A Google search result for "machine learning stock trading":

https://www.udacity.com/course/machine-learning-for-trading-...

well to be honest I never bothered googling that exact term but I was more interested in the details around his deployment of smaller and successful neural networks as part of a portfolio.

Basically, certain neural networks perform better at predicting different factors at different market conditions. You can string them together to get a decent trader, enough to make a profit, but not enough to justify hogging your GPUs.

As in the profit generated isn't enough to sustain the electricity cost of running the GPUs? Are you able to scale up with more initial investment? How much did you invest and what kind of return on investment were you getting?

Not enough to justify using up the compute capabilities of my GPUs since I need them for research.

I averaged a return of 7-13% a year. With less than 1000 in capital, it wasn't very profitable.

I don't see why it shouldn't scale.