Sequence to Sequence LSTM

I am training a stacked LSTM that takes as input a sequence [1,...,n] and outputs a sequence [1,...,m], for m<n, to predict stock prices.

Upon training the model with multiple architecture nuances, I am getting the same result: the yhat sequences all have the same pattern.

What might be causing this?

*All input columns are z-scored