Stock market prediction is well known for being an ambiguous and hard challenge that many investors and data scientists attempt. Its wealth of information and factors allow for multiple neural networks and algorithms to be designed around it. By mixing training algorithms and incorporating them into an ensemble neural network, it is possible to have greater accuracy than using individual factors. Using different investing strategies allows the neural network to have a better understanding of the factors that affect a certain stock. Predictions made through this method have incremental accuracy based on the factors analyzed and their relevance. A mobile application is also explored to deliver and communicate these insights in a way that an investor would be convinced by these predictions.