Alpha2Fund Claims AI Simplified Trading Strategy Development

CEO of the investment company Alpha2Fund, Jieyun Liu, stated that large language models (LLM) have simplified the creation of programs for analyzing financial markets. According to him, AI helps process data faster and test trading hypotheses, but it does not guarantee returns above the market. Liu spoke on November 2 at the Hong Kong FinTech Week 2026 conference, and on November 12, the company published his key points.
Why Access to AI Does Not Mean Market Advantage
Previously, developing algorithmic strategies required significant engineering resources: specialists set up the software environment, wrote code, and conducted tests. Modern AI tools have lowered the technical entry barrier and accelerated these processes, Liu believes. However, the availability of the same solutions can lead to the spread of similar strategies and increased competition.
The head of Alpha2Fund emphasized that proprietary data, testing results in real trading, and risk management discipline are still needed to find excess returns. In his assessment, the capabilities of models do not replace the ability of specialists to evaluate market patterns.
How Alpha2Fund Uses AI in Research
According to the company, neural networks help teams analyze more data and refine models faster. However, the decision on whether a trading signal is suitable and should be included in the investment portfolio is made by employees. Risk management decisions also remain with humans, and the fund's agents do not execute trades independently.
Similarity of Trading Strategies Intensifies Competition
Liu believes that competition among quantitative funds is shifting from the ability to write a program to the quality of research. At the same time, the availability of AI does not eliminate the costs of computing resources and the need to test strategies in the real market. These assessments reflect the position of the fund's leader, not the results of an independent study on the effectiveness of AI trading.
This material is prepared solely for informational purposes and does not constitute financial advice or a recommendation.





