In this study, we analyze the impact of input feature selection on the accuracy of short-term 1 price predictions of crude oil futures. We analyze the impact of using 39 different features compared 2 to using the Close price alone. The features we consider are the High, the Low, the Open and the 3 Close (OHLC) prices and the Volume, in addition to a list of technical indicators derived from them. 4 We use a model built from Bi-directional Gated Recurrent Units (BGRUs) for the analysis. In addition, 5 we quantitatively analyze the impact of varying the prediction window on the accuracy of prediction. 6 We find that adding more input features does not improve the accuracy of prediction compared 7 to using the Close price alone. On the contrary, we find evidence that using more input features 8 beyond the close price actually deteriorates the accuracy of prediction. We also find that the accuracy 9 of prediction is quickly lost once the prediction window exceeds about an hour into the future. 10 Therefore, it is recommended to confine the input features to the Close price alone, and limit the 11 prediction window to less than an hour for the purposes of day trade.