Futures
Access hundreds of perpetual contracts
TradFi
Gold
One platform for global traditional assets
Options
Hot
Trade European-style vanilla options
Unified Account
Maximize your capital efficiency
Demo Trading
Introduction to Futures Trading
Learn the basics of futures trading
Futures Events
Join events to earn rewards
Demo Trading
Use virtual funds to practice risk-free trading
Launch
CandyDrop
Collect candies to earn airdrops
Launchpool
Quick staking, earn potential new tokens
HODLer Airdrop
Hold GT and get massive airdrops for free
Launchpad
Be early to the next big token project
Alpha Points
Trade on-chain assets and earn airdrops
Futures Points
Earn futures points and claim airdrop rewards
The AI investment boom drives a surge in CDS demand... "Bubble theory" concerns intensify over becoming reality
With the surge in investment in the artificial intelligence(AI) industry, the so-called “AI bubble theory” on Wall Street has resurfaced. Major tech companies are attracting trillions of Korean won in funding for AI-related equipment, while their growth prospects are being questioned. The demand for credit default swaps(CDS), used as risk diversification tools, has also increased significantly in the financial markets.
Looking at recent trends in the financial markets, large cloud service providers are pouring huge amounts of capital into expanding data centers for AI and introducing next-generation semiconductors. For example, Oracle and CoreWeave are carrying debt levels in the tens of billions of dollars, and Meta Platforms issued bonds worth up to $30 billion in October to raise funds for AI operations. Consequently, CDS trading linked to these companies has surged, attracting attention as a risk hedging measure. According to data from derivatives clearinghouse DTCC cited by the Financial Times, such CDS trades have increased by nearly 90% since early September.
The reason for this surge in CDS demand is that, relative to the expansion of AI industry investments, the companies’ performance or growth indicators have failed to meet expectations, leading to a wave of disappointment in the market. A typical example is Oracle, whose cloud division’s revenue in the latest earnings report fell short of market expectations, causing its stock price to plummet and its bonds to be sold off. At the same time, Oracle’s CDS prices soared to the highest levels since the financial crisis. Other AI semiconductor companies like Broadcom and NVIDIA also experienced significant declines in stock prices due to cracks in investor confidence.
Investment bank JPMorgan Chase forecasts that AI-related investment funds will surge in the coming years. The bank also predicts that, by 2030, well-capitalized investment-grade tech companies will invest approximately $1.5 trillion, equivalent to about 2,210 trillion Korean won. However, contrary to these long-term expectations, current net profit growth rates are showing signs of slowdown. According to Bloomberg Intelligence, the net profits of the top seven US tech giants are expected to grow only 18% year-over-year next year, the lowest in nearly four years.
Nevertheless, voices opposing the AI bubble theory are also significant. Currently, the Nasdaq 100 index, dominated by tech stocks, has a price-to-earnings ratio(PER) of about 26 times. Many analysts believe that, compared to the over 80 times during the early 2000s internet bubble, the current overheating level is much lower. Leading tech companies like NVIDIA, Alphabet, and Microsoft are trading at P/E ratios below 30, which, while reflecting high expectations, are not considered excessively inflated.
This trend indicates that the AI industry is gradually being tested against standards of feasibility and profitability. While future investments will continue, the capital markets seem to need a more balanced approach that emphasizes visible performance and profit streams. Investors also need to change their attitude, moving away from unbridled optimism and instead assessing tech stocks from a risk management perspective.