If you've ever read a blog on trading when LSTMs came out, you'd have seen all sorts of weird stuff with predicting the price at t+1 on a very bad train/test split, where the author would usually say "it predicts t+1 with 99% accuracy compared to t", and the graph would be an exact copy with a t+1 offset.

So eye-balling the graph looks great, almost perfect even, until you realize that in real-time the model would've predicted yesterday's high on today's market crash and you'd have lost everything.

if you feed in price i.e. 280.1, 281.5, 281.9 ... you are going to get some pretty good looking results when it comes to predicting the next days price (t+1) with a margin of +/- a percent or so.