Using Neural Network to Predict Stock Price: Using SP500 as an example
The study uses multilayer neural network to predict the stock price and tests whether the stimulated prediction is aligned with the actual stock returns through mean squared error (MSE) value. Acquired from Yahoo Finance, S&P 500 stock data ranged from January 2002 to July 2019 are the sample for the study. Through comparing the MSE value obtained from multilayer neural network with those of other machine learning forecasting methods, random forest regression, gradient boosting, and support vector machine (SVM), the results demonstrate the former method to be the most effective.
Keywords - Machine Learning, Mean Squared Error, Multilayer Neural Networks, Stock Price Prediction