Thanks for explaining. I wish you luck my man! Instead of having the bot act, I was just going to have it predict price and then hardcode actions depending on the prediction. Really though, I feel like the net result is the same. There's so many people who have tried this and I'm yet to really hear of a success story, so I doubt there's much money in it unless you're creative with your data sources and your approach. Like finding a correlation somewhere that you can manipulate - for example - selling grain stocks when the weather is predicted to be a certain way for long periods of time.

Why is that the case? What makes it more difficult?

Why'd you settle on RL? My understanding that LSTM was better for this sort of thing. Is that not the case? Sorry I'm fresh with all of this, probably asking a question that doesn't even make sense here. Is LSTM a form of RL? If so, what algorithms did you end up deciding on?