Predicting Google Stock Prices Using Machine Learning Models

Abstract

Stock price prediction could help investors decide to sell or buy the stock, which returns and minimizes risk. Precise forecasts can bring substantial financial gains, while unprecise forecasts can bring significant financial losses. During the volatile financial markets, a reliable stock price prediction is a valuable source for traders, investors, and financial analysts. The research uses different models to compare and analyze Google's stock price prediction. The research uses machine learning models to predict Google's stock price. The researcher aims to find the best model to predict the stock price using the Mean Square Error (MSE) result. The researcher chose Google as the topic because of Google's importance in technology and the stock market. The research uses Goggle's stock data from 2016-2021. The data includes opening, closing, and high, and low prices. The study used three methods, linear regression, decision tree, and random forest, to predict Google's stock market price.