Thread

1. gyanchawdhary · 1789662689 · focus · HN ↗

   At the risk of sounding extremely naieve i have a question for the Wall St / quant / HFT folks lurking here ... but how hard would it actually be to brute force the math/algos behind Medallion Fund (or something in that general class) or even some of the average quant funds

   I know it’s not just the math but execution, infrastructure, risk management, data, colocation (if ur an HFT) etc ... but LLMs seem like a pretty powerful apparatus for running experiments that .. a few years ago would have required fairly deep multidisplinary skills across coding .. stats .. and math ..

   So assuming you have decent intuition for ideas .. how difficult would it actually be to reverseengineer / rediscover some of the underlying stuff?

   1. arn3n · 1789664223 · focus · HN ↗

      It’s actually really easy to make models that can predict “will the market move up or down in the next X microseconds” that score above 50% accuracy. It’s just that there are so many ways to do it that overfitting is practically guaranteed and most models don’t work when actually trading against the market, which reacts to you. Doing those trades well requires more understanding of the underlying mechanisms, not to mention access to data sources that the public simply doesn’t have.

Unofficial Hacker News client; not affiliated with Y Combinator.