The Quantitative Four Kings are about to break through the 100 billion mark.

Ask AI · How AI Technology Is Reshaping the Competitive Landscape of Quantitative Investing?

21st Century Business Herald Li Yu

Quantitative private equity funds are once again experiencing an expansion cycle. QIML’s latest statistics show that by the end of the first quarter of 2026, the combined scale of the “Big Four” quant firms—Huanfang Quant, Jiukun Investment, Mingsun Investment, and Yanfu Investment—has collectively surpassed 80 billion yuan, entering the 80-90 billion yuan range, significantly up from the 70-80 billion yuan range at the end of last year, just a step away from the 100 billion yuan mark.

Another set of data indicates that the number of domestic quant private funds with assets of over 70B yuan has reached 61, an increase of 9 compared to the end of 2025. The industry’s overall management scale (AUM), conservatively estimated, has exceeded 1.8 trillion yuan, a substantial increase of nearly 350 billion yuan from the end of Q4 2025.

On the product issuance side, leading institutions demonstrate strong capital-raising capabilities. Mingsun Investment, Pingfang and Investment, Black Wing Asset, Yanfu Investment, Wanyan Asset, Longqi Technology, Kuande Investment, among others, have each registered over 30 products in the first quarter, leading the industry.

While the scale is rapidly expanding, performance pressures are emerging. Influenced by the intense turbulence in global financial markets triggered by the Middle East conflict, some top quant firms’ macro strategies have experienced nearly 15% drawdowns, with some products even showing negative excess returns year-to-date.

“The temporary pullback in macro strategies is a short-term disturbance, and there is hope for recovery,” said a leading quant professional in Shanghai. “Maintaining excess returns amid continuous scale expansion is the core challenge for quant firms.”

Industry competition has quietly shifted its focus. Zhou Xiaoxiao, an analyst at China International Capital Corporation, pointed out that quant competition is moving from early-stage technical battles—such as faster data, lower latency, and more powerful single models—to the development of systemic capabilities centered around A. In the future, the “mid-frequency range,” which balances data richness and latency tolerance, will become the battlefield for AI technology deployment, prompting a reassessment of core quant competitiveness.

The momentum of expansion in quant funds is not limited to the top tier; the entire industry echelon is showing signs of upward movement and rapid reshuffling.

By the end of Q1 2026, the number of domestic quant private funds with assets over 18k yuan increased to 61, up by 9 from the end of 2025. Among them, institutions like Banqi Private Fund, Hongxi Fund, Kuaikuai Private Fund, Luoshu Investment, Youmeili Investment, and others have successfully broken through, newly joining the “billion-yuan club,” injecting fresh vitality into the industry.

Looking at the distribution of tiers, industry stratification is becoming clearer. Chengqi Fund has entered the 600-60B yuan range, Black Wing Asset and Wanyan Asset have crossed into the 500-70B yuan range, Maoyuan Quantitative and Tianyan Capital are in the 400-50B yuan range, and Evolutionary Theory Asset has entered the 300-60B yuan tier.

More notably, some institutions have achieved “leapfrog” growth. Ming Stone Fund jumped directly from the 200-40B yuan range into the 500-50B yuan tier, crossing three levels, while Qianxiang Investment and Longqi Technology also advanced two levels, becoming highlights of the industry’s expansion in Q1.

Behind this scale surge is the steady rise of the entire industry’s management volume and the continued hotness of product issuance. Conservative estimates suggest that the overall management scale (AUM) of the domestic quant private fund industry has surpassed 1.8 trillion yuan in Q1, a significant increase of nearly 350 billion yuan from the end of 2025.

The resonance of multiple capital sources has become the core driving force behind this round of quant scale expansion. Industry insiders note that the influx of funds in Q1 shows clear institutionalization and diversification trends, including capital from high-net-worth clients and family offices; funds from banks, private banks, third-party distributors; and allocations from insurance companies and securities firms’ asset management arms.

Many private fund professionals believe that the rapid growth of quant fund sizes is attributable to investors’ demand for stable returns and the performance of quant strategies in volatile markets.

Data from Private Equity Data Network shows that the impressive performance of quant strategies in 2025 laid a solid foundation for subsequent scale expansion. Nearly a thousand index-enhanced strategy products with performance records posted an average return of 45.08%, with an average excess return of 16.75%. Products with positive excess returns accounted for nearly 90%, fully demonstrating the strong ability of quant strategies to generate excess returns.

The performance of leading institutions is even more remarkable. Among 45 top-performing billion-yuan quant private funds with performance data, the average return was 37.61%, with all achieving positive returns, significantly outperforming the overall performance level of billion-yuan private funds. From the distribution of returns, industry differentiation is evident: four institutions had returns within 20%, 34 institutions ranged from 20% to 49.99%, and seven institutions exceeded 50%, showcasing the core competitiveness of top quant firms.

However, this performance differentiation reversed in Q1 2026. Influenced by the global financial market turbulence caused by the Middle East conflict, major A-share indices experienced notable declines. In this context, some top quant firms’ macro strategies faced nearly 15% drawdowns, with some products even showing negative excess returns for the year. Quant professionals say that the main causes of this excess drawdown include market mean reversion, crowded strategies, and external shocks.

“Although the temporary retreat of macro strategies is a short-term disturbance and is expected to recover, a deeper challenge looms: after rapid scale expansion, the decay of excess returns is highly probable,” said a quant expert. “This forces quant firms to continuously explore new factors and seek more diverse sources of excess returns. In Shanghai, a leading quant professional believes that maintaining excess returns amid ongoing scale growth is the core test for quant institutions.”

The focus of competition in the quant industry once centered on discovering stronger single predictive signals or faster hardware responses. However, as large models and multi-agent technologies gradually become practical, this logic is undergoing a fundamental shift.

Zhou Xiaoxiao believes that the core competitiveness of current quant firms is no longer limited to high-frequency factors or innovations in deep learning models but depends on whether they can leverage AI to build systems that integrate data, models, trading execution, and risk control into a closed loop. The essence of this competition is about who has higher research productivity and stronger system self-evolution capabilities.

Several quant professionals share similar views: “Future competition will depend more on comprehensive capabilities,” one said, “every link and detail involves investments in hardware and software.”

Behind this shift is a deep structural change in the sources of Alpha. Traditional quant advantages—“technological Alpha”—are mainly based on statistical pattern mining of price-volume data and structured financial indicators. The addition of large language models and intelligent agent technologies offers opportunities for quant strategies to expand toward “cognitive Alpha.”

It’s important to clarify that “Cognitive Alpha” and “Technological Alpha” are additive. This combination is gradually narrowing the gap between quant research and fundamental analysis, enabling machines to “understand” market sentiment and fundamentals.

In the environment of continuous new media development, the speed of information generation, dissemination, and fermentation has accelerated significantly, market rotations are speeding up, and the half-life of signals is shortening. This imposes higher demands on research and investment systems. Zhou Xiaoxiao believes that in an era of tool equality, integrating top-tier AI infrastructure with deep data assets, portfolio management, and risk control capabilities of quant firms is essential to continuously generate Alpha in this rapidly changing market.