Zhong Ou Fund Marks 20 Years With ‘Super Factory’ Model, Flags Debt-Deleveraging Timeline and Tech Reset

Zhong Ou Fund’s 20-Year Journey and the ‘Super Factory’ Concept

Zhong Ou Fund Management marked its 20th anniversary by publicly detailing an operational overhaul it calls the “Super Factory” – a bid to weave specialist expertise, industrial-grade processes and AI-driven tools into every aspect of its investment engine. At the celebratory event, General Manager Liu Jianping disclosed that the firm had grown to manage RMB 923.7 billion in assets as of mid-2026, serving nearly 98.83 million clients, and placed second among large Chinese fund houses for active equity absolute returns over a decade, according to a Guotai Hainan Securities ranking.

The Super Factory framework, introduced in 2023 and now central to the firm’s identity, breaks down into three layers: specialisation aimed at sharper investment insights; industrialisation that automates portfolio construction and trading; and digitalisation that embeds large language models and quantitative tools into daily research workflows. Liu described the anniversary as “a new starting line” rather than an endpoint, arguing that governance reform in 2014 – when the firm became one of the first in China to modernise its ownership and incentive structures – laid the foundation for the talent-driven growth he now says is the company’s greatest asset.

How AI, Process and Specialisation Are Redrawing Active Management

A Smart Assembly Line for Multi-Asset and Quant

Huang Hua, chair of the multi-asset investment committee, revealed that five portfolio templates and five core strategies are already being stitched together with a high degree of automation. Where the old workflow required 30–40 manual orders a day, an in-house system now proportionally allocates across hundreds of stocks and bonds, cutting execution time dramatically. Qu Jing, who leads quantitative investing, described a structure in which coding-savvy researchers no longer wait for dedicated IT support; they build and test strategies directly within an AI framework.

Where AI Has Limits – and Why That Matters

For all the efficiency gains, Ren Fei, head of equity research, stressed that AI “cannot replace the final judgement call.” He argued that current models lack the corpus to assess a company’s 5–10‑year value trajectory and tend to echo the analyst’s own biases once a hint of direction is given. The real moat, in his view, remains the ability to identify the two‑ or three‑year industrial themes that will dominate the economy – a skill he admitted is becoming scarcer precisely because AI’s speed tempts investors to skip long‑term thinking.

Bond Strategy and the Deleveraging Clock

Fixed-income head Wang Shen told the audience that the household debt‑deleveraging cycle probably will not conclude until late 2027 or the first half of 2028, meaning the bottom of the property cycle may still be some way off. He attributed the sharp bond‑market correction in the second half of 2025 to mispricing when the 10‑year government bond yield dropped below banks’ funding costs; after an overshoot early this year, pricing has returned to a reasonable range. Wang expects banks’ liability costs to drift lower by year‑end, and provided monetary policy stays loose, pure-debt products can still offer stable coupon returns – albeit lower than in the first half.

Tech Sector: A Leverage‑Driven Sell‑Off, Not a Broken Thesis

Du Houliang, from the firm’s technology team, characterised the recent pullback in Chinese tech stocks as a consequence of forced liquidations by highly leveraged offshore funds, rather than a reversal of the underlying industrial logic. He pointed to real-world AI adoption – programming tasks that already deliver material labour‑cost savings, medical‑imaging startups winning large contracts with top pharmaceutical companies, and penetration into cybersecurity, financial and legal verticals – as evidence that the demand pipeline is broadening. Du noted that some AI‑related names are now trading at relatively low valuations, but warned that a low multiple alone is no reason to buy; the mismatch between compute supply and token demand is unlikely to resolve quickly, so monitoring order delivery and capacity expansion remains critical.

What Investors Should Watch After Zhong Ou’s 20-Year Reset

• For buyers of Zhong Ou’s bond funds: the in‑house view is that net returns in the second half will be below those of the first half. Investors recalibrating return expectations now are less likely to react abruptly to softer pay‑outs.
• For those weighing a tech‑sector allocation: the sell‑off was largely technical rather than fundamental, and valuations have eased. However, Du’s caution – that cheapness alone does not guarantee a rebound and that supply‑demand dynamics still need watching – suggests that due‑diligence on individual names’ order books is more important than chasing a theme.
• For industry peers: Zhong Ou’s experience indicates that wiring AI into the investment workflow can compress costs and improve execution speed, but the human edge in long‑horizon stock‑picking remains intact. Building a system that combines the two – not treating AI as a black box – appears to be the practical path.