But:
The average error means that on average, predictions are off by that amount. If you have the neural network make predictions at every point in bitstamp's history and average how far off it was, you will get those numbers that I have put above the graphs.
There could be a logical flaw. Think about it. The more neurons you take, the better you can adjust it to the history. Take 1000 neurons and a big amount of computing power and you can lower the average error to 0.1%. But do you really think you can predict the future better?
Did you ever test your model? I don't mean the error you produce by taking the learning data. I mean the actual prediction for an at that point unknown future. For example: You are prediction 489.2$ for tomorrow 4pm GMT. Now save that prediction and compare with the real value tomorrow.
I think then you get a much larger number than 1.3%