Leading quantitative firm Lingjun Capital’s latest statement: AI is reshaping the development logic of the asset management industry; its application ceiling is determined by investment philosophy.

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How AI will ultimately affect the asset management industry is worth listening to the perspectives of leading quantitative institutions.

Recently, at the 2nd Hedge Fund Awards Ceremony and Family Office Awards Ceremony, a member of Lingjun Capital’s Hong Kong team gave a speech. The speech made it clear: AI is reshaping the development logic of the asset management industry, and from the perspective of industry transformation pace, the investment research segment will first undergo huge changes.

He further predicted: In the long run, only asset management institutions that can integrate research, trading, risk control, and client service, building a unified smart learning closed loop, can gain a competitive edge in the industry; the overall AI strength may become an important benchmark for distinguishing the competitiveness among quantitative institutions.

The AI revolution in investment research is underway

Lingjun Capital believes that with the rapid iteration of intelligent agents, reasoning models, and multimodal technology, AI has already moved beyond a mere auxiliary tool, embedding deeply into the entire quantitative investment process, becoming an indispensable part of the investment research production system, and is reshaping the logic of asset management industry development.

At this stage, AI technology not only handles basic efficiency-boosting tasks like data processing and material organization, but is also deeply involved in investment signal mining, strategy hypothesis testing, and data backtesting verification, shortening the cycle from investment idea to implementation, and fundamentally reshaping the entire investment research process.

From the perspective of industry transformation, the investment research segment will first see major changes. AI technology can broaden information coverage boundaries, shorten model iteration cycles, and is an important lever for institutions to build differentiated investment insights; at the same time, trading, risk management, and client service segments also benefit from AI upgrades. In long-term competition, only asset management institutions that can integrate research, trading, risk management, and client service into one smart learning closed loop can gain an industry competitive advantage. The overall strength in AI may become an important criterion for distinguishing competitiveness among quantitative institutions.

AI technology is the tool for local institutions to catch up

Lingjun Capital also stated: Compared with top overseas quantitative institutions which have long-standing industry backgrounds, mature infrastructure, and vast experience in investment research, domestic quantitative industry lacks the initial advantage.

But AI technology offers local institutions an opportunity to close the gap in the industry. With machine learning speeding up factor mining, multi-type data analysis, and strategy iteration, it’s possible to make up for years of investment research capabilities accumulated by foreign institutions in a much shorter period.

Now, leading domestic quant firms are continuously improving systems for data pipelines, investment research processes, and model iteration; relying on the unique market structure of A-shares, regulatory environment, and investor behavior, local quant institutions, while drawing on overseas quantitative theories and frameworks, can use AI technology to create exclusive quant systems tailored for the domestic market with more flexible response speed, thus turning technological tools into unique competitive barriers.

Independent, mature investment thinking is key

They further predict that, in the long-term development of the industry, data, computing power, and talent are all standardized resources that can be acquired through the market and do not have long-term scarcity. The truly core, scarce resource that determines the upper limit of institutional development and widens the industry gap is independent and mature investment thinking.

Therefore, the future test for quantitative institutions is whether they can truly establish clear and sustainable investment logic, rely on rigorous research discipline to harness AI technology, and convert that into stable and sustainable excess returns—this is the key for China’s quantitative institutions to stand out in global competition.

Risk Warning and DisclaimerThe market involves risk, and investments should be made with caution. This article does not constitute individual investment advice, nor does it take into account the specific investment objectives, financial situation, or needs of individual users. Users should consider whether any opinions, views, or conclusions in this article fit their particular circumstances. Investments made based on this are at one’s own risk. ```