, reflecting the view that data center spending needs extend beyond chip vendors.
That means weakness in memory stocks can quickly spread through portfolios that treat the supply chain as a single bet. When a regional market drop coincides with valuation concerns, traders may reduce exposure to entire categories even when individual companies report strong results, such as Samsung’s record quarter referenced by Cramer.
For NVIDIA specifically, the market often uses the company’s momentum as a proxy for AI demand expectations. Cramer’s comments placed memory in the spotlight relative to NVIDIA, implying that memory profitability and its forward outlook may not be as synchronized with NVIDIA’s stock performance as investors sometimes assume.
Still, the details of Cramer’s “warning” and the full rationale for SK Hynix’s $28 billion raise were not laid out in the material available for this story. Without the underlying plan’s specifics, investors are left to interpret whether the funding is mainly about capacity, technology, or other strategic needs, versus potential dilution or other financial impacts.
What to watch next is whether the memory complex can hold support if South Korea’s market stabilizes, and whether SK Hynix provides additional clarity on how its financing connects to near-term supply and pricing. Any updates on terms, timing, and use of proceeds would likely determine whether the market treats the raise as a risk premium or as a step toward meeting AI-driven demand.
Why It Matters
- Memory makers are key suppliers to AI server builds, so sentiment shifts can affect the whole AI infrastructure trade.
- Large financing plans, such as SK Hynix’s referenced $28 billion raise, can become a swing factor for investor expectations even when demand is intact.
- The trade-off for investors is balancing visible profitability indicates from companies like Samsung against uncertainty created by capital-raising activity elsewhere in the supply chain.
Key Facts
- CNBC host Jim Cramer defended memory-related stocks after South Korea’s market dropped nearly 5% overnight.
- Cramer pointed to Samsung posting a record quarter as evidence of continued profitability in memory.
- Cramer said he has a warning tied to SK Hynix’s planned $28 billion raise.
- The comments were framed around whether investors are overreacting in memory after the regional selloff.
- The research context notes that AI infrastructure depends on more than AI chips, including memory and storage components.
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