"Everyone Who Hasn't Boarded Yet Will Gather"...SK hynix's Long-Awaited Nasdaq Listing on the 10th
U.S. ADR Listing: Could Set New Record for Foreign Firms
Focus on Narrowing Valuation Gap with Micron
Funds Raised to Be Invested in Domestic Production Facilities
SK hynix will be listed on the Nasdaq in the United States on July 10. Analysts interpret this not only as a fundraising move, but also as a strategy to expand its competitiveness in the artificial intelligence (AI) semiconductor market against rivals such as Micron Technology.
According to Bloomberg on July 5 (local time), SK hynix’s American Depositary Receipts (ADR) will be listed on the Nasdaq on July 10. The total amount is $29 billion, which could make this the largest-ever initial U.S. stock offering by a foreign company.
The key driver of this listing is the surge in demand for high-bandwidth memory (HBM) used in AI data centers. SK hynix is a dominant player in the HBM market, but until now, it has been listed only on the Korean stock exchange, making it difficult for U.S. investors to invest directly. For U.S. investors, hurdles included differences in Korean market trading hours, currency exchange issues, and low liquidity of over-the-counter ADRs.
Once listed in the U.S., SK hynix shares will be tradable during regular trading hours in the U.S. and could potentially be included in major indices such as the Nasdaq 100. Index inclusion could lead to mechanical buying by passive exchange-traded funds (ETFs). For example, the assets under management of the Invesco QQQ Trust, which tracks the Nasdaq 100, amount to $482 billion.
The market is watching to see whether SK hynix can narrow its valuation discount to Micron through the U.S. listing. According to Bloomberg, SK hynix is trading at a forward price-to-earnings ratio (PER) of 6.2 times based on projected earnings over the next 12 months. In contrast, despite a recent stock price correction, Micron is trading at about 7 times, and as recently as June 22, exceeded 11 times.
Di Zhou, portfolio manager at Sunberg Investment Management, said, “This offering targets investors who have difficulty accessing the Korean stock market,” adding, “SK hynix’s Nasdaq listing provides a direct and frictionless opportunity to invest in the AI memory cycle.”
SK hynix plans to use the funds raised from the U.S. listing to invest in domestic production facilities. The company is expected to inject large-scale capital to build two new manufacturing plants in Korea and introduce advanced equipment to meet AI memory demand. Rival Samsung Electronics is also pursuing a similar expansion in capital investment.
The challenge lies in the inherent cyclicality of the memory industry. Memory semiconductors experience rapid increases in prices and profits during demand surges, but as supply grows and demand cools, prices quickly fall and companies face inventory burdens—a hallmark of cyclical industries. Just three years ago, both Micron and SK hynix posted losses as memory prices fell due to weakening demand.
The U.S. listing is also expected to spur demand for arbitrage trading. If there is a price difference between the Nasdaq-listed ADRs and the Seoul-listed shares, hedge funds may pursue trades to exploit this gap. Similar activity was observed during the U.S. listings of Alibaba and TSMC.
However, it remains unclear whether conversion between SK hynix ADRs and Korean-listed shares will be freely allowed. If conversion is unrestricted, the price gap between the two markets is likely to be limited; but if there are restrictions, the U.S. ADR could continue to trade at a premium.
In fact, TSMC’s ADRs traded at an average premium of over 21% compared to its local shares in Taiwan over the past year and currently maintain a premium of about 13%.
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On Wall Street, many expect SK hynix ADRs to absorb significant AI investment demand. Kim Forrest, Chief Investment Officer (CIO) at Bokeh Capital Partners, said, “Many people have not yet invested in this sector. When SK hynix comes to market, it could attract those wishing to participate in AI memory investments, even at a late stage.”
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