Forecasting Foreign Exchange with Neural Network - Lag in Prediction
A couple of ways to improve your design:


Consider a different normalization: The sigmoid function will attenuate large moves.  It is likely precisely these large non-linear moves that attracted you to using neural networks in the first place.  Why remove them?  A simple whitening of the data may be better
As pointed out by Nima, your model can only predict what is knowable from the data you give it.  If you are only fitting on data using historical prices, it will only give you what is predictable from them.  Things such as news events / earnings surprises / holidays / option market flows will not be fed into your model.  Consider adding these series as well.
Lots more historical data.  Neural networks often require very large sample sizes because they are trying to estimate a very large parameter space.  Although, more data doesn't always imply more information, this will still likely help.
Experiment with different network architectures.  The number of layers / size of the layers / different gradient decent algorithms / different activation functions / dropout etc..