App for predicting stock price fluctuation with neural network

Abstract

Prediction of stock price fluctuations with the use of Neural Network, mainly the LSTM Model. Datasets from the SPY Index Fund is used to train the LSTM Model with cleaning of the data. The data is separated into individual days of the week to be trained into the LSTM Model to predict each day of the week. This method of parsing dataset to the days of the week yield promising results, which is then translated and seen from the application made after. Using the model, the application will also be able to trade automatically with the backend system in place.