Baiont’s Feng Ji on AI in Quant Trading
Feng Ji, founder and CEO of Baiont, a top-performing Chinese quant fund, believes that quant managers who don’t adopt AI will be eliminated by the market within three years. In an interview with the Financial Times’ Zijing Wu, Ji explained how his team of young computer scientists is using machine learning to revolutionize the quant trading sector.
The Evolution of Quant Trading in China
Ji described the current landscape of quant trading in China, which began with Chinese traders returning from Wall Street around 2013. “The first wave of quant trading here started with very talented Chinese traders coming back from Wall Street,” Ji said. “We are the second generation and very different. We come from ‘out of the circle’ with zero finance background.”
Applying AI in Quant Trading
Baiont views quant trading as a pure AI task, approaching it holistically with a single foundation model rather than dividing tasks into separate functions. “AI technology has made significant progress in the past 10 years, especially in time series data modeling,” Ji explained. “Whether it’s language or multimedia AI models, fundamentally it’s all about modeling time series data.”
The fund focuses on short-term trading, from minutes to hours, where AI excels at predicting price fluctuations based on trading data. “We mainly rely on trading data. The core of short-term price fluctuation is driven by trading data,” Ji said.
Competitive Advantage Through AI
Ji attributes Baiont’s success to its holistic approach and heavy investment in AI technology. “Instead of hiring 50 people to find factors, we use 100 GPUs and one person who writes the algorithm for factor finding. The result is even better and much faster,” he explained.
With about 30 employees, Baiont manages close to RMB 7 billion ($970 million). Two-thirds of the team focus on research, improving algorithms and their foundation model.
Attracting Top Talent
Baiont’s team includes 13 gold medalists from computer science competitions, creating a “density” of talent likely higher than any tech giant. Ji believes quant trading attracts top machine learning talent, with 80% of the world’s top talents in Wall Street and 20% in Silicon Valley.
The fund’s success has allowed for “technology spillover,” enabling the team to explore other areas of interest. “Making a lot of money also means the team has the luxury to branch out to do things they are more interested in pursuing,” Ji noted.
Future Plans
Baiont aims to become a world-leading AI-native quant fund from China, currently trading mainly in Chinese markets but looking to expand into key overseas markets. In the long term, Ji wants to build a computing company, exploring other potential areas for their technology.
“In the long run, we would like to build a computing company. There are many potential areas we are excited about, where we could spill over our technology,” Ji said.
The interview concluded with Ji highlighting the competitive edge provided by China’s education system, which produces talented engineers and algorithm innovators. “China has a larger pool of such talents thanks to our education system with a stronger focus on science and technology,” he stated.
