One of the trickiest challenges for any honest investor is trying to work out whether they are lucky or smart. Is their successful trading strategy the equivalent of a coin toss coming up heads five times in a row? Or is it the result of superior insight or execution? Human nature (and fee structures) being what they are, most investors prefer the latter explanation. In truth, it is often hard to tell.
In an attempt to dial up the smart factor and dial down luck, many investors have resorted to technology. Public market quantitative traders, in particular, have long used mathematical computation and machine-learning systems to spot significant correlations in market data, correct for human bias and execute trades at lightning speed.
This has taken extreme form at Baiont, a Chinese quant fund that hires “nerds and geniuses” with top computer science expertise and zero finance experience. Just as generative artificial intelligence models, such as ChatGPT, are trained to complete the next word in a sentence, they can also predict very short-term price movements, Baiont asserts. “We regard it as a pure AI task,” Feng Ji, Baiont’s founder, told the FT.