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#英伟达市值重返5.4万亿美元 NVIDIA's market cap has returned to $5.4 trillion, marking an extreme validation of the industry logic and capital pricing of the AI computing power sector. The AI computing power sector's rally has not yet peaked, but has entered a phase of differentiation and volatility from the "broad-based rise" stage. Overall, the market will evolve in waves; medium- to long-term industry prosperity remains promising, but in the short term it faces pressure from valuation digestion and sentiment fluctuations.
I. The underlying logic of how long the rally can continue
1. Industry cycle support (long-term logic)
AI computing power demand is far from peaking. It is expanding from "large-model training" to "model inference" and "AI agents," with Token consumption growing exponentially and continuously driving demand for computing power. The capital expenditures of global technology giants (cloud service providers) continue to expand, providing long-term demand support for upstream computing power, and the industry-cycle logic of the computing power sector remains intact.
2. Earnings realization and valuation dynamics (medium-term logic)
The current valuation of the computing power sector has fully priced in growth expectations for the next two to three years. The sustainability of the short-term rally depends heavily on continued earnings realization (such as actual orders, gross margins, and cash flow across individual segments) and changes in macro liquidity. As the base rises, the computing power sector's growth rate may slow at the margin, and the market will become more selective, with the rally exhibiting a volatile upward trend characterized by "two steps forward and one step back."
II. Key indicators for observing the evolution of the rally
1. Sustainability of capital expenditures (CapEx): Monitor the implementation of capital expenditures by overseas cloud service providers (Microsoft, Google, Amazon, Meta, etc.) and domestic internet giants, as this is the most direct leading indicator of computing power demand.
2. Earnings realization: Monitor order visibility, actual revenue, and profit realization across segments of the computing power industry chain, such as optical modules, memory chips, advanced packaging, and liquid cooling. Earnings verification will determine internal differentiation within the sector.
3. Macro liquidity: The AI computing power sector is a high-valuation growth sector and is relatively sensitive to U.S. Treasury yields and Federal Reserve rate-cut expectations. Changes in liquidity will directly affect the sector's room for valuation recovery.
III. Structural differentiation within the sector
1. Segments with strong industry momentum and high earnings visibility (likely to go further): Upstream core hardware, such as high-end optical modules, HBM high-bandwidth memory, and advanced packaging, as well as computing power leaders with core technological barriers, have high earnings realization due to tight supply and demand and pricing-power advantages, giving them strong downside resilience and long-term allocation value.
2. Pure-concept or weaker earnings-realization segments (higher risk): Some stocks driven solely by AI speculation and lacking actual orders and earnings support may experience sharp pullbacks after valuation recovery as capital flows ebb and sentiment declines.
The long-term prospects for the AI computing power sector remain broad, but it will be difficult to replicate the previous one-way surge in the short term. Investors should lower their short-term return expectations, capture the resonance between industry trends and earnings realization, and avoid blindly chasing rallies. $NVDA
I. The underlying logic behind how long the rally can continue
1. Industrial cycle support (long-term logic)
AI computing power demand is far from peaking. It is extending from “large model training” to “model inference” and “AI agents,” with Token consumption growing exponentially and continuously driving demand for computing power. The continued expansion of capital expenditures by global technology giants (cloud providers) provides long-term demand support for the upstream computing power industry, and the industrial cycle logic of the computing power sector remains intact.
2. Earnings realization and valuation dynamics (medium-term logic)
The current valuation of the computing power sector has fully priced in growth expectations for the next two to three years. The sustainability of the short-term rally depends heavily on continued earnings realization (such as actual orders, gross margins, and cash flow across various segments) as well as changes in macro liquidity. As the base becomes higher, the growth rate of the computing power sector may slow marginally, and the market will become more selective, with the rally exhibiting a volatile upward trend characterized by “two steps forward and one step back.”
II. Key indicators for monitoring the market's evolution
1. Sustainability of capital expenditures (CapEx): Monitor the implementation of capital expenditures by overseas cloud providers (Microsoft, Google, Amazon, Meta, etc.) and domestic internet giants, as this is the most direct leading indicator of computing power demand.
2. Earnings realization: Monitor the order visibility, actual revenue, and profit realization across segments of the computing power industry chain (such as optical modules, memory chips, advanced packaging, and liquid cooling). Earnings validation will determine internal differentiation within the sector.
3. Macro liquidity: The AI computing power sector is a high-valuation growth sector and is relatively sensitive to U.S. Treasury yields and expectations for Federal Reserve rate cuts. Changes in liquidity will directly affect the room for valuation recovery in the sector.
III. Structural differentiation within the sector
1. Segments with strong growth and high earnings visibility (likely to advance further): Upstream core hardware (such as high-end optical modules, HBM high-bandwidth memory, and advanced packaging) and computing power leaders with core technological barriers have high earnings realization due to tight supply and demand and pricing power advantages, giving them strong downside resilience and long-term allocation value.
2. Purely conceptual segments or those with weak earnings realization (higher risk): Some stocks driven solely by AI concept speculation and lacking actual orders and earnings support are prone to significant pullbacks after valuation recovery as capital flows recede and sentiment declines.
The long-term potential of the AI computing power sector remains broad, but it will be difficult to replicate the one-way surge of the past in the short term. Investors should lower their short-term return expectations, capture the convergence of industry trends and earnings realization, and avoid blindly chasing highs. $NVDA