
SK Hynix is expected to launch its Nasdaq listing as early as August making it one of the biggest US stock market debuts in recent years, as per Korea Herald. The South Korean chipmaker confidentially filed for the listing with the US Securities and Exchange Commission (SEC) in March and has appointed Citigroup, JPMorgan, Goldman Sachs and Bank of America to manage the share sale, Korea Herald reported citing Reuters.
As per the report, while earlier a possible listing was reported for August, the company has only said that it plans to go public sometime in 2026.
An American Depositary Receipt (ADR) allows US investors to buy shares of foreign companies in dollar terms. For SK hynix, however, the bigger attraction is gaining access to US investors who increasingly view memory chips as a critical component of the artificial intelligence supply chain rather than a cyclical commodity business.
A Nasdaq listing would place SK hynix alongside US-listed peer Micron and could help the company secure a higher market valuation. "On the Nasdaq it would trade on the same screens as Micron, its closest US-listed peer, and be priced by investors who treat memory chips as the scarce input for AI rather than a commodity that swings with the cycle," Korea Herald reported.
The size of the offering remains uncertain, with estimates varying widely. Korea Herald further that SK hynix could raise up to about USD 14 billion by selling around 2-3 per cent of its shares, citing Reuters. "A company official said the 40 trillion won is an outside estimate built by the media and brokerages, not a figure the company has set. Approval is not a fixed-date event either," the report said.
According to Korea Herald, SK hynix reported an operating profit of 37.6 trillion won (USD 24.43 billion) in the first quarter. The company also shipped samples of its 12-layer HBM4E chips to major customers on June 17 and is investing about 31 trillion won in the first fabrication plant at its new Yongin semiconductor cluster south of Seoul.
"High-bandwidth memory has become the bottleneck in building AI accelerators, and the industry expects the shortage to persist," the report further noted. (ANI)
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