What is the optimal input and target variables for forecasting with a deep neural network on daily stock/index data? More specifically I’m training a temporal convolutional network, but a more general answer is also appreciated.
Are normalized closing prices, daily returns, or nominal daily changes better inputs? For target variables, which is more interesting: nominal price, returns, or daily changes?
Are there any literature references on these topics?