Should I concat multiple stock timeseries datasets into one?
I would suggest option two. Because this way your model would have the chance to learn something for one stock, which it can apply for other stocks as well. If you provide the type of stock as an input feature, it should be able to distinguish between the specialities which only occure within one stock and the common things. So it is kind of able to transfer knowledge from one stock to the other.
But at the same time, I would suggest to try out both and choose whatever performs the best. This way you can also justify your choice in the end.