Short Term Stock Price Prediction Using Machine Learning

Abstract: This report assesses different machine learning models’accuracies to predict whether a stock will go up or down invalue in a short term. The models that is used is linear regression,LSTM and Elman RNN. These models was trained on historicalprice data from the Nasdaq Stock Exchange. The idea that thereexist a relationship of the price movement of a stock and its futurevalue is called ’techncial analysis’. The result shows that neitherLSTM nor Elman RNN provides any statistical significance ofits accuracy for any of the implementations. Linear regression,provides a significant accuracy for longer time series predictionof the price when trained on 100 days of data and prediction ofits movement after five more days.