I suspect trading firms have already done this to the maximum extent that it's profitable to do so. I think if you were to integrate LLMs into a trading algorithm, you would need to incorporate more than just signals from the market itself. For example, I hazard a guess you could outperform a model that operates purely on market data with a model that also includes a vector embedding of a selection of key social and news media accounts or other information sources that have historically been difficult to encode until LLMs.
The part people are missing here is that if the trading firms are all doing something, that in itself influences the market.
If they are all giving the LLMs money to invest and the AIs generally buy the same group of stocks, those stocks will go up. As more people attempt the strategy it infuses fresh capital and more importantly signaling to the trading firms there are inflows to these stocks. I think its probably a reflexive loop at this point.
They could have the AI perform paper trading: give it a simulated account but real data. This would make sense to me if it was just a research project. That said, I imagine the more high-tech trading firms started running this research a long time ago and wouldn't be surprised if there were already LLM-based trading bots that could be influencing the market.
"includes a vector embedding of a selection of key social and news media accounts or other information sources that have historically been difficult to encode until LLMs."
Not really. Sentiment analysis in social networks has been around for years. It's probably cheaper to by that analysis and feed it to LLMs than to have LLMs do it.
