SK Hynix’s share price has tumbled more than 24% from its June record, caught between a US cartel lawsuit and a single unconfirmed report that Meta is weighing a cloud business. The stock closed at 2,251,000 Won, still 232.5% higher year-to-date but well off the 2,987,000 Won peak. The twin shocks have forced investors to reassess whether the company’s explosive pricing power can survive both a regulatory challenge and a potential shift in hyperscaler demand.
The first blow landed in late June, when a class-action lawsuit filed in the US District Court for Northern California accused SK Hynix, Samsung and Micron of colluding to artificially restrict supply of older DRAM chips while focusing their production on high-end HBM memory. The allegations remain unproven, and the case is at an early stage. Yet the mere filing knocked the stock 12% in a single session, sending the price to around 2,560,000 Won at the time.
Days later, a Bloomberg report that Meta is exploring a cloud-computing business – selling excess AI compute capacity to third parties – triggered a second wave of selling. Meta did not confirm the story, and Reuters could not independently verify it. But the market interpreted the possibility as a signal that hyperscalers might be building capacity ahead of real demand, potentially loosening the memory supply constraints that have driven SK Hynix’s margins. The stock shed another 12% on that news, dragging its seven-day loss to nearly a quarter of its value.
Bulls point to tangible product milestones that they believe will outweigh legal noise and speculative headlines. On June 7, SK Hynix announced a multi-year technology partnership with Nvidia covering advanced memory supply and joint development across AI infrastructure, personal AI and physical AI platforms. Eleven days later, the company shipped first samples of its next-generation HBM4E memory to key customers. Sampling is not mass production, but it marks a concrete qualification step. The strong first-quarter results, driven by HBM, high-capacity server DRAM and enterprise SSDs, suggest underlying AI demand remains robust. “The bull case rests on continued memory tightness, not on a single rumour,” one Seoul-based analyst noted.
Should investors sell immediately? Or is it worth buying SK Hynix?
Bears counter that the stock’s valuation leaves no room for error. After a 278% year-to-date surge prior to the recent slide, even a modest shift in the demand narrative – such as Meta monetising spare compute – can compress the premium investors assign to SK Hynix. The 30-day annualised volatility of 111.69% underscores how violently the shares can swing on fresh information. The cartel lawsuit adds a structural layer: if the market begins to view memory scarcity as the product of illegal collusion rather than genuine supply-demand tension, SK Hynix’s pricing power could be permanently discounted. Foreign investors have already trimmed positions in Asian AI winners, and the paltry 375 Won dividend offers no downside buffer.
Technical indicators paint a mixed picture. The stock sits 11.31% above its 50-day moving average of 2,022,320 Won and far above the 100-day average of 1,484,530 Won, but the relative strength index of 46.8 signals neither oversold euphoria nor deep exhaustion. The shares remain in a volatile consolidation zone rather than a definitive breakdown.
The next catalyst is less a date than a process. SK Hynix must convert HBM4E samples into customer-qualified volume production. The first case management hearing in the US lawsuit is set for September 23, 2026, but until then the company’s operational strength will determine the narrative. If AI-related memory demand stays broad – spanning HBM, server DRAM and storage – and clients validate the new product cycle, the legal and market-cloud risks may prove manageable. If, however, further hyperscalers signal a willingness to sell or lease excess compute capacity, the duration of SK Hynix’s pricing cycle could shrink faster than bulls anticipate. For now, the stock is caught between the hard fact of a 24.64% decline from its high and the unresolved question of whether AI compute remains structurally memory-constrained.
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