title: Predicting future values in a multivariate time forecasting LSTM model
body: <p>I am confused on how to predict future results with a time series multivariate LSTM model.</p>
  
  <p>I am trying to build a model for a stock market prediction and I have the following data features</p>
  
  <p>Date
  DailyHighPrice
  DailyLowPrice
  Volume
  ClosePrice</p>
  
  <p>If I train my model on 5 years of data up until today and I want to predict tomorrows ClosePrice, essentially I will need to predict all the data features for tomorrow.  This is where I am confused.... Because if all the data features are dependent on one another how do i predict for one day in the future when all the data features for tomorrow are still unknown?  Does anyone have any example code on how to deal with this issue?</p>