#SK海力士市值登顶韩股 A company that almost went bankrupt, with a market value surpassing Bitcoin
On June 22, SK Hynix's stock price rose, pushing its market capitalization to $1.35 trillion, surpassing Bitcoin's total market value of about $1.29 trillion, and during trading, it temporarily overtook Samsung Electronics to become Korea's most valuable company.
According to Coinglass data, in the global asset rankings, SK Hynix rose to 16th place, while Bitcoin slipped to 18th.
HBM, and a 13-year betting game
The core driver of SK Hynix's recent rise is HBM (High Bandwidth Memory).
AI training and inference demand extremely high memory bandwidth, and SK Hynix is NVIDIA's main HBM supplier, with a market share exceeding 60%. Financial reports show SK Hynix's Q1 revenue was 52.58 trillion won, operating profit was 37.61 trillion won, with a profit margin of 72%.
Analysts currently expect SK Hynix's Q2 operating profit to be around 62-65 trillion won, with some brokerages' optimistic forecasts raised to over 68 trillion won. In early April, market expectations for Q2 mostly remained in the 50 trillion won range, but as memory prices continued to stay strong, brokerages widely revised their forecasts upward. Management stated at the earnings call that the structural memory shortage brought by AI will last for several years at least, and plans to significantly increase capital expenditure to expand advanced capacity.
It is reported that SK Hynix has been betting on HBM technology since 2009, when the market paid little attention to this complex technology with limited initial demand. From the first generation HBM to HBM3E, this high-stakes gamble has lasted nearly 13 years, until the emergence of ChatGPT, which marked its crowning moment.
SK Hynix's current success is inseparable from a key external aid. After the dot-com bubble burst in 2001, Hynix was mired in debt crisis, with its stock price falling to junk status, and even negotiating with Micron Technology to sell, which ultimately failed. For the next decade, the company was under creditor control. In 2012, SK Group Chairman Chey Tae-won overruled the board's opposition and acquired it through its investment holding subsidiary SK Square for about $3 billion, rebranding it as SK Hynix, and injecting large-scale R&D funds. This investment allowed the company to continue advancing HBM technology, which was still a niche market at the time.
Currently, SK Square owns about 20% of SK Hynix, making it its largest single shareholder. Notably, SK Square has also attempted to enter the crypto market. In 2021, it acquired a 35% stake in Korean crypto exchange Korbit for about 90 billion won and planned to issue its own token, SK Coin. Public reports indicate that after the Terra/LUNA collapse in 2022, market enthusiasm cooled sharply, and SK Coin's issuance plan was shelved, with no substantial progress since. According to Reuters, citing sources, SK Hynix plans to go public on Nasdaq as early as August this year, which would lower trading barriers for US institutions and passive funds, potentially further attracting capital inflows.
NVIDIA CEO Jensen Huang recently stated that future cooperation between NVIDIA and SK Hynix could bring hundreds of billions of dollars in business opportunities to Korea.
Why is capital paying? The mirror of Crypto AI
In this AI wave, the market is more willing to pay premiums for segments with actual orders and visible supply bottlenecks.
Compute power, memory, electricity—assets directly involved in AI supply—are prioritized because their revenues are quantifiable and barriers verifiable. HBM capacity is highly concentrated in SK Hynix, Samsung, and Micron, with expansion cycles lasting 2 to 3 years. This physical scarcity is not built on narratives but is locked in by capacity cycles and technological barriers.
The valuation logic of the storage industry is also shifting from "cyclical stocks" to "growth stocks."
SK Hynix's market cap surpassing Bitcoin is a public statement from the capital market about two kinds of scarcity. The physical barriers are already so high that the situation of Crypto AI deserves re-examination. Over the past two years, the Crypto AI track has been telling a story: decentralized computing power will reshape AI infrastructure, and open networks will surpass closed enterprise data centers. This potential is real, but in light of SK Hynix's current market value, several realities must be faced.
The IC3 report jointly released by 13 universities including Cornell states that the integration of Crypto and AI is still in its early stages, and the hype around this intersection has overshadowed actual progress. Decentralized computing, data markets, and governance mostly remain in conceptual stages.
At the project level, the most representative project in the Crypto AI track, Bittensor, saw its token TAO decline 20% over the past three months. Bittensor co-founder const posted on X that the project's economic incentives are still dominated by the core team, who choose to maintain centralization for faster iteration, and it will take another year and a half to complete the core mechanism. In other words, their underlying mechanism is still being patched.
Closer to hardware, crypto mining companies are also not in an easy situation. According to Galaxy Research data, Bitcoin miners are entering a "surrender phase," with current network mining difficulty down over 20% from its historical high, the largest retreat since China's crackdown on Bitcoin mining in 2021, with some miners continuing to exit the network or shut down equipment.
To seek transformation, miners like Core Scientific, TeraWulf, and Hut 8 have announced ventures into AI and high-performance computing. But according to VanEck, this transition faces a short-term funding gap of about $50 billion, with long-term capital needs around $221 billion, and only about 25% of leased AI capacity has been delivered—companies missing construction milestones are facing downgrades from investors.
On the funding side, Arthur Hayes recently pointed out in his article "Reality Test" that since the release of ChatGPT in 2022, the AI industry has issued about $1.5 trillion in debt, roughly matching the increase in US dollar M2 during the same period—AI has almost absorbed all new liquidity, and Bitcoin has never had such an opportunity.
Hayes believes this is not just "AI losing funds and flowing back into crypto." The upcoming IPOs of Anthropic and OpenAI will further siphon market funds. Once the AI bubble bursts, bank credit tightening will also restrict liquidity, and Bitcoin will be sold along with AI.
Since the second half of last year, many traders active in the crypto market have shifted their focus to US and Korean stocks, chasing AI hardware trends. The logic behind capital flowing into AI infrastructure is simple and brutal: real orders, physical barriers, quantifiable profit margins. This certainty is the fundamental reason why current capital is willing to pay high premiums, while the AI narrative in crypto markets lacks this certainty.
In other words, the current dividends of AI infrastructure are more likely to be captured by entities with technological barriers and real supply capabilities. Crypto networks need to better define their position within the value chain in this process.
On June 22, SK Hynix's stock price rose, pushing its market capitalization to $1.35 trillion, surpassing Bitcoin's total market value of about $1.29 trillion, and during trading, it temporarily overtook Samsung Electronics to become Korea's most valuable company.
According to Coinglass data, in the global asset rankings, SK Hynix rose to 16th place, while Bitcoin slipped to 18th.
HBM, and a 13-year betting game
The core driver of SK Hynix's recent rise is HBM (High Bandwidth Memory).
AI training and inference demand extremely high memory bandwidth, and SK Hynix is NVIDIA's main HBM supplier, with a market share exceeding 60%. Financial reports show SK Hynix's Q1 revenue was 52.58 trillion won, operating profit was 37.61 trillion won, with a profit margin of 72%.
Analysts currently expect SK Hynix's Q2 operating profit to be around 62-65 trillion won, with some brokerages' optimistic forecasts raised to over 68 trillion won. In early April, market expectations for Q2 mostly remained in the 50 trillion won range, but as memory prices continued to stay strong, brokerages widely revised their forecasts upward. Management stated at the earnings call that the structural memory shortage brought by AI will last for several years at least, and plans to significantly increase capital expenditure to expand advanced capacity.
It is reported that SK Hynix has been betting on HBM technology since 2009, when the market paid little attention to this complex technology with limited initial demand. From the first generation HBM to HBM3E, this high-stakes gamble has lasted nearly 13 years, until the emergence of ChatGPT, which marked its crowning moment.
SK Hynix's current success is inseparable from a key external aid. After the dot-com bubble burst in 2001, Hynix was mired in debt crisis, with its stock price falling to junk status, and even negotiating with Micron Technology to sell, which ultimately failed. For the next decade, the company was under creditor control. In 2012, SK Group Chairman Chey Tae-won overruled the board's opposition and acquired it through its investment holding subsidiary SK Square for about $3 billion, rebranding it as SK Hynix, and injecting large-scale R&D funds. This investment allowed the company to continue advancing HBM technology, which was still a niche market at the time.
Currently, SK Square owns about 20% of SK Hynix, making it its largest single shareholder. Notably, SK Square has also attempted to enter the crypto market. In 2021, it acquired a 35% stake in Korean crypto exchange Korbit for about 90 billion won and planned to issue its own token, SK Coin. Public reports indicate that after the Terra/LUNA collapse in 2022, market enthusiasm cooled sharply, and SK Coin's issuance plan was shelved, with no substantial progress since. According to Reuters, citing sources, SK Hynix plans to go public on Nasdaq as early as August this year, which would lower trading barriers for US institutions and passive funds, potentially further attracting capital inflows.
NVIDIA CEO Jensen Huang recently stated that future cooperation between NVIDIA and SK Hynix could bring hundreds of billions of dollars in business opportunities to Korea.
Why is capital paying? The mirror of Crypto AI
In this AI wave, the market is more willing to pay premiums for segments with actual orders and visible supply bottlenecks.
Compute power, memory, electricity—assets directly involved in AI supply—are prioritized because their revenues are quantifiable and barriers verifiable. HBM capacity is highly concentrated in SK Hynix, Samsung, and Micron, with expansion cycles lasting 2 to 3 years. This physical scarcity is not built on narratives but is locked in by capacity cycles and technological barriers.
The valuation logic of the storage industry is also shifting from "cyclical stocks" to "growth stocks."
SK Hynix's market cap surpassing Bitcoin is a public statement from the capital market about two kinds of scarcity. The physical barriers are already so high that the situation of Crypto AI deserves re-examination. Over the past two years, the Crypto AI track has been telling a story: decentralized computing power will reshape AI infrastructure, and open networks will surpass closed enterprise data centers. This potential is real, but in light of SK Hynix's current market value, several realities must be faced.
The IC3 report jointly released by 13 universities including Cornell states that the integration of Crypto and AI is still in its early stages, and the hype around this intersection has overshadowed actual progress. Decentralized computing, data markets, and governance mostly remain in conceptual stages.
At the project level, the most representative project in the Crypto AI track, Bittensor, saw its token TAO decline 20% over the past three months. Bittensor co-founder const posted on X that the project's economic incentives are still dominated by the core team, who choose to maintain centralization for faster iteration, and it will take another year and a half to complete the core mechanism. In other words, their underlying mechanism is still being patched.
Closer to hardware, crypto mining companies are also not in an easy situation. According to Galaxy Research data, Bitcoin miners are entering a "surrender phase," with current network mining difficulty down over 20% from its historical high, the largest retreat since China's crackdown on Bitcoin mining in 2021, with some miners continuing to exit the network or shut down equipment.
To seek transformation, miners like Core Scientific, TeraWulf, and Hut 8 have announced ventures into AI and high-performance computing. But according to VanEck, this transition faces a short-term funding gap of about $50 billion, with long-term capital needs around $221 billion, and only about 25% of leased AI capacity has been delivered—companies missing construction milestones are facing downgrades from investors.
On the funding side, Arthur Hayes recently pointed out in his article "Reality Test" that since the release of ChatGPT in 2022, the AI industry has issued about $1.5 trillion in debt, roughly matching the increase in US dollar M2 during the same period—AI has almost absorbed all new liquidity, and Bitcoin has never had such an opportunity.
Hayes believes this is not just "AI losing funds and flowing back into crypto." The upcoming IPOs of Anthropic and OpenAI will further siphon market funds. Once the AI bubble bursts, bank credit tightening will also restrict liquidity, and Bitcoin will be sold along with AI.
Since the second half of last year, many traders active in the crypto market have shifted their focus to US and Korean stocks, chasing AI hardware trends. The logic behind capital flowing into AI infrastructure is simple and brutal: real orders, physical barriers, quantifiable profit margins. This certainty is the fundamental reason why current capital is willing to pay high premiums, while the AI narrative in crypto markets lacks this certainty.
In other words, the current dividends of AI infrastructure are more likely to be captured by entities with technological barriers and real supply capabilities. Crypto networks need to better define their position within the value chain in this process.
