Exploiting LightGBM Ensemble Method for Stock Prediction

Abstract

This paper leverages the LightGBM Ensemble Method to predict stock prices. First, the time features are from the dates and these generated features are used to build a regression model. Experiments are performed on the Tesla and the Coca Cola stock historical data to show the effectiveness of the method in predicting stock prices