Binary classification for variable outputs
Actually what you need is a linear regression model and not a binary classifier. You can trying to predict continuous variables using a classifier. So we need to build a regression model which predicts continuous variables in a range i.e from -1 to 1.

You can do this with some changes in your code.

model = Sequential()
model.add(Dense(30, input_dim=60, activation='relu')) 
model.add(Dense(1)) 
model.compile(loss='mse', optimizer='adam', metrics=['accuracy'])


So basically we maintain a linear activation function in the output layer for regression.

Tip: 

Instead of accuracy as the metric, use mae or mean absolute error to monitor the model's progress.