LSTM Sequential Model question re: ValueError: non-broadcastable output operand with shape doesn't match broadcast shape
The final dense layer's units should be equal to the number of features in your y_train.
Suppose your y_train has shape (11784,5) then dense layer's units should be 5 or if y_train has shape (11784,1), then units should be 1. Model expects final dense layer's units equal to the number of output features.
You have to identify which features you need in input and output.
'open', 'low', 'high' and 'close' and 'volume' - these are your features.
What do you want to predict? Is this a classification or regression problem? What is your problem statement?
Based on these, identify your input and output features.
Put input features in x_train and output features in y_train.
Now, in the final dense layer, you should use units equal to the number of features in y_train.