I am currently building a LSTM model to predict only the daily Open price of a stock.
Is there a difference in the prediction of the Opening price if I include other parallel series (High, Low, Close, technical indicators etc) using a Multiple Parallel Series Model compared to using a univariate LSTM only on Open prices?
In other words, a Multiple Parallel Series LSTM with N series, just runs N different univariate LSTMs?
Thank you in advance!
The code for Multiple Parallel Series LSTM is from this tutorial: https://machinelearningmastery.com/how-to-develop-lstm-models-for-time-series-forecasting/