One thing I always think about whenever someone talks about solving investment is "and then what?"
Say there's a crystal ball, wouldn't everyone use such crystal ball? Wouldn't crystal ball become illegal? Wouldn't crystal ball nullify the effects of things?
What am I missing, can someone from this field educate me on how this stuff scales?
I'm skeptical frontier LLMs can actually do well (e.g. alpha 5%+) without fine-tuning, especially on historical market data. Presumably you support fine-tuned models?
cofounder here - LLMs can do some model training, they train on ML competition data after all. But they do struggle with low signal to noise ratio of market data. But that’s exactly what our environments will teach.
We do a 2 step anonymisation:
1. Mask all symbols, timestamps etc. So the agents cannot infer the assets/time periods.
2. Mathematically transform numerical values and returns. E.g. the market return targets are not the raw market returns, but neutralised and manipulated. So even the agents have certain bullish/bearish biases, it cannot make use of it, as we use the transformed values.
ah i thought so, interesting. I think the challenge is to do 2 while still keeping it realistic, which actually gets very close to synthetic data generation.
we do affine transformations of the data, so all return/ pnl measures are still the same as with untransformed data. The transformation doesn’t change the conditional distribution of the data, which is what alphas ultimately measure
Say there's a crystal ball, wouldn't everyone use such crystal ball? Wouldn't crystal ball become illegal? Wouldn't crystal ball nullify the effects of things?
What am I missing, can someone from this field educate me on how this stuff scales?
In addition, we did not observe such behaviour in our traces. An example: https://hub.harborframework.com/jobs/af0299f9-a3bb-44ea-8ced...