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
Top Fund Giants: Chinese AI Giants Possess Greater Investment Value Than US Counterparts
A emerging market fund that has outperformed 97% of its peers is increasing its bets on China’s AI sector, betting on the valuation advantages and application potential of Chinese internet giants like Tencent and Alibaba. It believes these companies will surpass American tech giants that are heavily spending on expansion.
According to Bloomberg on Friday, Caroline Cai, CEO of Pzena Investment Management, stated that her $3.9 billion fund has recently been increasing its holdings in Tencent Holdings and Alibaba Group.
She believes these companies are undervalued and have enormous potential to deeply embed AI into existing platforms and change daily life, with considerable upside. “The cost of enhancing productivity through AI is not high,” she said in an interview.
Cai’s view on AI investment value sharply contrasts with current market sentiment. Over the past few months, investors have been selling Tencent and Alibaba due to concerns over intensified platform competition, with some funds shifting into emerging AI companies like MiniMax.
Valuation Disparity: China’s Internet Companies Have Relative Advantages
Cai’s core logic centers on the significant valuation gap between Chinese and U.S. AI companies. Chinese internet companies are generally valued lower than most large U.S. cloud computing giants, yet their potential in AI applications does not match.
In terms of capital expenditure strategies, the paths of Chinese and American tech companies are quite different. The four major U.S. tech giants are expected to spend about $650 billion on capital expenditures by 2026, mainly on new data centers and related equipment.
In contrast, Chinese internet companies are more restrained in their investments—according to Bloomberg industry research, Alibaba, Tencent, Baidu, JD.com, and Meituan are projected to have cumulative capital expenditures exceeding $240 billion by 2030. Currently, this group holds a combined cash reserve of $224 billion, providing a safety margin.
Cai believes the key is not how much money is spent, but where it is spent. “When you examine the quality of these models and their focus on application layers, this might be a more interesting way to monetize AI than in developed countries,” she said.
Rebalancing Strategy: From Chips to Platforms
To establish new positions in Alibaba and Tencent, Pzena’s emerging market value fund has reduced holdings in Samsung Electronics and TSMC. Cai said these companies are no longer as attractive to the fund as before.
Regarding Samsung, Cai pointed out that as AI demand has driven up storage chip prices significantly, the fund’s investment logic has already been realized ahead of schedule, exceeding expectations. This means the original valuation recovery potential has greatly narrowed, reducing the cost-effectiveness of holding these stocks.
Currently, the top ten holdings of Pzena’s emerging market value fund still include Samsung Electronics, TSMC, and Alibaba. According to Bloomberg data, the fund has outperformed 97% of its peers over the past five years and has surpassed 90% of similar products this year. Cai is co-portfolio manager of all Pzena products, managing approximately $67 billion in assets.
Although Cai is optimistic about China’s AI sector, she also admits that it remains difficult to predict the ultimate winners and losers at this stage. Her strategy is based on this uncertainty—buying companies with transformation potential at lower prices before the landscape becomes clear. “In the early stages, when outcomes are still unpredictable, this kind of strategy should pay off,” she said.