SK Hynix stock fell as much as 11% in Seoul on Thursday, surrendering most of the previous session’s sharp rebound as another sell-off in memory and AI-hardware stocks spread across Asia.
The reversal came after the company’s Korean shares surged nearly 13% on Wednesday.
Its Nasdaq-listed depositary receipts moved in the opposite direction, falling about 9% after jumping 27% one session earlier.
SK Hynix stock: Wall Street sell-off lands in Seoul
Thursday’s decline followed a broad retreat in US chip and hardware stocks.
Micron Technology (NASDAQ: MU) lost about 8% on Wednesday, while Dell fell almost 10%.
SanDisk, Western Digital and other storage companies also suffered steep declines as investors rotated towards large technology platforms and away from the companies supplying their infrastructure.
David Russell, global head of market strategy at TradeStation, told MarketWatch that technology investors may have already “priced in years of growth”.
That does not mean demand has suddenly collapsed, but it helps explain why even strong earnings expectations are no longer enough to prevent violent profit-taking.
SK Hynix is particularly vulnerable because it has become one of the market’s clearest proxies for the entire AI-memory trade.
Its Seoul shares had more than tripled in 2026 before the latest turbulence.
The Nasdaq listing then introduced a second investor base, options and leveraged exchange-traded products that can magnify movements in both directions.
Thursday’s pressure was intensified by a 7.3% drop in the Kospi and South Korea’s first interest-rate increase in more than three years.
Concerns about leveraged retail positions also remained prominent after regulators said they were preparing measures to address volatility linked to single-stock ETFs.
HBM bulls say this cycle is different
The bullish argument is that high-bandwidth memory, or HBM, has improved the quality and visibility of SK Hynix’s earnings.
HBM chips are more complex to manufacture than ordinary memory and consume greater production capacity.
They are also essential to the systems surrounding Nvidia and other AI accelerators, making supply difficult to expand quickly.
Barclays analyst Simon Coles initiated coverage of the ADRs with an Overweight rating and a $330 target.
He expects the memory shortage to intensify in 2027, with only limited improvement during 2028, while SK Hynix retains more than half of the HBM market.
IBK Securities analyst Kim Woon-ho has made a similarly bullish call on the Korean shares, raising his target to 4 million won.
Kim told Korean financial media that investors continued to underestimate memory demand and forecast an 11th consecutive quarterly earnings surprise as demand spreads from HBM into conventional DRAM and NAND storage.
Hanwha Investment & Securities has an even higher target of 4.3 million won, reflecting expectations for continued earnings growth.
The broader structural argument is that three- to five-year supply agreements can provide greater pricing visibility and reduce some of the extreme profit volatility that defined previous memory cycles.
The bust may be delayed, not defeated
BNK Investment & Securities analyst Lee Min-hee represents the sceptical end of the debate.
Lee has a Hold rating and a 1.85 million won target, acknowledging firm AI-server demand while warning that the momentum behind hyperscaler infrastructure investment could slow.
That is the pressure point for the entire bull case. Cloud companies must continue spending extraordinary amounts on processors, memory, networking, buildings and electricity.
If financing costs rise or AI products fail to generate sufficient returns, they may delay projects even while remaining committed to the technology.
New production capacity presents the longer-term risk. Factories and packaging facilities being built to address today’s shortage could begin easing supply constraints in 2027 and 2028.
The industry’s old problem would then return: capacity arrives after prices and profits have already encouraged customers and manufacturers to change their behaviour.
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