Why did AI experience a widespread decline overnight?

Author: Gelong

Overnight, the AI industry chain in the US stock market saw a significant decline, with the Nasdaq closing down 1.33% and the Philadelphia Semiconductor Index plummeting nearly 5%. Stocks related to storage, optical communication, and AI computing power generally faced heavy losses.

Panic sentiment quickly spread across markets, with today's Asia-Pacific market opening lower across the board. South Korean stocks, including Samsung Electronics and SK Hynix, dropped over 6%. Leveraged ETFs for double long positions on Samsung and SK Hynix both plummeted over 14%, further amplifying volatility due to leveraged funds.

The A-share AI industry chain also faced significant impacts, with core sectors such as computing power, optical modules, and storage generally falling over 5%, and several leading companies in niche segments seeing declines exceeding 8%.

The negative stimuli mainly come from several aspects.

First, the sudden escalation of tensions between the US and Iran has pushed up oil prices and inflation expectations, suppressing the valuation of the entire growth sector from a macro perspective.

The US announced a suspension of negotiations with Iran, further intensifying regional conflicts and increasing risks in the Strait of Hormuz, leading to a rise in international oil prices, which reached a three-week high. At the same time, the UAE has announced a suspension of all trade and financial exchanges with Iran, further escalating regional tensions.

The rise in oil prices directly brings concerns about a rebound in inflation, prompting the market to reassess the monetary policy space of the Federal Reserve.

Long-term US Treasury yields surged significantly, with the 30-year Treasury yield reaching a new high since 2007, and the 10-year Treasury yield also rising significantly.

In a high-interest-rate environment, the AI sector, characterized by high valuations and high capital expenditures, is directly impacted.

The construction of AI computing power heavily relies on debt financing, and this year, the supply of AI-related bonds has significantly exceeded previous annual expectations. Bonds issued by Blackstone for Microsoft's data center have seen yields approaching junk bond levels, reflecting the rising financing costs for AI infrastructure.

Goldman Sachs pointed out that the massive capital expenditures in AI, combined with sovereign deficits, have led to a large influx of funds into the bond market, even as economic data weakens, making it likely that the Federal Reserve will have to maintain a tight policy.

As financing costs continue to rise, the market is beginning to reassess the logic of expanding computing power at any cost, leading to a sell-off in the AI hardware sector.

Second, there is a clear divergence in the commercialization of large AI models, with OpenAI's performance slowdown shattering the market's linear optimism regarding AI applications.

The latest disclosed data for the second quarter shows that OpenAI's quarterly revenue growth rate is only 18% quarter-on-quarter, with operating losses continuing to expand, while several company executives have left, raising market concerns about internal management stability.

Although competitor Anthropic has achieved explosive revenue growth and made a small profit, the differences in revenue accounting do not represent that the entire industry has smoothly entered a profitable era.

OpenAI's slowdown in growth has made the market realize that the commercialization of large AI models is not smooth sailing, and there are still significant challenges in converting enterprise clients and controlling costs.

In the past, the market was accustomed to unconditionally believing in the story of AI capital expenditures, but now investors are beginning to question how much real revenue and profit can be generated from massive investments in computing power. The AI industry chain has officially entered a period of assessment for its commercialization capabilities, moving from the "burning money to expand scale" phase.

Third, the ongoing investment game between South Korea and the US in semiconductors continues to ferment, exacerbating the uncertainty in the global storage industry chain and directly impacting the HBM storage sector, which is core to AI computing power.

South Korea has publicly denied reports regarding the US's proposal for priority construction of memory chip factories in the US. South Korea has already planned to invest over $580 billion in local chips and data center clusters.

If Samsung and SK Hynix are forced to establish memory production lines on a large scale in the US, it will consume a significant amount of corporate capital and weaken the domestic semiconductor industry ecosystem.

However, the US's pressure tactics are multifaceted, using tariffs as leverage, and delays in investment landing may also spill over to affect cooperation in security between South Korea and the US.

This reflects the reality of "earning money from the US market, keeping capital in the US, and complying with industrial demands." South Korean storage companies rely on supplying HBM to the US AI market for substantial profits, while the US demands that companies repatriate capital to build factories domestically, or face trade penalties.

The market is concerned that if subsequent negotiations continue to drag on, whether South Korea chooses to compromise or confront, it will disrupt the global storage supply pattern.

If South Korea compromises, corporate capital will be diverted, and profits will be eroded by the high costs of building factories in the US; if they take a hardline stance, they may face the risk of trade barriers.

This dilemma has directly triggered a sell-off of Samsung and SK Hynix, with leveraged ETFs further amplifying the decline, and panic sentiment spreading along the storage industry chain.

Of course, a short-term crash does not mean the complete end of the AI industry logic.

The long-term demand for AI computing power still objectively exists, but the market is no longer willing to pay high premiums for an infinitely optimistic long-term story.

Going forward, the market's focus will shift from merely looking at the scale of capital expenditures to examining the real profit levels of enterprises, changes in financing costs, and the ultimate direction of global supply chain dynamics.

For the A-share market, external emotional shocks bring more disturbances at the emotional level. It will be necessary to observe the domestic industry chain's own orders and profit realization, distinguishing between short-term emotional sell-offs and substantial deterioration in fundamentals.