China's Quant Fund AUM Doubles as AI Strategies Attract Over 2.6 Trillion Yuan
Alina Collins
China's quant-fund assets doubled in under a year to over ¥2.6 trillion. Last year, quant long-equity strategies returned 44.7% — beating active stock-pickers by more than 20 percentage points — and money is now migrating from human-driven to machine-driven investing at scale.
How fast is the money pouring in?
Ubiquant (宽邦), a top quant manager, raised ¥2.6 billion for a new fund in May — in under two hours.
A Shenzhen-based firm, Chengqi Asset, saw one product snapped up for over ¥100 million in seconds.
This means → investors are no longer comparing funds one by one; the mindset is "grab any quant allocation first." Capital migration has shifted from cautious to stampede.
Why is quant crushing active stock-picking?
Last year, quant long-equity strategies returned 44.7%, outperforming active peers by more than 20 percentage points — the widest gap since 2021.
In plain terms = machines scan thousands of stocks for patterns simultaneously; human analysts simply cannot match that breadth or speed.
BigQuant.cn COO Chen Xu said: "Quant's breadth across thousands of stocks has overtaken active management's edge in research depth."
How big is the new-product boom?
Industrial Securities reported that over 6,296 new quant products launched last year, doubling year-on-year.
Quant accounted for 46% of all new hedge-fund launches; among top managers' newly registered products, quant exceeded 80%.
This means → quant is no longer a hedge-fund niche — it is approaching half the industry.
How is AI building a moat around the leaders?
Guolian Minsheng Securities noted that the investment logic has shifted from "pick quant" to "pick the quant with the strongest AI," naturally concentrating capital at the top.
Ningbo Lingjun Investment is a case study: after a 2024 penalty for concentrated selling, it upgraded algo risk controls and layered in short-term signals. Post-overhaul, it led top quant rankings last year with an average return above 70%.
Lingjun now manages ¥40–50 billion and plans to add ¥20–40 billion more. This reflects a self-reinforcing loop: performance attracts scale, and scale funds more AI investment.
Is there a path forward for active stock-pickers?
Shanghai Minority Asset spent five years shifting from pure active picking to an AI-agent — a program that autonomously discovers investment factors — driven model, training it on the firm's core thesis that "excess returns come from the majority's cognitive biases."
Founder Zhou Liang said: "The moat that once protected us has become a wall. Evolution is not a choice — it is survival."
In plain terms = funds that do not transform face more than underperformance; investors will simply abandon them — the money keeps moving.
Where is the suspense in this reshaping?
Top quant firms' AI moats are deepening; whether smaller quants can keep pace with the technology cycle is the first unknown.
Whether active funds' AI transformations will actually work is the second unknown.
This means → the shakeout is far from over: concentration toward the top will most likely continue, and both smaller quants and traditional active managers are racing against time.
Content is for reference only, not financial advice.