The aim of this paper is to achieve two goals. Firstly, build and apply a convolutional neural
network to make predictions on historical data of the Vanguard Industrials ETF (VIS) in the
form of Buy, Hold and Sell signals. Secondly, making comparisons among different indus triesin order to derive potential performance deviations. By using three image encoding tech niques and a randomly generated model for comparison purposes, some promising results
have been achieved. Nevertheless, several classic strategies and the market performance
could not be beaten, mainly because model predictions for Buy and Sell signals showed
weaknesses