#分享美股交易赢英伟达股票

Rational Analysis—How to View the Current AI Bull Market, Can Tech Stocks Still Be Held?

The recent pullback in the US stock market, especially the sharp decline in AI tech stocks, has left many people regretful. Having just recovered from losses in Bitcoin, they now jumped into US stocks again, incurring significant losses and feeling quite discouraged. Currently, market sentiment is very impatient; long-position holders are desperately promoting AI as the future and unstoppable, while short-sellers are counting their money and mocking the "AI bubble," leading to intense clashes. Today, let's set aside positions and alliances, and calmly analyze the true nature of this AI bull market and how it might develop in the future. Let’s go:

1. Industry Wave: The Underlying Logic of This Bull Market

Explosive performance growth has become the core engine. Leading companies’ financial reports show: Nvidia’s quarterly revenue surpassing $80 billion, up 85% year-over-year; Microsoft, Google, and Meta’s combined annual AI capital expenditure approaching $700 billion. This growth is not just hype—global daily AI inference call volume has exceeded 140 trillion tokens, driven by real demand that pushes hardware procurement volume and prices higher.

Technological iteration triggering industry restructuring is reshaping the landscape. As AI applications shift from training to inference, the pattern of computing power consumption changes fundamentally: demand for single-user computing power surges 3-5 times, and the ratio of server CPUs to GPUs evolves from 1:8 to 1:1. This structural change has created ongoing gaps in storage chips, optical modules, and high-speed interconnect devices, with giants like Micron and Samsung maintaining high capacity utilization.

2. Market Turbulence: The Triple Pressures Behind the Crash

Liquidity expectation reversal as a fuse. The latest non-farm payroll data exceeded expectations, strengthening rate hike expectations. The 10-year US Treasury yield soared 27 basis points in a single day, hitting tech stocks with high valuations hardest. The Philadelphia Semiconductor Index lost $1.5 trillion in market value over two days, essentially correcting overly optimistic rate policies from earlier.

Fragile trading structures accelerate sell-offs. The AI sector’s holdings concentration hit a ten-year high, with the top ten stocks accounting for over 40% of the Nasdaq index weight. When Nvidia’s daily trading volume exceeds $80 billion (12% of total US stock trading), any marginal change can trigger a chain reaction of algorithmic trading.

Supply-side disturbances amplify volatility. SpaceX’s billion-dollar IPO is approaching, coupled with expectations for unicorns like OpenAI to go public, raising concerns about capital flow diversion. More notably, Nvidia was reported to be adjusting the memory configuration of its next-generation chips—cost optimization measures that were misinterpreted as signals of demand contraction.

3. Future Outlook: Validating the Sustainability of the Bull Market

Short-term gap repair:

- The imbalance between supply and demand for computing power continues to worsen. Leading cloud providers’ AI computing rental prices have increased by 34% this year, with order lead times extending to 2027.
- Silicon-based inflation persists. Prices of 12-inch silicon wafers have risen twice, and delivery times for special semiconductor materials have extended to 26 weeks.
- Enterprise-level application demand is releasing strongly. Tencent and Alibaba’s full-industry agent deployments have doubled server procurement year-over-year.

Mid-term technological generations:

- Inference chip iterations drive hardware upgrade waves, with Blackwell architecture GPUs expected to surpass 30% penetration in Q3.
- Multimodal large models are commercializing, opening trillion-yuan markets in medical, industrial inspection, and other scenarios.
- Breakthroughs in integrated memory and computing technology may solve the memory wall bottleneck; new architecture products are already in tape-out stages.

Long-term ecosystem restructuring:

- Government and enterprise markets become new growth poles. China’s mandatory domestic chip procurement policies trigger chain reactions, and the US and Europe have introduced local AI computing laws.
- Edge AI is imminent. AI PC penetration is expected to surpass 40% by year-end, with demand for edge computing chips growing exponentially.
- Energy efficiency sets the ceiling. Every 10% increase in liquid cooling technology adoption can triple data center computing density.

4. Core Conclusion: The Path of Evolution Amidst Turbulence

The current adjustment is essentially a valuation system restructuring. As the sector’s dynamic P/E ratio drops from 45x to 32x (still above the five-year average of 28x), capital is shifting from conceptual plays to companies with proven performance. Companies with the following features will lead the new phase:

- Mastery of full-stack technology capabilities (e.g., Lenovo’s edge-cloud-network architecture)
- Tying into top cloud providers’ capital expenditure (e.g., TSMC’s CoWoS capacity monopoly)
- Connecting to commercial closed loops (e.g., Baidu AI revenue accounting for over 50%)
- The industry trend train will not change direction due to track bumps. When global daily AI interactions exceed 50 billion, and a single autonomous vehicle generates 200TB of data annually, the productivity revolution is just beginning. Short-term fluctuations will eventually give way to an irreversible tide of technological progress.