Graph Theory for Computer Science

21An Effective Stock Market Price Graph Prediction Model Using Random Forest Algorithm

Santhosh Nithyananda¹, R. Sankar Ganesh², Samyuktha P.S.¹, V. Ramadevi³, J. Sudarvel⁴* and Karthick S.R.⁴

¹Department of Management, University of Technology and Applied Science, Musannah, Muladha, Oman

²Department of Management, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, India

³Department of Management, Sri Krishna College of Engineering and Technology Kuniamuthur, Tamil Nadu, India

⁴Department of Management, Karpagam Academy of Higher Education, Coimbatore, India

Abstract

The trading of stocks on the stock market is a topic that has attracted the interest of investors, academics, and scholars. The challenge that lies ahead is the analysis of the intrinsic non-linear properties that stock market data possesses. The study of market behaviors and the improvement of forecast accuracy have result in the development of a huge category of learning algorithms, which have been optimized with the help of swarm and evolutionary algorithms. The key objective of this paper is stock price prediction utilizing machine learning (ML) algorithm. In this analysis, a hybrid ML model is proposed for the stock prediction. This hybrid model is a graph prediction model that combines a swarm intelligence algorithm, the whale optimization algorithm (WOA), and a machine learning model, random forest (RF). Stock market data from the Bombay Stock Exchange (BSE) is collected ...