Research on the Stock Price Prediction Using Machine Learning

Abstract

Stock price prediction is a complex and challenging problem that has attracted the attention of investors and researchers for decades. In recent years, machine learning algorithms have become powerful tools for predicting stock prices. This paper first introduces four popular machine learning algorithms used for stock price prediction which are linear regression, support vector machines, artificial neural networks and long short-term memory. In addition, applications and potential challenges of stock price prediction using machine learning are examined. Overall, this paper provides a comprehensive overview of ML-based models for stock price prediction and highlights the potential benefits and limitations of these models for financial researchers and artificial intelligence developers.