T. Rowe Price Bets on China's AI Supply Chain, Fund Returns Exceed 25% This Year
nashnova research
T. Rowe Price's China Evolution Equity Fund returned over 25% this year while its benchmark fell roughly 7%; portfolio specialist Agnes Ng says the outperformance came from Greater China manufacturers in the AI supply chain that sit outside mainstream indices, and she sees China's AI capex cycle — lagging the U.S. by about 18–24 months — as a more durable return driver than government policy.
How did this fund beat its benchmark by 32 percentage points?
T. Rowe Price's China Evolution Equity Fund manages $735 million and returned over 25% year-to-date, while the MSCI China All Shares index fell roughly 7%.
On Morningstar's China equity peer ranking, it sits in the top 6% over three years through August.
This means → the result is not one good quarter — it reflects three consecutive years of stock-picking near the top of its peer group.
Where did the alpha come from — and why PCBs and chip equipment?
Portfolio specialist Agnes Ng says the outperformance came from Greater China manufacturers in the mid-to-downstream AI supply chain — printed circuit boards (PCBs — the boards chips are soldered onto so they can talk to each other), chip equipment, and power components.
Top holdings include PCB makers Unimicron Technology, WUS Printed Circuit Kunshan, and Shengyi Technology.
In plain terms = the spotlight lands on chip designers like Nvidia, but the "supporting cast" — circuit boards, equipment, power parts — rides the same AI spending wave, and these names sit outside mainstream indices, overlooked by most capital.
How does a Korean capacity bottleneck turn into an opportunity for Chinese and Japanese suppliers?
Samsung Electronics and SK Hynix have announced plans to spend tens of billions of dollars building new fabs to produce high-bandwidth memory (HBM — ultra-fast memory designed to feed data to AI chips) for AI data servers.
Ng notes that capacity bottlenecks at Korea's top chipmakers are creating spillover opportunities for second-tier suppliers in Japan and China.
This means → demand is too large for the leaders to absorb alone, so orders flow naturally to the second tier — exactly where the fund is positioned.
Why is the fund shifting its energy exposure from commodities to power management?
The fund is moving its energy allocation away from commodity-type components toward higher-value-add segments: power-management chips (small chips that control voltage distribution), voltage-conversion equipment, and backup-power suppliers.
This reflects a shift in what AI infrastructure needs from electricity — not just "more power" but "more precisely managed power." Every GPU requires a stable, efficient power-delivery chain.
The core thesis: China's AI cycle lags by 18–24 months — why is that an opportunity?
Ng estimates China's AI investment cycle currently trails the U.S. by roughly 18 to 24 months.
She sees this catch-up gap as a more durable return driver than government policy — "Even if expectations for the global AI cycle are being recalibrated, China may still experience a notable catch-up investment cycle beneath that."
In plain terms = U.S. AI spending is well advanced and markets are starting to worry about overheating; China is just entering the acceleration phase, with capital yet to be deployed. The catch-up gap itself is the return source.
What is the risk in this story?
Whether China's AI supply chain can keep outperforming ultimately depends on the catch-up cycle translating into actual capital expenditure within the next one to two years, rather than remaining at the expectation level.
This means → if Chinese companies' AI capex falls short of expectations, the fund's current overweight thesis loses its foundation — the gap between expectation and execution is the single biggest risk.
市场有风险，内容仅供研究参考，不构成投资建议。